observational research business example

10 Observational Research Examples

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

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Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

Observational research involves observing the actions of people or animals, usually in their natural environments.

For example, Jane Goodall famously observed chimpanzees in the wild and reported on their group behaviors. Similarly, many educational researchers will conduct observations in classrooms to gain insights into how children learn.

Examples of Observational Research

1. jane goodall’s research.

Jane Goodall is famous for her discovery that chimpanzees use tools. It is one of the most remarkable findings in psychology and anthropology .

Her primary method of study involved simply entering the natural habitat of her research subjects, sitting down with pencil and paper, and making detailed notes of what she observed.

Those observations were later organized and transformed into research papers that provided the world with amazing insights into animal behavior.

When she first discovered that chimpanzees use twigs to “fish” for termites, it was absolutely stunning. The renowned Louis Leakey proclaimed: “we must now redefine tool, redefine man, or accept chimps as humans.”

2. Linguistic Development of Children

Answering a question like, “how do children learn to speak,” can only be answered by observing young children at home.

By the time kids get to first grade, their language skills have already become well-developed, with a vocabulary of thousands of words and the ability to use relatively complex sentences.

Therefore, a researcher has to conduct their study in the child’s home environment. This typically involves having a trained data collector sit in a corner of a room and take detailed notes about what and how parents speak to their child.

Those observations are later classified in a way that they can be converted into quantifiable measures for statistical analysis.

For example, the data might be coded in terms of how many words the parents spoke, degree of sentence complexity, or emotional dynamic of being encouraging or critical. When the data is analyzed, it might reveal how patterns of parental comments are linked to the child’s level of linguistic development.

Related Article: 15 Action Research Examples

3. Consumer Product Design

Before Apple releases a new product to the market, they conduct extensive analyses of how the product will be perceived and used by consumers.

The company wants to know what kind of experience the consumer will have when using the product. Is the interface user-friendly and smooth? Does it fit comfortably in a person’s hand?

Is the overall experience pleasant?

So, the company will arrange for groups of prospective customers come to the lab and simply use the next iteration of one of their great products. That lab will absolutely contain a two-way mirror and a team of trained observers sitting behind it, taking detailed notes of what the test groups are doing. The groups might even be video recorded so their behavior can be observed again and again.

That will be followed by a focus group discussion , maybe a survey or two, and possibly some one-on-one interviews.

4. Satellite Images of Walmart

Observational research can even make some people millions of dollars. For example, a report by NPR describes how stock market analysts observe Walmart parking lots to predict the company’s earnings.

The analysts purchase satellite images of selected parking lots across the country, maybe even worldwide. That data is combined with what they know about customer purchasing habits, broken down by time of day and geographic region.

Over time, a detailed set of calculations are performed that allows the analysts to predict the company’s earnings with a remarkable degree of accuracy .

This kind of observational research can result in substantial profits.

5. Spying on Farms

Similar to the example above, observational research can also be implemented to study agriculture and farming.

By using infrared imaging software from satellites, some companies can observe crops across the globe. The images provide measures of chlorophyll absorption and moisture content, which can then be used to predict yields. Those images also allow analysts to simply count the number of acres being planted for specific crops across the globe.

In commodities such as wheat and corn, that prediction can lead to huge profits in the futures markets.

It’s an interesting application of observational research with serious monetary implications.

6. Decision-making Group Dynamics

When large corporations make big decisions, it can have serious consequences to the company’s profitability, or even survival.

Therefore, having a deep understanding of decision-making processes is essential. Although most of us think that we are quite rational in how we process information and formulate a solution, as it turns out, that’s not entirely true.

Decades of psychological research has focused on the function of statements that people make to each other during meetings. For example, there are task-masters, harmonizers, jokers, and others that are not involved at all.

A typical study involves having professional, trained observers watch a meeting transpire, either from a two-way mirror, by sitting-in on the meeting at the side, or observing through CCTV.

By tracking who says what to whom, and the type of statements being made, researchers can identify weaknesses and inefficiencies in how a particular group engages the decision-making process.

See More: Decision-Making Examples

7. Case Studies

A case study is an in-depth examination of one particular person. It is a form of observational research that involves the researcher spending a great deal of time with a single individual to gain a very detailed understanding of their behavior.

The researcher may take extensive notes, conduct interviews with the individual, or take video recordings of behavior for further study.

Case studies give a level of detailed information that is not available when studying large groups of people. That level of detail can often provide insights into a phenomenon that could lead to the development of a new theory or help a researcher identify new areas of research.

Researchers sometimes have no choice but to conduct a case study in situations in which the phenomenon under study is “rare and unusual” (Lee & Saunders, 2017). Because the condition is so uncommon, it is impossible to find a large enough sample of cases to study with quantitative methods.

Go Deeper: Pros and Cons of Case Study Research

8. Infant Attachment

One of the first studies on infant attachment utilized an observational research methodology . Mary Ainsworth went to Uganda in 1954 to study maternal practices and mother/infant bonding.

Ainsworth visited the homes of 26 families on a bi-monthly basis for 2 years, taking detailed notes and interviewing the mothers regarding their parenting practices.

Her notes were then turned into academic papers and formed the basis for the Strange Situations test that she developed for the laboratory setting.

The Strange Situations test consists of 8 situations, each one lasting no more than a few minutes. Trained observers are stationed behind a two-way mirror and have been trained to make systematic observations of the baby’s actions in each situation.

9. Ethnographic Research

Ethnography is a type of observational research where the researcher becomes part of a particular group or society.

The researcher’s role as data collector is hidden and they attempt to immerse themselves in the community as a regular member of the group.

By being a part of the group and keeping one’s purpose hidden, the researcher can observe the natural behavior of the members up-close. The group will behave as they would naturally and treat the researcher as if they were just another member. This can lead to insights into the group dynamics , beliefs, customs and rituals that could never be studied otherwise.

10. Time and Motion Studies

Time and motion studies involve observing work processes in the work environment. The goal is to make procedures more efficient, which can involve reducing the number of movements needed to complete a task.

Reducing the movements necessary to complete a task increases efficiency, and therefore improves productivity. A time and motion study can also identify safety issues that may cause harm to workers, and thereby help create a safer work environment.

The two most famous early pioneers of this type of observational research are Frank and Lillian Gilbreth.

Lilian was a psychologist that began to study the bricklayers of her husband Frank’s construction company. Together, they figured out a way to reduce the number of movements needed to lay bricks from 18 to 4 (see original video footage here ).

The couple became quite famous for their work during the industrial revolution and

Lillian became the only psychologist to appear on a postage stamp (in 1884).

Why do Observational Research?

Psychologists and anthropologists employ this methodology because:

Psychologists find that studying people in a laboratory setting is very artificial. People often change their behavior if they know it is going to be analyzed by a psychologist later.
Anthropologists often study unique cultures and indigenous peoples that have little contact with modern society. They often live in remote regions of the world, so, observing their behavior in a natural setting may be the only option.
In animal studies , there are lots of interesting phenomenon that simply cannot be observed in a laboratory, such as foraging behavior or mate selection. Therefore, observational research is the best and only option available.

Read Also: Difference Between Observation and Inference

Observational research is an incredibly useful way to collect data on a phenomenon that simply can’t be observed in a lab setting. This can provide insights into human behavior that could never be revealed in an experiment (see: experimental vs observational research ).

Researchers employ observational research methodologies when they travel to remote regions of the world to study indigenous people, try to understand how parental interactions affect a child’s language development, or how animals survive in their natural habitats.

On the business side, observational research is used to understand how products are perceived by customers, how groups make important decisions that affect profits, or make economic predictions that can lead to huge monetary gains.

Ainsworth, M. D. S. (1967). Infancy in Uganda . Baltimore: Johns Hopkins University Press.

Ainsworth, M. D. S., Blehar, M., Waters, E., & Wall, S. (1978). Patterns of attachment: A

psychological study of the Strange Situation. Hillsdale: Erlbaum.

Crowe, S., Cresswell, K., Robertson, A., Huby, G., Avery, A., & Sheikh, A. (2011). The case study approach. BMC Medical Research Methodology , 11 , 100. https://doi.org/10.1186/1471-2288-11-100

d’Apice, K., Latham, R., & Stumm, S. (2019). A naturalistic home observational approach to children’s language, cognition, and behavior. Developmental Psychology, 55 (7),1414-1427. https://doi.org/10.1037/dev0000733

Lee, B., & Saunders, M. N. K. (2017). Conducting Case Study Research for Business and Management Students. SAGE Publications.

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What is Observational Research in Marketing?

Observational research is the wide-ranging set of methods businesses use to collect information by directly or indirectly “watching” consumers act in natural (and sometimes planned) environments. As such, it’s used primarily in B2C contexts. What observational research ultimately offers is behavioral data … but it measures behavior directly , rather than relying on consumers’ (sometimes inaccurate) self-reporting. While the subject of observational research might know that data is being collected, they aren’t explicitly involved in collecting it (by filling out survey answers, for example). Often, in fact, there’s no interaction whatsoever—which is why it can be one of the more unobtrusive market research methods out there.

The “observer” takes one of three forms: human, software, or mechanical device. Human observation may be as simple as walking into a brick-and-mortar store and watching consumers pick up your product and your competitor’s product and compare them. Online observation includes tracking devices and web metrics to map user and consumer behavior; Google Analytics and heatmaps fall into this category. Mechanical observation entails the use of devices—such as cameras or footfall counters—that track consumer behavior in the non-virtual world.

You’ll note that some of these techniques are more sophisticated than others; and their availability may depend upon your financial resources. But the field is vast enough to support sole proprietorships and enterprises alike.

Observational Research Methods

Here are some methods to consider when deciding what “observation” will mean for your market research question:

Natural v. contrived observation . In natural observation, subjects are studied in “real life” circumstances and environments. They may or may not know that they’re being observed. In contrived observation, subjects are studied in controlled settings (research labs, for example), and know that they’re being observed. While natural observation can be time-consuming, it often produces better results: Unnatural settings and awareness of observation ( the Hawthorne effect ) can both alter subjects’ behavior.
Direct v. indirect observation . In direct observation, researchers watch subjects as the behavior is occurring (how many consumers purchase drinks at an event, for example). Indirect observation examines the results of the behavior, rather than the behavior itself (receipts for drink sales or the number of empty cups in nearby trash cans).
Disguised v. open observation . In disguised (or covert) observation, the subject doesn’t know they’re being observed: Think hidden cameras, one-way mirrors, or online tracking. In open (or overt) observation, they do While the latter runs the risk of altering consumer behavior, it also allows researchers to interact with consumers during or after the study—in effect creating a hybrid of observational research and in-depth interviews.
Structured v. unstructured observation . In structured observation, researchers clearly define what behaviors will be observed, and the study focuses on that set of predefined, pre-categorized behaviors. In unstructured observation, researchers attempt to capture everything : typical and divergent behaviors, contextual details, and so on. While the “subject” of observation is less defined in unstructured observation, it allows you to better perceive the unexpected. (And believe us when we say… consumers will surprise you.)

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Pros and Cons of Observational Research

We mentioned some advantages and disadvantages of the above methods. But there are some pros and cons that many observational techniques share in common; and if you’re wondering whether these approaches are right for you, they’re worth considering.

Advantages of Observational Research:

Humans often say one thing, but do another: Consumers may not understand their motivations very well, or can’t be certain about how they’d react in a situation until they’re actually faced with it. What’s more, while other forms of primary research leave room for recall error (respondents may not remember the factors that contributed to a purchase decision, for example), observational research collects information as the action is taking place—so nothing gets lost in the time gap. In other words, observational research can offer a more accurate reflection of “the truth.”
There are certain types of questions that only observational techniques can answer. The number of shoppers who enter a store on a given day, the image or copy that catches visitors’ eyes first on a web page, or what products children are most interested in simply can’t be answered by surveys or interviews.
In other forms of primary market research, you run the risk of question bias (when the wording of questions leads a respondent to answer in a particular way), courtesy bias (when a respondent is reluctant to give negative feedback out of concern for offending the interviewer), or group dynamic bias (when participants respond the way the majority responds, rather than the way they really feel). These typically aren’t issues in observational research.
Whereas other primary research methods (focus groups, for instance) will only get you a representative sample of your target market, many observational techniques (analytics, heatmapping, keyword research, in-store cameras) will get you data on a much larger census . This eliminates both sampling error and sampling bias .

Disadvantages of Observational Research:

While observation can tell you volumes about behavior , it has little to say about those crucial—but unobservable—matters such as attitudes, motivations, intentions, and awareness (the “why”). You’ll need direct contact with your subjects to get those answers.
Because they can’t discern motives or attitudes based on outward behavior, observational researchers are often left to make subjective inferences on behavior that is ultimately difficult to interpret. Not only can this invite researcher bias (subconscious judgments on demographics, for example); it also leaves room for erroneous assumptions about cause-and-effect.
In many forms of observational research (in-store observation or website analytics, for example), researchers don’t have any control over environments, context, or even subject presence . They must patiently let consumer behavior unfold as slowly as it does— whenever they finally walk into the store or land on the website—which makes it a potentially time-consuming endeavor with long periods of inactivity.
Observational research is often limited to discrete activities (shopping for a cereal or looking at a web page); and it can’t take the entire context—let alone the entire activity—into account. (Of course, taking a hybrid approach and pairing observational research with an interview can correct this.)
It’s limited to research on products, services, apps, etc. that already exist . In other words, observational research won’t let you research what hasn’t happened yet… which means it can’t offer intelligence on the “What if ?” questions.
It brings up a whole set of questions about ethics. The definition of “ethical” is likely to keep evolving over the years—especially as more and more technologies are capable of generating and collecting big data. Consumers feel less and less protected as time goes on; and you’ll want to be sure you don’t blur the line between research and privacy infringement. Under GDPR , there are legal repercussions to consider… but also ask yourself if you’d want to be asked permission if you were in the consumer’s shoes.

As you may have noted, observational research often works best when paired with other market research methodologies. Observation might give you insights into actual consumer behavior in real-world situations, but a focus group might fill in the thought processes behind the behavior. Between the two, you’ll have a more complete picture of the consumer’s experience.

Examples of Observational Research

What follows is hardly an exhaustive list: There are probably more observational techniques out there than we’re even aware of. Our goal here is simply to give you a sense of the range of types of observational research out there… maybe some of them will resonate with the questions you’re asking about your business right now.

In-store observation

In-store observation is quite possibly the oldest form of observational research. You can perform it in your own brick-and-mortar store, or in your competitors’ stores. How many people enter the store in a given time period? Are they drawn to something in the window display or were they already clearly intent on entering? How do they get their bearings once they’re inside? What do they notice and where do they go first? How many products do they pick up; how long do they scrutinize the packaging; and what do they ultimately purchase, if anything? What are the demographic characteristics of those who do buy?

The answers can be arrived at via human observation (mystery shoppers or your own employees), mechanical observation (video cameras, electronic checkout scanners, etc), or observational research tools such as footfall counters or frequent shopper cards that gather data about the types of purchases made by certain demographics.

Some businesses even conduct “shop-alongs,” which combine observational techniques and traditional market research: The researcher follows the consumer around the store, and the consumer describes the reasoning behind their purchasing behavior in the moment, or after purchases are made.

Contextual inquiry

Contextual inquiry is just what it sounds like: inquiring into a consumer’s behaviors or experiences in the context of where those behaviors or experiences take place. Shop-alongs are certainly one form of contextual inquiry; but in-home, in-car, and in-office observation are other “natural environments” were consumers can be observed. What are the pain points in their morning routines? In using certain kitchen appliances? What products are in their laundry rooms? How do they actually use that cleaning product, or implement that business process? (Note that contextual inquiry is typically a hybrid research form.)

These are more intrusive observational techniques, for sure; and they fall under the category of “ethnographic research” (a method popularized by anthropology but widely used in marketing). But they’ll help you identify needs and beliefs that consumers don’t recognize themselves, or that go unarticulated because they don’t know how to verbalize them.

Eye tracking, heatmapping, and scrollmapping

Now we’re talking a different kind of “observational” research altogether: These are all forms of “observing the observer.” Eye-tracking is a technology that detects where an observer’s pupil is by reflecting near-infrared light off the retina. It follows a viewer’s gaze (on a webpage or an advertisement, for example), giving the business a better sense of where visual attention is drawn—and thus, how that website or ad could be optimized.

The technology creates a heatmap: a graphical representation of where users most often look. (Heatmaps can also show where website users most often click .) Here’s an example from Zoho PageSense :

Usability testing

Usability testing encompasses a series of methods of gathering feedback about the ways consumers use your products (or your app, or your website, etc). One form of usability testing is watching a consumer use a prototype of your device. Another is asking subjects to complete a task on your website or app while you watch, listen, and take notes on their spoken thought processes.

The point is to discover if your offering is intuitive enough that users don’t have to call your business for help navigating your website, or resort to a user manual. (Unless your product is complex enough that they need one… in which case, test your manual !) How satisfying is the user experience? Where are the usability hiccups; where could you make the experience smoother; how could you better encourage desired behaviors (getting them to click that “Purchase” CTA, for example)? UserTesting and UsabilityHub are places to turn for such feedback… or maybe you’ve got a group of willing consumers already ready to help you out.

Trace analyses

A “trace” is any residual physical evidence of past consumer behavior. (Traces always deal in the past). Many of these traces will yield data for your marketing research efforts. These include:

credit card and sales records
wear and tear of physical spaces (i.e. tile erosion or carpet wear will indicate customer footfall)
garbology (purchase patterns can be detected by a glance through the trash)
cookie data (web users also leave “traces” behind; researchers can analyze browsing history for deeper insights)

Social intelligence

Social listening, too, is “observation”; and it gives you qualitative insights on a quantitative scale . 2.34 billion people worldwide have a social media profile , and many of them are using their profiles to reflect their lives (and their opinions!); so consumer insights and behavior can be uncovered if you’ve got the right tools. Indeed, social media may be one of the most powerful resources available for modern market research.

Of course, social platforms can be used to pose questions, post surveys, and have public conversations with your target market. But it’s also useful for strictly observational research… in which you simply “listen,” without interacting. Intent to purchase, sentiment analysis (how consumers in different demographics feel about your brand), and campaign analysis can all be deduced through listening. You’ll learn what’s getting liked, what’s getting shared, and who is influencing your target market to have the opinions they have.

Joining a Facebook group in your industry will allow you to “observe” by reading through the group feed. What’s more, there are a wide array of tools out there—including Zoho Social , Mention , Social Mention , and Google Alerts —that let you set alerts for certain keywords, such as your business or your product. The platform will notify you every time it uncovers a new mention online… so you only have to do the work of analyzing what that mention might mean for your business.

Q&A sites

Quora , Reddit , and Yahoo! Answers are all substantial online forums that can provide a wealth of consumer behavior. (Free questions from your target market? Yes, please!) You can search these , too, for your product or brand name… though if you’re using some of the tools we mentioned above (Mention and Google Alerts search beyond social media platforms) they’ll catch these mentions for you.

Quora, for example, will notify you when questions have been tagged with the topics you select when you set up your profile. And because it organizes answers based on “upvotes,” you’ll be able to see which answers users think are most valuable (as well as which questions have been most often answered):

You can also conduct broader search queries on these platforms: What are the pain points people out there are complaining about (the ones you could solve)? What is your target market interested in learning (the stuff you could teach them on your business blog )? What’s the sentiment around your competitors’ offerings? What frustrates or pleases them about the currently-available solutions to their problems?

Keyword research

Consumers’ browsing habits will alert you to their pain points, interests, and concerns. What’s more, keyword research helps you discover the language consumers use to talk about those pain points, interests, and concerns. Google offers both autocomplete suggestions and “Searches related to” at the bottom of every SERP; pay attention to these, because they’re the terms most often used or currently trending.

Other keyword tools include Ubersuggest , Google Trends , and WordStream’s Free Keyword Tools . Each offers different forms of intelligence—search volume, related keywords, average cost per click, tracking of keywords based on distinct criteria, and more. You can generate keyword performance reports as well as lists of keywords specific demographics search for. In other words, keyword research isn’t just for SEO: It’s a market research strategy in and of itself.

We’d be remiss if we didn’t include analytics here. The biggest tool in this toolbox, of course, is Google Analytics , which can offer remarkable insights into your market based on how they engage with your website: where visitors are coming from (this is called “referral traffic”), what page they’re first landing on, which pages or blog posts they spend the most time on, and which have the highest exit rate. Analytics will “observe” your market for you, helping you better optimize your virtual offerings in the long run.

You can also combine website tracking with marketing automation, which tracks email engagement (open rates, link clicks, forwards, replies), so you can adjust future email marketing campaigns accordingly.

A third analytics strategy—for use on both your website and your email marketing campaigns —is A/B testing. You’ll develop two different versions of a web page or email, with a single variation between the two (a different headline or call to action, for example). A portion of your visitors or recipients will get one version and the rest will get the other version; the software tracks the two and determines which version is most effective. A/B testing will help you make small, incremental refinements that will ultimately make a big difference. In general, analytics allows you to go from insight to action pretty quickly.

There are plenty of observational techniques we didn’t cover here— tracking software for devices and content analyses are two that come to mind—and the next new technology may be available by the time this page goes live. (We’ll keep you updated, of course.) Each method above will add value to your market research in different ways; and if you couple them with surveys, focus groups, competitor research and other forms of secondary market research, you’ll have a wealth of information at your fingertips to improve every aspect of your business—for both yourself and your target market.

Lauren Shufran

The Business Owner's Guide to Conducting Observational Research

As a business owner, staying ahead of the competition and understanding your target audience's needs are crucial to your company's success. One effective way to gain insight into the behavior and preferences of your customers is through observational research. However, conducting observational research requires careful planning and execution to ensure accurate results. This blog will provide a comprehensive guide for business owners on conducting effective observational research to make actionable decisions for their business.

To learn more about other market research methods you can use to understand your customer better, check out my guide on How to do Market Research for your Business afterward.

What is observational research?

Observational research is a market research method that involves observing individuals or groups in their natural settings and gathering data about their behavior, interactions, and other relevant information.

What are the advantages of observational research?

Observational research offers several advantages to business owners. Here are some of the key benefits:

Accurate and reliable data: Observational research allows you to gather reliable data about your customer's behavior, preferences, and interactions. By observing customers in natural settings, you can collect data free from response biases that can arise in other research methods, such as surveys or interviews.
Uncovering hidden insights: Observational research enables you to find insights that customers may not be able to articulate or may not even be aware of themselves. Observing customers' behavior lets you gain insights into their unconscious actions, emotions, and preferences.
Flexibility: Observational research can adapt to different research questions, settings, and participants. This method can be applied to various topics, including consumer behavior, workplace dynamics, and social interactions.
Real-time feedback: Observational research provides real-time feedback, allowing you to change your business practices based on your observations immediately. This can be especially useful for businesses requiring quick feedback to make informed decisions.
Cost-effective: Observational research can be a cost-effective method of gathering data, particularly if observing customers in a natural setting requires little to no additional resources.

What are the drawbacks of observational research?

Like any market research method, observational research also has some disadvantages that business owners should be aware of before implementing. Here are some of the key cons of observational research:

Limited generalizability: Observational research provides insights into a specific group in a particular setting, which may not represent a larger population. The results may not apply to other groups or situations, limiting the generalizability of the findings.
Time-consuming: Observational research can be time-consuming, mainly if you observe customers in multiple settings or over an extended period. It may also require a large sample size to generate meaningful results, increasing the time required.
Potential observer bias: Observational research can be susceptible to observer bias, where the researcher's expectations or preconceptions may influence their interpretation of the data.
Ethical concerns: Observational research can raise ethical concerns, particularly if you are observing people without their knowledge or consent. Obtaining the necessary permissions and ensuring participants' privacy is respected is essential.
Lack of context: Observational research may provide valuable insights into behavior and interactions, but it may not provide context or explanations for why people behave in a particular way. It may be necessary to complement observational research with other methods, such as interviews or surveys, to understand the behavior completely.

Common use cases for observational research

Several common use cases exist where a business owner might use observational research to gain insights into their customers' behavior and preferences. Here are seven examples:

Store layout optimization: Observing customers' movements, interactions, and behaviors in-store can help business owners optimize their store layout, including product placement and aisle design.
Menu optimization: Observing customers' interactions with menus in restaurants or cafes can help business owners optimize their menu design, including item placement, pricing, and descriptions. This can help increase sales and improve customer satisfaction.
Website design: Observing customers' interactions with websites can help business owners optimize their website design, including page layout, navigation, and user experience. This can help increase website traffic, engagement, and conversion rates.
Event planning: Businesses may use observational research to gain insights into attendee behavior and preferences at events such as conferences, trade shows, or product launches. This can help them optimize event planning, including venue selection, booth design, and product demonstrations, leading to increased engagement and sales.
Packaging design: Observing customers' reactions to product packaging can help business owners optimize their packaging design, including color schemes, graphics, and messaging. This can help improve brand recognition, customer engagement, and sales.
Advertising effectiveness: Observing customers' reactions to advertisements can help business owners optimize their advertising strategy, including messaging, placement, and targeting. This can help improve brand awareness, customer engagement, and sales.
User testing: Observing customers' interactions with a product or service during the development process can provide valuable insights into usability, user experience, and areas for improvement. This can help businesses create products that meet customers' needs and expectations.

Types of observational research

Naturalistic observation: This type of observational research involves observing people in their natural environment without interfering with their behavior. This is the most cost-effective and common form of observational research businesses use.
Participant observation: Similar to naturalistic observation, a researcher will observe people in their national environment. However, with participant observation, the researcher will participate in the activity, such as joining a focus group or trying out a product. Participant observation can help to gain deeper insights into customer behavior and preferences.
Controlled observation: This type of observational research involves observing customers in a controlled setting, such as a laboratory or research facility. Companies with products or services that need to demonstrate reliability, such as a glucose monitoring product, may use a controlled observation to conduct the observational research required for their business.

What are the steps to conduct observational research?

Step 1: define your topic.

Start by identifying your objective for observational research. For example, a craft beer company might use an observational study to understand better how customers view the artwork they designed for their can label in a crowded grocery aisle.

Step 2: Select your observation type

For most businesses, naturalistic observation will suffice.

Step 3: Determine how many people to observe

Set your sample size for the experiment. As a rule of thumb, you'll want to observe as many people as possible to identify trends and common behaviors.

Step 4: Create a run-of-show

Detail the behaviors and variables you'll be observing, the data collection methods you will use, and any specific procedures you will follow.

For example, here's a craft beer company's run-of-show:

Behaviors and variables: We will collect the gender, age range, and ethnicity of observed participants. We will record their time in the alcohol aisle, whether they recognized our brand, and whether they purchased one of our beers.
Data collection methods: We will use two trained team members at each end of the aisle to observe the subjects and have received permission from the grocery stores to supplement our findings with video recordings.
Specific procedures: We will remove from our dataset any subjects who become aware of our team members who are observing them at any time.

Step 5: Train your observers and recruit participants

Train your observers to follow the protocols outlined in your run-of-show document and to ensure they understand how specific actions, such as getting caught observing someone, may bias participants.

Recruit participants who you will observe for the study. For this example, the beer company could email people from their customer database or advertise the study with a flier in one of their locations.

Step 6: Conduct your observational research

With all your preparation to get to this point, you should be confident to conduct your observational research. Don't be afraid to adjust if you notice details or things you did not prepare for. However, ensure you are not making these changes because you want to confirm your previous assumptions (confirmation bias). You may observe behaviors in subjects you didn't expect to see or predict, which you should welcome as valuable insights to leverage with your business.

Step 7: Analyze the results

After the observational research study has finished, organize your notes, transcribe your recordings, and analyze them carefully to draw meaningful conclusions.

Step 8: Thank and follow up with participants

It is essential to thank the participants for their time and effort in participating in the observational research. This can build trust and goodwill with your business and encourage future participation, as it may be necessary to complement observational research with other methods, such as interviews or surveys, to understand the behavior entirely.

What biases do you need to control for observational research?

Hawthorne effect: Participants may change their behavior when they know they are being observed, leading to inaccurate results. To control for this bias, use unobtrusive observation methods or inform participants of the observation in advance.
Selection bias: The sample of participants may not represent the studied population. To control this bias, select the participants carefully based on the research objectives and criteria.
Contextual bias: The setting or context in which the observations occur may influence participants' behavior. To control this bias, conduct the observation study in a naturalistic setting and consider the context of the observed behavior.
Experimenter bias: The experimenter may unconsciously influence the participants' behavior or the interpretation of the data. To control for this bias, ensure that the experiment is standardized and that the experimenter is neutral and impartial.

What tools should you use for online observational research?

Glassbox : best overall
Hotjar : best free plan
Mouseflow : best for small businesses

Tips to get the most value from observational research

Use multiple observers: One way to get the most value from observational research is to use numerous observers. This can reduce observer bias and increase the reliability of your findings. By having multiple observers, you can compare their notes and observations to identify patterns and trends.
Document context: Observations are often context-dependent. Therefore, it's essential to document the context of your observations. This can include details such as time of day, location, weather, and any other relevant environmental factors. This can help you better understand the factors that influence the behavior you are observing.
Observe over time: Observing behavior over time can help you identify changes in behavior and help you understand how different factors influence behavior. By observing behavior over time, you can also specify the long-term effects of interventions or modifications to the environment.

Common mistakes with observational research

Lack of clear research question: Without a straightforward research question, observational research can be aimless and lack focus. This can lead to collecting irrelevant or uninterpretable data.
Overgeneralization: Observational research should not be used to draw conclusions about a larger population. The findings should only be used to generate hypotheses for further investigation.
Failure to account for contextual factors: Contextual factors, such as the environment or social norms, can influence observed behaviors or events. Researchers should document this and make sure that they take these factors into account.

Observational research examples

IKEA uses observational research to understand how customers use and navigate its stores and to improve the store layout and design. By doing so, they have mastered the Gruen effect , which makes customers more susceptible to purchases. Ikea's creative director admitted that only 20% of customer purchases are logical or based on actual needs.

SoFi uses Glassbox to conduct observation research to get the most accurate picture of how members experience their app.

3. Hewlett-Packard

Hewlett-Packard is well-known for using observation research to gain insights that it can use to drive business success. In one instance, they conducted a two-week study on customers' buying behavior at a large independent bookstore Kepler's Books & Magazines, in Menlo Park. Notably, they acknowledged many unexpected findings, such as more gift buyers than initially anticipated.

With a solid understanding of observational research and a commitment to following best practices outlined in this guide, business owners can unlock valuable insights into their customers' behavior and preferences.

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Experimental vs Observational Studies: Differences & Examples

Understanding the differences between experimental vs observational studies is crucial for interpreting findings and drawing valid conclusions. Both methodologies are used extensively in various fields, including medicine, social sciences, and environmental studies.

Researchers often use observational and experimental studies to gather comprehensive data and draw robust conclusions about their investigating phenomena.

This blog post will explore what makes these two types of studies unique, their fundamental differences, and examples to illustrate their applications.

What is an Experimental Study?

An experimental study is a research design in which the investigator actively manipulates one or more variables to observe their effect on another variable. This type of study often takes place in a controlled environment, which allows researchers to establish cause-and-effect relationships.

Key Characteristics of Experimental Studies:

Manipulation: Researchers manipulate the independent variable(s).
Control: Other variables are kept constant to isolate the effect of the independent variable.
Randomization: Subjects are randomly assigned to different groups to minimize bias.
Replication: The study can be replicated to verify results.

Types of Experimental Study

Laboratory Experiments: Conducted in a controlled environment where variables can be precisely controlled.
Field Research : These are conducted in a natural setting but still involve manipulation and control of variables.
Clinical Trials: Used in medical research and the healthcare industry to test the efficacy of new treatments or drugs.

Example of an Experimental Study:

Imagine a study to test the effectiveness of a new drug for reducing blood pressure. Researchers would:

Randomly assign participants to two groups: receiving the drug and receiving a placebo.
Ensure that participants do not know their group (double-blind procedure).
Measure blood pressure before and after the intervention.
Compare the changes in blood pressure between the two groups to determine the drug’s effectiveness.

What is an Observational Study?

An observational study is a research design in which the investigator observes subjects and measures variables without intervening or manipulating the study environment. This type of study is often used when manipulating impractical or unethical variables.

Key Characteristics of Observational Studies:

No Manipulation: Researchers do not manipulate the independent variable.
Natural Setting: Observations are made in a natural environment.
Causation Limitations: It is difficult to establish cause-and-effect relationships due to the need for more control over variables.
Descriptive: Often used to describe characteristics or outcomes.

Types of Observational Studies:

Cohort Studies : Follow a control group of people over time to observe the development of outcomes.
Case-Control Studies: Compare individuals with a specific outcome (cases) to those without (controls) to identify factors that might contribute to the outcome.
Cross-Sectional Studies : Collect data from a population at a single point to analyze the prevalence of an outcome or characteristic.

Example of an Observational Study:

Consider a study examining the relationship between smoking and lung cancer. Researchers would:

Identify a cohort of smokers and non-smokers.
Follow both groups over time to record incidences of lung cancer.
Analyze the data to observe any differences in cancer rates between smokers and non-smokers.

Difference Between Experimental vs Observational Studies

Topic	Experimental Studies	Observational Studies
Manipulation	Yes	No
Control	High control over variables	Little to no control over variables
Randomization	Yes, often, random assignment of subjects	No random assignment
Environment	Controlled or laboratory settings	Natural or real-world settings
Causation	Can establish causation	Can identify correlations, not causation
Ethics and Practicality	May involve ethical concerns and be impractical	More ethical and practical in many cases
Cost and Time	Often more expensive and time-consuming	Generally less costly and faster

Choosing Between Experimental and Observational Studies

The researchers relied on statistical analysis to interpret the results of randomized controlled trials, building upon the foundations established by prior research.

Use Experimental Studies When:

Causality is Important: If determining a cause-and-effect relationship is crucial, experimental studies are the way to go.
Variables Can Be Controlled: When you can manipulate and control the variables in a lab or controlled setting, experimental studies are suitable.
Randomization is Possible: When random assignment of subjects is feasible and ethical, experimental designs are appropriate.

Use Observational Studies When:

Ethical Concerns Exist: If manipulating variables is unethical, such as exposing individuals to harmful substances, observational studies are necessary.
Practical Constraints Apply: When experimental studies are impractical due to cost or logistics, observational studies can be a viable alternative.
Natural Settings Are Required: If studying phenomena in their natural environment is essential, observational studies are the right choice.

Strengths and Limitations

Experimental studies.

Establish Causality: Experimental studies can establish causal relationships between variables by controlling and using randomization.
Control Over Confounding Variables: The controlled environment allows researchers to minimize the influence of external variables that might skew results.
Repeatability: Experiments can often be repeated to verify results and ensure consistency.

Limitations:

Ethical Concerns: Manipulating variables may be unethical in certain situations, such as exposing individuals to harmful conditions.
Artificial Environment: The controlled setting may not reflect real-world conditions, potentially affecting the generalizability of results.
Cost and Complexity: Experimental studies can be costly and logistically complex, especially with large sample sizes.

Observational Studies

Real-World Insights: Observational studies provide valuable insights into how variables interact in natural settings.
Ethical and Practical: These studies avoid ethical concerns associated with manipulation and can be more practical regarding cost and time.
Diverse Applications: Observational studies can be used in various fields and situations where experiments are not feasible.
Lack of Causality: It’s easier to establish causation with manipulation, and results are limited to identifying correlations.
Potential for Confounding: Uncontrolled external variables may influence the results, leading to biased conclusions.
Observer Bias: Researchers may unintentionally influence outcomes through their expectations or interpretations of data.

Examples in Various Fields

Experimental Study: Clinical trials testing the effectiveness of a new drug against a placebo to determine its impact on patient recovery.
Observational Study: Studying the dietary habits of different populations to identify potential links between nutrition and disease prevalence.
Experimental Study: Conducting a lab experiment to test the effect of sleep deprivation on cognitive performance by controlling sleep hours and measuring test scores.
Observational Study: Observing social interactions in a public setting to explore natural communication patterns without intervention.

Environmental Science

Experimental Study: Testing the impact of a specific pollutant on plant growth in a controlled greenhouse setting.
Observational Study: Monitoring wildlife populations in a natural habitat to assess the effects of climate change on species distribution.

How QuestionPro Research Can Help in Experimental vs Observational Studies

Choosing between experimental and observational studies is a critical decision that can significantly impact the outcomes and interpretations of a study. QuestionPro Research offers powerful tools and features that can enhance both types of studies, giving researchers the flexibility and capability to gather, analyze, and interpret data effectively.

Enhancing Experimental Studies with QuestionPro

Experimental studies require a high degree of control over variables, randomization, and, often, repeated trials to establish causal relationships. QuestionPro excels in facilitating these requirements through several key features:

Survey Design and Distribution: With QuestionPro, researchers can design intricate surveys tailored to their experimental needs. The platform supports random assignment of participants to different groups, ensuring unbiased distribution and enhancing the study’s validity.
Data Collection and Management: Real-time data collection and management tools allow researchers to monitor responses as they come in. This is crucial for experimental studies where data collection timing and sequence can impact the results.
Advanced Analytics: QuestionPro offers robust analytical tools that can handle complex data sets, enabling researchers to conduct in-depth statistical analyses to determine the effects of the experimental interventions.

Supporting Observational Studies with QuestionPro

Observational studies involve gathering data without manipulating variables, focusing on natural settings and real-world scenarios. QuestionPro’s capabilities are well-suited for these studies as well:

Customizable Surveys: Researchers can create detailed surveys to capture a wide range of observational data. QuestionPro’s customizable templates and question types allow for flexibility in capturing nuanced information.
Mobile Data Collection: For field research, QuestionPro’s mobile app enables data collection on the go, making it easier to conduct studies in diverse settings without internet connectivity.
Longitudinal Data Tracking: Observational studies often require data collection over extended periods. QuestionPro’s platform supports longitudinal studies, allowing researchers to track changes and trends.

Experimental and observational studies are essential tools in the researcher’s toolkit. Each serves a unique purpose and offers distinct advantages and limitations. By understanding their differences, researchers can choose the most appropriate study design for their specific objectives, ensuring their findings are valid and applicable to real-world situations.

Whether establishing causality through experimental studies or exploring correlations with observational research designs, the insights gained from these methodologies continue to shape our understanding of the world around us.

Whether conducting experimental or observational studies, QuestionPro Research provides a comprehensive suite of tools that enhance research efficiency, accuracy, and depth. By leveraging its advanced features, researchers can ensure that their studies are well-designed, their data is robustly analyzed, and their conclusions are reliable and impactful.

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Observational Research

Have you ever people-watched at a crowded café or observed how shoppers behave in a store? Congratulations, you've already engaged in observational research! Observational research is a method of gathering data by watching and recording the behaviors of people, animals, or objects in their natural environment. In this article, we'll explore the definition of observational research, its types, advantages and disadvantages, and various examples of how it's used in marketing research. From observing shoppers in a supermarket to studying animal behavior in the wild, let's dive into the fascinating world of observational research!

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Cell Biology

Direct observation happens when researchers watch the subject perform a task or ask them direct questions.

The type of research where the researcher observes the subject interacting in their everyday situations, such as in an office or home is called _____________.

Some customer data can only be observed through observational research.

What is NOT a disadvantage of observational research?

Shop-along happens when the researcher observes the subject's behaviour in a __________ store and asks questions related to the experience

Observational research is a type of ____________.

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Observational Research Definition

Observational research is when a researcher watches and takes notes on what they see happening without interfering. It is like being a naturalist who observes animals without interfering. In the case of observation, a researcher would observe human subjects without manipulating any variables. The goal of observational research is to gather information about behavior, attitudes, and beliefs in a natural setting without changing the way people behave.

Observational research is a type of research design in which a researcher observes participants in their natural environment without intervening or manipulating variables. It involves watching and taking notes on behavior, actions, and interactions and can be used to gather information on attitudes, beliefs, and habits.

Imagine a researcher who wants to study how children interact with each other on a playground. They go to a nearby park and observe the children playing without interfering. They take notes on what games they play, who they play with, and how they communicate with each other. From this research, the researcher can learn about the social dynamics of children's play and use this information to develop interventions or programs to promote positive interactions.

Direct vs Indirect observation

Direct observation happens when researchers watch the subject perform a task or ask them direct questions. For example, in a study of young children's behaviour, researchers observe them interacting with other children on a playground. In contrast, indirect observation studies the results of an action. For example, the number of likes or views on a video helps researchers determine what type of content appeals to customers.

Any data can become observational, including text, numbers, videos, and images. By collecting and analysing observational data, the researcher can determine how customers behave in a particular situation and which factors influence their decisions. Observational research can sometimes help describe a phenomenon.

One common type of observational research is ethnographic observation . This happens when the researcher can observe the subject interacting in everyday situations, such as in an office or home.

To learn more about other primary data collection methods, check out our explanation of primary data collection.

Observation Market Research

Observation market research is a method of collecting data about consumers by observing their behavior in a natural or controlled setting. This type of research is used to gain insights into how consumers interact with products, packaging, and advertising in real-world situations. It is often conducted in combination with other research methods, such as surveys and focus groups , to provide a more complete understanding of consumer behavior and preferences.

Observation market research is a research method that involves observing consumers in a natural or controlled environment to gain insights into their behavior and preferences. This type of research is used to inform decisions about product design, packaging, and marketing strategies.

Imagine a company that sells smartphones wants to know how consumers use their products. The company could conduct observation market research by visiting consumers' homes and observing how they use their smartphones in their daily lives. The researchers could note which features and apps are used most frequently, how consumers hold and interact with their phones, and what types of content they access. This information could be used to inform decisions about product design and marketing strategies that better meet consumers' needs and preferences.

Types of Observation in Research

Types of observation in research include:

Naturalistic and controlled observation

Participant and non-participant observation, structured and unstructured observation.

Overt and covert observation

Naturalistic observation involves observing people in their natural environment without manipulating variables, while controlled observation involves observing people in a controlled environment where variables can be manipulated to create specific conditions. For example, naturalistic observation could involve observing people's behavior in a public park, while controlled observation could involve observing people's behavior in a laboratory setting.

Participant observation happens when the observer becomes a part of the group being studied and actively participates in the activities being studied. In contrast, non-participant observation involves observing from a distance without becoming a part of the group. For example, participant observation could involve joining a group therapy session and taking notes on the interactions between group members, while non-participant observation could involve observing a public meeting from a distance and taking notes on the behavior of attendees.

Structured observation refers to observing people in a structured setting with predetermined activities, while unstructured observation involves observing people without predetermined activities to observe. For example, structured observation could involve observing children's behavior during a specific game, while unstructured observation could involve observing the behavior of patrons in a coffee shop.

Overt observation and Covert observation

Overt observation involves observing people with their knowledge and consent, while covert observation involves observing people without their knowledge or consent. For example, overt observation could involve observing people in a focus group discussion, while covert observation could involve observing people through hidden cameras in a retail store.

Advantages of Observational Research

Observational research comes with many benefits, including:

More accurate insights

The customers may not remember the full detail of their actions or do something different from what they say. In such cases, the information collected can be inaccurate, resulting in wrong conclusions. To improve the reliability of data collected, researchers can watch customers interact in their environment.

Some data can only be observed

Some information, such as people's eye movements when visiting a shop or how people behave in a group, is not something researchers can collect with a questionnaire. The subjects themselves may not be aware of their own behaviour. The only way to collect such data is through observation.

Remove biases

People's answers can be biased due to their desire to impress others or the question's wording. Observing customer behaviour will eliminate these biases and give the researcher more accurate data.

Remove sampling errors

Other research approaches, such as surveys or experiments, involve collecting data from a sample.

Sampling saves time and money, but there's a lot of room for errors as individuals in the same group can differ significantly in certain aspects. With observational research, there is no sampling, and thus researchers can avoid sampling errors.

Disadvantages of Observational Research

There are two significant drawbacks to observational research:

Some data are not observable

Researchers cannot observe data such as customers' beliefs, motivation, and awareness via actions or situations. Thus, observational research may not be the best approach to studying what people think about a business.

Learn about survey methods to collect data on customers' attitudes and motivation.

Time-consuming

In some observational studies, researchers can't control the environment. That means they have to wait patiently for the customer to perform a task and collect data, resulting in a lot of dead time due to inactivity.

Observational Research Design

The observational research design process is composed of six steps:

The first three steps answer the questions - Who? Why? How?

Who is the subject of the research?

Why is the research carried out?

How is the study conducted?

The last three steps include data collection, organisation, and analysis.

Here is a more detailed breakdown of the process:

Step 1: Identify the research target

This step answers the 'who' question. Who is the target audience? To which customer group do they belong? Is there any information about this target group that the researcher can use to assist the research?

Step 2: Determine the purpose of the research

Once the target group is defined, the next step is to decide on the research's goals and purpose. Why is the research conducted? What problem does it help solve? Is there a hypothesis the study tries to verify?

Step 3: Decide on the method of the research.

After defining 'who' and 'why', researchers need to work on the 'how'. This involves determining the method of observational research.

Reread the previous section to learn more about observational research methods.

Step 4: Observe the subjects

This step is where the actual observation takes place. The researcher can watch their subject in the natural or contrived environment, directly or indirectly, based on the research method.

Step 5: Sort and organise data

During this step, raw data is synthesised and organised to suit the purpose of the research. Any irrelevant information will be left out.

Step 6: Analyse the data collected.

The final step is data analysis. The researcher will assess the data collected to draw conclusions or confirm a hypothesis.

Marketing Observation Examples

There are many observational research examples in market research:

Shop-along happens when the researcher observes a subject's behaviour in a brick-and-mortar store and asks questions about the experience. 1

Some examples of questions that the researcher may pose:

What placement catches your attention?

What distracts you from getting what you want to buy?

Does the packaging influence your buying decision?

Does the shop's layout make it easy to find what you want?

Observational research example shop along Vaia

Eye-tracking or heat map

Another example of observational research is eye-tracking. Eye-tracking refers to using technology to observe the subjects' eye movements to see what draws their attention. On an online platform, heat maps track viewers' eye movements. Heat maps visualise customer data such as website clicks, scrolls, or mouse movements with appealing colours.

Here's an example of what it looks like:

Observational research example eye tracking heat map Vaia

Utility testing

Utility testing is also a common form of observational research. Here, the researcher will ask the subject to perform a task, then observe and ask for feedback on their experience. This kind of research comes in handy when the researcher wants to identify a problem, an opportunity for their product, or collect data on customer behaviour. 2

Observational Research Examples

Here are three famous examples of observational research from different fields:

Jane Goodall's study of chimpanzees: In the 1960s, Jane Goodall conducted a groundbreaking study of chimpanzees in the Gombe Stream National Park in Tanzania. Goodall spent years observing the behavior of the chimpanzees in their natural habitat, documenting their social interactions, tool use, and hunting behavior. Her research has had a major impact on our understanding of animal behavior and the evolution of humans.

The Hawthorne studies: The Hawthorne studies were a series of experiments conducted by researchers at Western Electric in the 1920s and 1930s to investigate the effects of different working conditions on employee productivity. The researchers observed workers in a factory setting and made changes to their working conditions, such as adjusting lighting and work hours. The results of the study showed that the mere act of being observed by researchers led to increased productivity, a phenomenon now known as the "Hawthorne effect."

Rosenthal and Jacobson's study of teacher expectations: In the 1960s, researchers Robert Rosenthal and Lenore Jacobson conducted a study in which they told teachers that certain students had been identified as "academic bloomers" who were likely to experience significant academic growth. In reality, the students had been selected at random. The researchers observed the students over the course of a school year and found that the students who had been labeled as "bloomers" showed greater academic progress than their peers. This study demonstrated the power of teacher expectations in shaping student performance.

Observational Research - Key Takeaways

Observational research gathers primary customer data by observing them in a natural setting.
Observational research helps researchers understand how people behave in different situations and which factors influence their decisions.
Types of observation methods include: naturalistic and controlled observation, p articipant and non-participant observation, s tructured and unstructured observation, and o vert and covert observation
Observational research allows for more accurate data collection, removing biases and sampling errors. However, it can be time-consuming due to long hours of inactivity.
There are six steps to conducting observational research: identifying the target group, determining the research purpose, deciding on the research method, observing the subject, sorting data, and finally analysing data.
SIS International Research, Shop-Along Market Research, 2022, https://www.sisinternational.com/solutions/branding-and-customer-research-solutions/shop-along-research.
Kate Moran, Utility Testing 101, 2019.

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Frequently Asked Questions about Observational Research

What is observational research?

Observational research means gathering primary data by observing people interact in a natural or controlled setting.

What is an advantage of the participant observation research method?

An advantage of the participant observation research method is that it provides more accurate customer data without fewer sampling errors.

How to avoid bias in observational research?

To avoid bias in observational research, the observers should be well-trained and follow procedures that have been established.

What type of research is an observational study?

Why observation is important in research?

Observation is important to research as it allows researchers to understand why customers behave the way they do and what factors influence their decisions.

What is observation in market research?

Observation in market research is the process of watching and recording consumers' behaviors, actions, and interactions with products or services in a natural or controlled environment. It is used to gain insight into how consumers behave in real-life situations and inform decisions about product design, packaging, and marketing strategies.

Are observational studies primary research

Yes, observational studies are a type of primary research. Primary research is defined as research that is conducted directly by the researcher to gather original data, rather than relying on existing data sources. Observational studies involve the direct observation of a phenomenon or behavior in a natural or controlled setting, and are therefore a form of primary research.

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Direct observation happens when researchers watch the subject perform a task or ask them direct questions.

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The Ultimate Guide to Qualitative Research - Part 1: The Basics

Introduction and overview
What is qualitative research?
What is qualitative data?
Examples of qualitative data
Qualitative vs. quantitative research
Mixed methods
Qualitative research preparation
Theoretical perspective
Theoretical framework
Literature reviews
Research question
Conceptual framework
Conceptual vs. theoretical framework

Data collection

Qualitative research methods
Focus groups

What is observational research?

Uses for observational research, observations in research, the different types of observational research, conducting observational studies, uses with other methods, challenges of observational studies.

Case studies
Ethnographical research
Ethical considerations
Confidentiality and privacy
Power dynamics
Reflexivity

Observational research

Observational research is a social research technique that involves the direct observation of phenomena in their natural setting.

An observational study is a non-experimental method to examine how research participants behave. Observational research is typically associated with qualitative methods , where the data ultimately require some reorganization and analysis .

Contemporary research is often associated with controlled experiments or randomized controlled trials, which involve testing or developing a theory in a controlled setting. Such an approach is appropriate for many physical and material sciences that rely on objective concepts such as the melting point of substances or the mass of objects. On the other hand, observational studies help capture socially constructed or subjective phenomena whose fundamental essence might change when taken out of their natural setting.

What is an example of observational research?

For example, imagine a study where you want to understand the actions and behaviors of single parents taking care of children. A controlled experiment might prove challenging, given the possibility that the behaviors of parents and their children will change if you isolate them in a lab or an otherwise unfamiliar context.

Instead, researchers pursuing such inquiries can observe participants in their natural environment, collecting data on what people do, say, and behave in interaction with others. Non-experimental research methods like observation are less about testing theories than learning something new to contribute to theories.

The goal of the observational study is to collect data about what people do and say. Observational data is helpful in several fields:

market research
health services research
educational research
user research

Observational studies are valuable in any domain where researchers want to learn about people's actions and behaviors in a natural setting. For example, observational studies in market research might seek out information about the target market of a product or service by identifying the needs or problems of prospective consumers. In medical contexts, observers might be interested in how patients cope with a particular medical treatment or interact with doctors and nurses under certain conditions.

Researchers may still be hung up on science being all about experiments to the point where they may overlook the empirical contribution that observations bring to research and theory. With that in mind, let's look at the strengths and weaknesses of observations in research .

Strengths of observational research

Observational research, especially those conducted in natural settings, can generate more insightful knowledge about social processes or rituals that one cannot fully understand by reading a plain-text description in a book or an online resource. Think about a cookbook with recipes, then think about a series of videos showing a cook making the same recipes. Both are informative, but the videos are often easier to understand as the cook can describe the recipe and show how to follow the steps at the same time. When you can observe what is happening, you can emulate the process for yourself.

Observing also allows researchers to create rich data about phenomena that cannot be explained through numbers. The quality of a theatrical performance, for example, cannot easily be reduced to a set of numbers. Qualitatively, a researcher can analyze aspects gleaned from observing that performance and create a working theory about the quality of that performance. Through data analysis, the researcher can identify patterns related to the aesthetics and creativity of the performance to provide a framework to judge the quality of other performances.

Weaknesses of observational research

Science is about organizing knowledge for the purposes of identifying the aspects of a concept or of determining cause-and-effect relationships between different phenomena. Experiments look to empirically accomplish these tasks by controlling certain variables to determine how other variables change under changing conditions. Those conducting observational research, on the other hand, exert no such control, which makes replication by other researchers difficult or even impossible when observing dynamic environments.

Observational studies take on various forms. There are various types of observational research, each of which has strengths and weaknesses. These types are organized below by the extent to which an experimenter intrudes upon or controls the environment.

Naturalistic observation

Naturalistic observation refers to a method where researchers study participants in their natural environment without manipulating variables or intervening in any way. It provides a realistic snapshot of behavior as it occurs in real-life settings, thereby enhancing ecological validity.

Examples of naturalistic observation include people-watching in public places, observing animal behaviors in the wild, and longitudinally studying children's social development at school. This method can reveal insights about behavior and relationships that might not surface in experimental designs, such as patterns of social interaction, routines, or responses to environmental changes.

Participant observation

Participant observation is similar to naturalistic observation, except that the researcher is part of the natural environment they are observing. In such studies, the researcher is also interested in rituals or cultural practices where they can only determine their value by actually experiencing them firsthand. For example, any individual can understand the basic rules of baseball by watching a game or following a team. Participant observation, on the other hand, allows for direct participation to develop a better sense of team dynamics and relationships among fellow players.

Most commonly, this process involves the researcher inserting themselves into a group to observe behavior that otherwise would not be accessible by observing from afar. Participant observation can capture rich data from the interactions with those who are observed to the reflections of the researchers themselves.

Controlled observation

A more structured observation involves capturing the behaviors of research participants in an isolated environment. Case-control studies have a greater resemblance to experimental research while still relying on observational research methods. Researchers may utilize a case-control study when they want to establish the causation of a particular phenomenon.

For example, a researcher may want to establish a structured observation of a control group and an experimental group, each with randomly assigned research participants, to observe the effects of variables such as distractions on people completing a particular task. By subjecting the experimental group to distractions such as noise and lights, researchers can observe the time it takes participants to complete a task and determine causation accordingly.

Longitudinal study

Among the different types of observational research, this observational method is quite arduous and time-consuming as it requires observation of people or events over extended periods. Researchers should consider longitudinal observations when their inquiry involves variables that can only be observed over time. After all, variables such as literacy development or weight loss cannot be fully captured in any particular moment of observation. Longitudinal studies keep track of the same research participants or events through multiple observations to document changes to or patterns in behavior.

A cohort study is a specific type of longitudinal study where researchers observe participants with similar traits (e.g., a similar risk factor or biological characteristic). Cohort studies aim to observe multiple participants over time to identify a relationship between observed phenomena and a common characteristic.

All forms of observational or field research benefit extensively from the special capabilities of qualitative research tools like ATLAS.ti . Our software can accommodate the major forms of data , such as text, audio, video, and images . The ATLAS.ti platform can help you organize all your observations , whatever method you employ.

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Like any other study design, observational studies begin by posing research questions . Inquiries common when employing observational methods include the study of different cultures, interactions between people from different communities, or people in particular circumstances warranting further study (e.g., people coping with a rare disease).

Generally, a research question that seeks to learn more about a relatively unfamiliar phenomenon would be best suited for observational research. On the other hand, quantitative methods or experimental research methods may be more suitable for inquiries where the theory about a social phenomenon is fairly established.

Study design

Study design for observational research involves thinking about who to observe, where they should be observed, and what the researcher should look for during observation. Many events can occur in a natural, dynamic environment in a short period, so it is challenging to document everything. If the researcher knows what they want to observe, they can pursue a structured observation which involves taking notes on a limited set of phenomena.

The actual data collection for an observational study can take several forms. Note-taking is common in observational research, where the researcher writes down what they see during the course of their observation. The goal of this method is to provide a record of the events that are observed to determine patterns and themes useful for theoretical development.

Observation can also involve taking pictures or recording audio for a richer understanding of social phenomena. Video recorded from observations can also provide data that the researcher can use to document the facial expressions, gestures, and other body language of research participants.

Note that there are ethical considerations when conducting observational research. Researchers should respect the privacy and confidentiality of their research participants to ensure they are not adversely affected by the research. Researchers should obtain informed consent from participants before any observation where possible.

Observational studies can be supplemented with other methods to further contextualize the research inquiry. Researchers can conduct interviews or focus groups with research participants to gather data about what they recall about their actions and behaviors in a natural setting. Focus groups, in particular, provide further opportunities to observe participants interacting with each other. In both cases, these research methods are ideal where the researcher needs to follow up with research participants about the evidence they've collected regarding their behaviors or actions.

As with many other methods in qualitative research , conducting an observational study is time-consuming. While experimental methods can quickly generate data , observational research relies on documenting events and interactions in detail that can be analyzed for theoretical development.

Unstructured data

One common critique of observational research is that it lacks the structure inherent to experimental research, which has concepts such as selection bias and interrater reliability to ensure research quality. On the other hand, qualitative research relies on the assumption that the study and its data are presented transparently and honestly . Under this principle, researchers are responsible for convincing their audiences that the assertions they make are connected empirically to the observations they have made and the data they have collected.

Researcher bias

In most qualitative research, but especially in observational research, the most important data collection instrument is the researcher themselves. This raises issues of bias and subjectivity influencing the collection and interpretation of the data.

Later in this guide, there will be discussion of reflexivity , a concept where the researcher comprehensively accounts for their place in the research relative to others in the environment. For now, it's important to know that social science researchers can and do adequately address critiques of researcher bias to maintain the empirical nature of their observational research.

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Home » Observational Research – Methods and Guide

Observational Research – Methods and Guide

Table of Contents

Observational Research

Definition:

Observational research is a type of research method where the researcher observes and records the behavior of individuals or groups in their natural environment. In other words, the researcher does not intervene or manipulate any variables but simply observes and describes what is happening.

Observation

Observation is the process of collecting and recording data by observing and noting events, behaviors, or phenomena in a systematic and objective manner. It is a fundamental method used in research, scientific inquiry, and everyday life to gain an understanding of the world around us.

Types of Observational Research

Observational research can be categorized into different types based on the level of control and the degree of involvement of the researcher in the study. Some of the common types of observational research are:

Naturalistic Observation

In naturalistic observation, the researcher observes and records the behavior of individuals or groups in their natural environment without any interference or manipulation of variables.

Controlled Observation

In controlled observation, the researcher controls the environment in which the observation is taking place. This type of observation is often used in laboratory settings.

Participant Observation

In participant observation, the researcher becomes an active participant in the group or situation being observed. The researcher may interact with the individuals being observed and gather data on their behavior, attitudes, and experiences.

Structured Observation

In structured observation, the researcher defines a set of behaviors or events to be observed and records their occurrence.

Unstructured Observation

In unstructured observation, the researcher observes and records any behaviors or events that occur without predetermined categories.

Cross-Sectional Observation

In cross-sectional observation, the researcher observes and records the behavior of different individuals or groups at a single point in time.

Longitudinal Observation

In longitudinal observation, the researcher observes and records the behavior of the same individuals or groups over an extended period of time.

Data Collection Methods

Observational research uses various data collection methods to gather information about the behaviors and experiences of individuals or groups being observed. Some common data collection methods used in observational research include:

Field Notes

This method involves recording detailed notes of the observed behavior, events, and interactions. These notes are usually written in real-time during the observation process.

Audio and Video Recordings

Audio and video recordings can be used to capture the observed behavior and interactions. These recordings can be later analyzed to extract relevant information.

Surveys and Questionnaires

Surveys and questionnaires can be used to gather additional information from the individuals or groups being observed. This method can be used to validate or supplement the observational data.

Time Sampling

This method involves taking a snapshot of the observed behavior at pre-determined time intervals. This method helps to identify the frequency and duration of the observed behavior.

Event Sampling

This method involves recording specific events or behaviors that are of interest to the researcher. This method helps to provide detailed information about specific behaviors or events.

Checklists and Rating Scales

Checklists and rating scales can be used to record the occurrence and frequency of specific behaviors or events. This method helps to simplify and standardize the data collection process.

Observational Data Analysis Methods

Observational Data Analysis Methods are:

Descriptive Statistics

This method involves using statistical techniques such as frequency distributions, means, and standard deviations to summarize the observed behaviors, events, or interactions.

Qualitative Analysis

Qualitative analysis involves identifying patterns and themes in the observed behaviors or interactions. This analysis can be done manually or with the help of software tools.

Content Analysis

Content analysis involves categorizing and counting the occurrences of specific behaviors or events. This analysis can be done manually or with the help of software tools.

Time-series Analysis

Time-series analysis involves analyzing the changes in behavior or interactions over time. This analysis can help identify trends and patterns in the observed data.

Inter-observer Reliability Analysis

Inter-observer reliability analysis involves comparing the observations made by multiple observers to ensure the consistency and reliability of the data.

Multivariate Analysis

Multivariate analysis involves analyzing multiple variables simultaneously to identify the relationships between the observed behaviors, events, or interactions.

Event Coding

This method involves coding observed behaviors or events into specific categories and then analyzing the frequency and duration of each category.

Cluster Analysis

Cluster analysis involves grouping similar behaviors or events into clusters based on their characteristics or patterns.

Latent Class Analysis

Latent class analysis involves identifying subgroups of individuals or groups based on their observed behaviors or interactions.

Social network Analysis

Social network analysis involves mapping the social relationships and interactions between individuals or groups based on their observed behaviors.

The choice of data analysis method depends on the research question, the type of data collected, and the available resources. Researchers should choose the appropriate method that best fits their research question and objectives. It is also important to ensure the validity and reliability of the data analysis by using appropriate statistical tests and measures.

Applications of Observational Research

Observational research is a versatile research method that can be used in a variety of fields to explore and understand human behavior, attitudes, and preferences. Here are some common applications of observational research:

Psychology : Observational research is commonly used in psychology to study human behavior in natural settings. This can include observing children at play to understand their social development or observing people’s reactions to stress to better understand how stress affects behavior.
Marketing : Observational research is used in marketing to understand consumer behavior and preferences. This can include observing shoppers in stores to understand how they make purchase decisions or observing how people interact with advertisements to determine their effectiveness.
Education : Observational research is used in education to study teaching and learning in natural settings. This can include observing classrooms to understand how teachers interact with students or observing students to understand how they learn.
Anthropology : Observational research is commonly used in anthropology to understand cultural practices and beliefs. This can include observing people’s daily routines to understand their culture or observing rituals and ceremonies to better understand their significance.
Healthcare : Observational research is used in healthcare to understand patient behavior and preferences. This can include observing patients in hospitals to understand how they interact with healthcare professionals or observing patients with chronic illnesses to better understand their daily routines and needs.
Sociology : Observational research is used in sociology to understand social interactions and relationships. This can include observing people in public spaces to understand how they interact with others or observing groups to understand how they function.
Ecology : Observational research is used in ecology to understand the behavior and interactions of animals and plants in their natural habitats. This can include observing animal behavior to understand their social structures or observing plant growth to understand their response to environmental factors.
Criminology : Observational research is used in criminology to understand criminal behavior and the factors that contribute to it. This can include observing criminal activity in a particular area to identify patterns or observing the behavior of inmates to understand their experience in the criminal justice system.

Observational Research Examples

Here are some real-time observational research examples:

A researcher observes and records the behaviors of a group of children on a playground to study their social interactions and play patterns.
A researcher observes the buying behaviors of customers in a retail store to study the impact of store layout and product placement on purchase decisions.
A researcher observes the behavior of drivers at a busy intersection to study the effectiveness of traffic signs and signals.
A researcher observes the behavior of patients in a hospital to study the impact of staff communication and interaction on patient satisfaction and recovery.
A researcher observes the behavior of employees in a workplace to study the impact of the work environment on productivity and job satisfaction.
A researcher observes the behavior of shoppers in a mall to study the impact of music and lighting on consumer behavior.
A researcher observes the behavior of animals in their natural habitat to study their social and feeding behaviors.
A researcher observes the behavior of students in a classroom to study the effectiveness of teaching methods and student engagement.
A researcher observes the behavior of pedestrians and cyclists on a city street to study the impact of infrastructure and traffic regulations on safety.

How to Conduct Observational Research

Here are some general steps for conducting Observational Research:

Define the Research Question: Determine the research question and objectives to guide the observational research study. The research question should be specific, clear, and relevant to the area of study.
Choose the appropriate observational method: Choose the appropriate observational method based on the research question, the type of data required, and the available resources.
Plan the observation: Plan the observation by selecting the observation location, duration, and sampling technique. Identify the population or sample to be observed and the characteristics to be recorded.
Train observers: Train the observers on the observational method, data collection tools, and techniques. Ensure that the observers understand the research question and objectives and can accurately record the observed behaviors or events.
Conduct the observation : Conduct the observation by recording the observed behaviors or events using the data collection tools and techniques. Ensure that the observation is conducted in a consistent and unbiased manner.
Analyze the data: Analyze the observed data using appropriate data analysis methods such as descriptive statistics, qualitative analysis, or content analysis. Validate the data by checking the inter-observer reliability and conducting statistical tests.
Interpret the results: Interpret the results by answering the research question and objectives. Identify the patterns, trends, or relationships in the observed data and draw conclusions based on the analysis.
Report the findings: Report the findings in a clear and concise manner, using appropriate visual aids and tables. Discuss the implications of the results and the limitations of the study.

When to use Observational Research

Here are some situations where observational research can be useful:

Exploratory Research: Observational research can be used in exploratory studies to gain insights into new phenomena or areas of interest.
Hypothesis Generation: Observational research can be used to generate hypotheses about the relationships between variables, which can be tested using experimental research.
Naturalistic Settings: Observational research is useful in naturalistic settings where it is difficult or unethical to manipulate the environment or variables.
Human Behavior: Observational research is useful in studying human behavior, such as social interactions, decision-making, and communication patterns.
Animal Behavior: Observational research is useful in studying animal behavior in their natural habitats, such as social and feeding behaviors.
Longitudinal Studies: Observational research can be used in longitudinal studies to observe changes in behavior over time.
Ethical Considerations: Observational research can be used in situations where manipulating the environment or variables would be unethical or impractical.

Purpose of Observational Research

Observational research is a method of collecting and analyzing data by observing individuals or phenomena in their natural settings, without manipulating them in any way. The purpose of observational research is to gain insights into human behavior, attitudes, and preferences, as well as to identify patterns, trends, and relationships that may exist between variables.

The primary purpose of observational research is to generate hypotheses that can be tested through more rigorous experimental methods. By observing behavior and identifying patterns, researchers can develop a better understanding of the factors that influence human behavior, and use this knowledge to design experiments that test specific hypotheses.

Observational research is also used to generate descriptive data about a population or phenomenon. For example, an observational study of shoppers in a grocery store might reveal that women are more likely than men to buy organic produce. This type of information can be useful for marketers or policy-makers who want to understand consumer preferences and behavior.

In addition, observational research can be used to monitor changes over time. By observing behavior at different points in time, researchers can identify trends and changes that may be indicative of broader social or cultural shifts.

Overall, the purpose of observational research is to provide insights into human behavior and to generate hypotheses that can be tested through further research.

Advantages of Observational Research

There are several advantages to using observational research in different fields, including:

Naturalistic observation: Observational research allows researchers to observe behavior in a naturalistic setting, which means that people are observed in their natural environment without the constraints of a laboratory. This helps to ensure that the behavior observed is more representative of the real-world situation.
Unobtrusive : Observational research is often unobtrusive, which means that the researcher does not interfere with the behavior being observed. This can reduce the likelihood of the research being affected by the observer’s presence or the Hawthorne effect, where people modify their behavior when they know they are being observed.
Cost-effective : Observational research can be less expensive than other research methods, such as experiments or surveys. Researchers do not need to recruit participants or pay for expensive equipment, making it a more cost-effective research method.
Flexibility: Observational research is a flexible research method that can be used in a variety of settings and for a range of research questions. Observational research can be used to generate hypotheses, to collect data on behavior, or to monitor changes over time.
Rich data : Observational research provides rich data that can be analyzed to identify patterns and relationships between variables. It can also provide context for behaviors, helping to explain why people behave in a certain way.
Validity : Observational research can provide high levels of validity, meaning that the results accurately reflect the behavior being studied. This is because the behavior is being observed in a natural setting without interference from the researcher.

Disadvantages of Observational Research

While observational research has many advantages, it also has some limitations and disadvantages. Here are some of the disadvantages of observational research:

Observer bias: Observational research is prone to observer bias, which is when the observer’s own beliefs and assumptions affect the way they interpret and record behavior. This can lead to inaccurate or unreliable data.
Limited generalizability: The behavior observed in a specific setting may not be representative of the behavior in other settings. This can limit the generalizability of the findings from observational research.
Difficulty in establishing causality: Observational research is often correlational, which means that it identifies relationships between variables but does not establish causality. This can make it difficult to determine if a particular behavior is causing an outcome or if the relationship is due to other factors.
Ethical concerns: Observational research can raise ethical concerns if the participants being observed are unaware that they are being observed or if the observations invade their privacy.
Time-consuming: Observational research can be time-consuming, especially if the behavior being observed is infrequent or occurs over a long period of time. This can make it difficult to collect enough data to draw valid conclusions.
Difficulty in measuring internal processes: Observational research may not be effective in measuring internal processes, such as thoughts, feelings, and attitudes. This can limit the ability to understand the reasons behind behavior.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Observational Techniques in Marketing Research

Through direct observation of people, marketing specialists are able to identify actions and watch how subjects respond to various stimuli. For a small business, observational marketing research is one of the most simple ways that one can find out many things about their customers and clients.

Observational Technique Definition

Observational marketing research is a qualitative method of collecting and analyzing information obtained through directly or indirectly watching and observing others in natural or planned environments, according to Zoho. It is often the first, and sometimes only, step in developing a marketing plan or project. Social research techniques and observational research methods may be done covertly or overtly to obtain the best, most efficient results. Additionally, researchers may participate in the experience to provide a more informed report.

Advantages of Observational Techniques

There are many advantages to utilizing observation techniques when conducing marketing research for your small business, says Fuel Cycle. During observation only, subjects often behave more naturally and do not purport to demonstrate their "ideal selves" instead of their true actions. Recall error is not a problem when conducting observational research. In clinical settings, behaviors are reported in relationship to activities or other stimuli.

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In observational research done in natural settings, subjects are reported as doing exactly as what was observed. Observational research can be modified to obtain the best results possible, if necessary. For instance, if one cannot see clearly enough from a particular location, he may choose to move to a closer observing spot. Observational techniques often provide the only way to conduct certain research, such as determining the number of shoppers visiting a store or the behavior of children.

Disadvantages of Observational Techniques

While observational techniques have many advantages, they also have some faults, too. Researchers have no control over the situations and environments typically used in observational research. Additionally, observational research is time consuming. One must have patience and time to devote to watching a set number of individuals or settings to obtain the information necessary. Researchers may also become distracted while observing, which can taint the results of the research. Anomalies may pose themselves as regular occurrences without the high accuracy of statistics, making it hard to build a comprehensive market observation report.

Examples of Observational Techniques

Several common marketing observation examples exist and are used frequently. Perhaps, one of the most common ways researchers use observational techniques is through cookies on computers, used to track users' web views and visits.

Focus groups utilize observational techniques, as does the Nielson ratings used to track popular viewing habits of television programs. Transportation departments use observational research to conduct traffic counts and usage patterns. Many retail marketers use observational techniques when they count license plates in parking lots, record purchasing behavior through bar-coded transactions and observe package scrutiny and preference.

Zoho: Conducting Observational Research for Your Business
Fuel Cycle: The 3 Most Common Observation Research Methods

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What is an Observational Study: Definition & Examples

By Jim Frost 10 Comments

What is an Observational Study?

An observational study uses sample data to find correlations in situations where the researchers do not control the treatment, or independent variable, that relates to the primary research question. The definition of an observational study hinges on the notion that the researchers only observe subjects and do not assign them to the control and treatment groups. That’s the key difference between an observational study vs experiment. These studies are also known as quasi-experiments and correlational studies .

True experiments assign subject to the experimental groups where the researchers can manipulate the conditions. Unfortunately, random assignment is not always possible. For these cases, you can conduct an observational study.

In this post, learn about the types of observational studies, why they are susceptible to confounding variables, and how they compare to experiments. I’ll close this post by reviewing a published observational study about vitamin supplement usage.

Observational Study Definition

In an observational study, the researchers only observe the subjects and do not interfere or try to influence the outcomes. In other words, the researchers do not control the treatments or assign subjects to experimental groups. Instead, they observe and measure variables of interest and look for relationships between them. Usually, researchers conduct observational studies when it is difficult, impossible, or unethical to assign study participants to the experimental groups randomly. If you can’t randomly assign subjects to the treatment and control groups, then you observe the subjects in their self-selected states.

Observational Study vs Experiment

Randomized experiments provide better results than observational studies. Consequently, you should always use a randomized experiment whenever possible. However, if randomization is not possible, science should not come to a halt. After all, we still want to learn things, discover relationships, and make discoveries. For these cases, observational studies are a good alternative to a true experiment. Let’s compare the differences between an observational study vs. an experiment.

Random assignment in an experiment reduces systematic differences between experimental groups at the beginning of the study, which increases your confidence that the treatments caused any differences between groups you observe at the end of the study. In contrast, an observational study uses self-formed groups that can have pre-existing differences, which introduces the problem of confounding variables. More on that later!

In a randomized experiment, randomization tends to equalize confounders between groups and, thereby, prevents problems. In my post about random assignment , I describe that process as an elegant solution for confounding variables. You don’t need to measure or even know which variables are confounders, and randomization will still mitigate their effects. Additionally, you can use control variables in an experiment to keep the conditions as consistent as possible. For more detail about the differences, read Observational Study vs. Experiment .



Does not assign subjects to groups	Randomly assigns subjects to control and treatment groups
Does not control variables that can affect outcome	Administers treatments and controls influence of other variables
Correlational findings. Differences might be due to confounders rather than the treatment	More confident that treatments cause the differences in outcomes

If you’re looking for a middle ground choice between observational studies vs experiments, consider using a quasi-experimental design. These methods don’t require you to randomly assign participants to the experimental groups and still allow you to draw better causal conclusions about an intervention than an observational study. Learn more about Quasi-Experimental Design Overview & Examples .

Related posts : Experimental Design: Definition and Examples , Randomized Controlled Trials (RCTs) , and Control Groups in Experiments

Observational Study Examples

Photograph of a person observing to illustrate an observational study.

Consider using an observational study when random assignment for an experiment is problematic. This approach allows us to proceed and draw conclusions about effects even though we can’t control the independent variables. The following observational study examples will help you understand when and why to use them.

For example, if you’re studying how depression affects performance of an activity, it’s impossible to assign subjects to the depression and control group randomly. However, you can have subjects with and without depression perform the activity and compare the results in an observational study.

Or imagine trying to assign subjects to cigarette smoking and non-smoking groups randomly?! However, you can observe people in both groups and assess the differences in health outcomes in an observational study.

Suppose you’re studying a treatment for a disease. Ideally, you recruit a group of patients who all have the disease, and then randomly assign them to the treatment and control group. However, it’s unethical to withhold the treatment, which rules out a control group. Instead, you can compare patients who voluntarily do not use the medicine to those who do use it.

In all these observational study examples, the researchers do not assign subjects to the experimental groups. Instead, they observe people who are already in these groups and compare the outcomes. Hence, the scientists must use an observational study vs. an experiment.

Types of Observational Studies

The observational study definition states that researchers only observe the outcomes and do not manipulate or control factors . Despite this limitation, there various types of observational studies.

The following experimental designs are three standard types of observational studies.

Cohort Study : A longitudinal observational study that follows a group who share a defining characteristic. These studies frequently determine whether exposure to risk factor affects an outcome over time.
Case-Control Study : A retrospective observational study that compares two existing groups—the case group with the condition and the control group without it. Researchers compare the groups looking for potential risk factors for the condition.
Cross-Sectional Study : Takes a snapshot of a moment in time so researchers can understand the prevalence of outcomes and correlations between variables at that instant.

Qualitative research studies are usually observational in nature, but they collect non-numeric data and do not perform statistical analyses.

Retrospective studies must be observational.

Later in this post, we’ll closely examine a quantitative observational study example that assesses vitamin supplement consumption and how that affects the risk of death. It’s possible to use random assignment to place each subject in either the vitamin treatment group or the control group. However, the study assesses vitamin consumption in 40,000 participants over the course of two decades. It’s unrealistic to enforce the treatment and control protocols over such a long time for so many people!

Drawbacks of Observational Studies

While observational studies get around the inability to assign subjects randomly, this approach opens the door to the problem of confounding variables. A confounding variable, or confounder, correlates with both the experimental groups and the outcome variable. Because there is no random process that equalizes the experimental groups in an observational study, confounding variables can systematically differ between groups when the study begins. Consequently, confounders can be the actual cause for differences in outcome at the end of the study rather than the primary variable of interest. If an experiment does not account for confounding variables, confounders can bias the results and create spurious correlations .

Performing an observational study can decrease the internal validity of your study but increase the external validity. Learn more about internal and external validity .

Let’s see how this works. Imagine an observational study that compares people who take vitamin supplements to those who do not. People who use vitamin supplements voluntarily will tend to have other healthy habits that exist at the beginning of the study. These healthy habits are confounding variables. If there are differences in health outcomes at the end of the study, it’s possible that these healthy habits actually caused them rather than the vitamin consumption itself. In short, confounders confuse the results because they provide alternative explanations for the differences.

Despite the limitations, an observational study can be a valid approach. However, you must ensure that your research accounts for confounding variables. Fortunately, there are several methods for doing just that!

Learn more about Correlation vs. Causation: Understanding the Differences .

Accounting for Confounding Variables in an Observational Study

Because observational studies don’t use random assignment, confounders can be distributed disproportionately between conditions. Consequently, experimenters need to know which variables are confounders, measure them, and then use a method to account for them. It involves more work, and the additional measurements can increase the costs. And there’s always a chance that researchers will fail to identify a confounder, not account for it, and produce biased results. However, if randomization isn’t an option, then you probably need to consider an observational study.

Trait matching and statistically controlling confounders using multivariate procedures are two standard approaches for incorporating confounding variables.

Related post : Causation versus Correlation in Statistics

Matching in Observational Studies

Matching is a technique that involves selecting study participants with similar characteristics outside the variable of interest or treatment. Rather than using random assignment to equalize the experimental groups, the experimenters do it by matching observable characteristics. For every participant in the treatment group, the researchers find a participant with comparable traits to include in the control group. Matching subjects facilitates valid comparisons between those groups. The researchers use subject-area knowledge to identify characteristics that are critical to match.

For example, a vitamin supplement study using matching will select subjects who have similar health-related habits and attributes. The goal is that vitamin consumption will be the primary difference between the groups, which helps you attribute differences in health outcomes to vitamin consumption. However, the researchers are still observing participants who decide whether they consume supplements.

Matching has some drawbacks. The experimenters might not be aware of all the relevant characteristics they need to match. In other words, the groups might be different in an essential aspect that the researchers don’t recognize. For example, in the hypothetical vitamin study, there might be a healthy habit or attribute that affects the outcome that the researchers don’t measure and match. These unmatched characteristics might cause the observed differences in outcomes rather than vitamin consumption.

Learn more about Matched Pairs Design: Uses & Examples .

Using Multiple Regression in Observational Studies

Random assignment and matching use different methods to equalize the experimental groups in an observational study. However, statistical techniques, such as multiple regression analysis , don’t try to equalize the groups but instead use a model that accounts for confounding variables. These studies statistically control for confounding variables.

In multiple regression analysis, including a variable in the model holds it constant while you vary the variable/treatment of interest. For information about this property, read my post When Should I Use Regression Analysis?

As with matching, the challenge is to identify, measure, and include all confounders in the regression model. Failure to include a confounding variable in a regression model can cause omitted variable bias to distort your results.

Next, we’ll look at a published observational study that uses multiple regression to account for confounding variables.

Related post : Independent and Dependent Variables in a Regression Model

Vitamin Supplement Observational Study Example

Vitamins for the example of an observational study.

Murso et al. (2011)* use a longitudinal observational study that ran 22 years to assess differences in death rates for subjects who used vitamin supplements regularly compared to those who did not use them. This study used surveys to record the characteristics of approximately 40,000 participants. The surveys asked questions about potential confounding variables such as demographic information, food intake, health details, physical activity, and, of course, supplement intake.

Because this is an observational study, the subjects decided for themselves whether they were taking vitamin supplements. Consequently, it’s safe to assume that supplement users and non-users might be different in other ways. From their article, the researchers found the following pre-existing differences between the two groups:

Supplement users had a lower prevalence of diabetes mellitus, high blood pressure, and smoking status; a lower BMI and waist to hip ratio, and were less likely to live on a farm. Supplement users had a higher educational level, were more physically active and were more likely to use estrogen replacement therapy. Also, supplement users were more likely to have a lower intake of energy, total fat, and monounsaturated fatty acids, saturated fatty acids and to have a higher intake of protein, carbohydrates, polyunsaturated fatty acids, alcohol, whole grain products, fruits, and vegetables.

Whew! That’s a long list of differences! Supplement users were different from non-users in a multitude of ways that are likely to affect their risk of dying. The researchers must account for these confounding variables when they compare supplement users to non-users. If they do not, their results can be biased.

This example illustrates a key difference between an observational study vs experiment. In a randomized experiment, the randomization would have equalized the characteristics of those the researchers assigned to the treatment and control groups. Instead, the study works with self-sorted groups that have numerous pre-existing differences!

Using Multiple Regression to Statistically Control for Confounders

To account for these initial differences in the vitamin supplement observational study, the researchers use regression analysis and include the confounding variables in the model.

The researchers present three regression models. The simplest model accounts only for age and caloric intake. Next, are two models that include additional confounding variables beyond age and calories. The first model adds various demographic information and seven health measures. The second model includes everything in the previous model and adds several more specific dietary intake measures. Using statistical significance as a guide for specifying the correct regression model , the researchers present the model with the most variables as the basis for their final results.

It’s instructive to compare the raw results and the final regression results.

Raw results

The raw differences in death risks for consumers of folic acid, vitamin B6, magnesium, zinc, copper, and multivitamins are NOT statistically significant. However, the raw results show a significant reduction in the death risk for users of B complex, C, calcium, D, and E.

However, those are the raw results for the observational study, and they do not control for the long list of differences between the groups that exist at the beginning of the study. After using the regression model to control for the confounding variables statistically, the results change dramatically.

Adjusted results

Of the 15 supplements that the study tracked in the observational study, researchers found consuming seven of these supplements were linked to a statistically significant INCREASE in death risk ( p-value < 0.05): multivitamins (increase in death risk 2.4%), vitamin B6 (4.1%), iron (3.9%), folic acid (5.9%), zinc (3.0%), magnesium (3.6%), and copper (18.0%). Only calcium was associated with a statistically significant reduction in death risk of 3.8%.

In short, the raw results suggest that those who consume supplements either have the same or lower death risks than non-consumers. However, these results do not account for the multitude of healthier habits and attributes in the group that uses supplements.

In fact, these confounders seem to produce most of the apparent benefits in the raw results because, after you statistically control the effects of these confounding variables, the results worsen for those who consume vitamin supplements. The adjusted results indicate that most vitamin supplements actually increase your death risk!

This research illustrates the differences between an observational study vs experiment. Namely how the pre-existing differences between the groups allow confounders to bias the raw results, making the vitamin consumption outcomes look better than they really are.

In conclusion, if you can’t randomly assign subjects to the experimental groups, an observational study might be right for you. However, be aware that you’ll need to identify, measure, and account for confounding variables in your experimental design.

Jaakko Mursu, PhD; Kim Robien, PhD; Lisa J. Harnack, DrPH, MPH; Kyong Park, PhD; David R. Jacobs Jr, PhD; Dietary Supplements and Mortality Rate in Older Women: The Iowa Women’s Health Study ; Arch Intern Med . 2011;171(18):1625-1633.

Reader Interactions

December 30, 2023 at 5:05 am

I see, but our professor required us to indicate what year it was put into the article. May you tell me what year was this published originally? <3

December 30, 2023 at 3:40 pm

December 29, 2023 at 10:46 am

Hi, may I use your article as a citation for my thesis paper? If so, may I know the exact date you published this article? Thank you!

December 29, 2023 at 2:13 pm

Definitely feel free to cite this article! 🙂

When citing online resources, you typically use an “Accessed” date rather than a publication date because online content can change over time. For more information, read Purdue University’s Citing Electronic Resources .

November 18, 2021 at 10:09 pm

Love your content and has been very helpful!

Can you please advise the question below using an observational data set:

I have three years of observational GPS data collected on athletes (2019/2020/2021). Approximately 14-15 athletes per game and 8 games per year. The GPS software outputs 50+ variables for each athlete in each game, which we have narrowed down to 16 variables of interest from previous research.

2 factors 1) Period (first half, second half, and whole game), 2) Position (two groups with three subgroups in each – forwards (group 1, group 2, group 3) and backs (group 1, group 2, group 3))

16 variables of interest – all numerical and scale variables. Some of these are correlated, but not all.

My understanding is that I can use a oneway ANOVA for each year on it’s own, using one factor at a time (period or position) with post hoc analysis. This is fine, if data meets assumptions and is normally distributed. This tells me any significant interactions between variables of interest with chosen factor. For example, with position factor, do forwards in group 1 cover more total running distance than forwards in group 2 or backs in group 3.

However, I want to go deeper with my analysis. If I want to see if forwards in group 1 cover more total running distance in period 1 than backs in group 3 in the same period, I need an additional factor and the oneway ANOVA does not suit. Therefore I can use a twoway ANOVA instead of 2 oneway ANOVA’s and that solves the issue, correct?

This is complicated further by looking to compare 2019 to 2020 or 2019 to 2021 to identify changes over time, which would introduce a third independent variable.

I believe this would require a threeway ANOVA for this observational data set. 3 factors – Position, Period, and Year?

Are there any issues or concerns you see at first glance?

I appreciate your time and consideration.

April 12, 2021 at 2:02 pm

Could an observational study use a correlational design.

e.g. measuring effects of two variables on happiness, if you’re not intervening.

April 13, 2021 at 12:14 am

Typically, with observational studies, you’d want to include potential confounders, etc. Consequently, I’ve seen regression analysis used more frequently for observational studies to be able to control for other things because you’re not using randomization. You could use correlation to observe the relationship. However, you wouldn’t be controlling for potential confounding variables. Just something to consider.

April 11, 2021 at 1:28 pm

Hi, If I am to administer moderate doses of coffee for a hypothetical experiment, does it raise ethical concerns? Can I use random assignment for it?

April 11, 2021 at 4:06 pm

I don’t see any inherent ethical problems here as long as you describe the participant’s experience in the experiment including the coffee consumption. They key with human subjects is “informed consent.” They’re agreeing to participate based on a full and accurate understanding of what participation involves. Additionally, you as a researcher, understand the process well enough to be able to ensure their safety.

In your study, as long as subject know they’ll be drinking coffee and agree to that, I don’t see a problem. It’s a proven safe substance for the vast majority of people. If potential subjects are aware of the need to consume coffee, they can determine whether they are ok with that before agreeing to participate.

June 17, 2019 at 4:51 am

Really great article which explains observational and experimental study very well. It presents broad picture with the case study which helped a lot in understanding the core concepts. Thanks

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Fuel Cycle Blog: The 3 Most Common Observation Research Methods

Some researchers call self-reported research the Achillie’s heal of survey data collection in terms of reliability.

The reason? Self-reported research is sometimes inaccurate and thwarted by a consumer’s misguided perception.

For example, research states that some polls reported that 40% of Americans attended church every week. However, when Marlar and Hadaway (2005) examined actual church attendance records, they found the actual percentage was closer to fewer than 22% attendance every week. This is a prime example of self-reporting gone wrong.

Additionally, Seth Stephens-Davidowitz found that sometimes survey respondents outright lie about their perceptions on sensitive topics to present a better view of themselves.

If the reliability of survey research comes into question, and market researchers need accurate data to inform marketing, product, and business decisions, what is the solution?

The answer? Observational research.

This article will dive deeper into what observational research is, when you should use it, and what the three types of observational research are.

What is Observational Research?

Observation research is a qualitative research technique where researchers observe participants’ ongoing behavior in a natural situation.

Depending on the type of observation research and the goal of the study, the market researcher will have varying levels of participation in the study. Sometimes the researcher will insert themselves into the environment, and other times, the researcher will not intervene in the setting and observe from a distance or in a laboratory setting.

The purpose of this type of research is to gather more reliable insights. In other words, researchers can capture data on what participants do as opposed to what they say they do.

When should a market researcher use observational research?

As a market researcher, you have several different research methodologies at your disposal, including surveys, interviews, observations, etc.

Using observational data is best when one of the following situations apply:

You need to gather sensitive information, and you don’t trust your participants will be honest with their self-reporting.
You need to understand the how or what of a research question .
The topic is new, and you need robust data to explain consumer behavior.
When behavior in a natural setting is vital to your research question.
When behavior in a controlled setting is critical to your research question.
If you are concerned that self-reported data about behaviors will differ from actual actions, even if it’s unintentional.
When you need more information about a specific research question to formulate a more complete and accurate survey.

If any of these situations describe you or your current research state, then an observational study may be just what you need.

What are the three types of observational research?

When it comes to observational research, you have three different types of methodologies: controlled observations , naturalistic observations, and participant observations .

Let’s quickly look at what each type of observation includes, how they differ, and the strengths and weaknesses of each type of observation.

1. Controlled observation

Controlled observations are typically a structured observation that takes place in a psych lab. The researcher has a question in mind and controls many of the variables, including participants, observation location, time of the study, circumstances surrounding the research, and more.

During this type of study, the researcher will often create codes that represent different types of behaviors. That way, instead of writing a detailed report, they can classify behavior into different categories and analyze the data with more ease.

Advantages and limitations of controlled observation

The advantages of controlled observation include:

You can make an observation schedule for your sampling, and have other market researchers use the same codes if they replicate the study. This helps test for reliability.
The coded data is easy to analyze and quantify.
Controlled studies aren’t as time-consuming.

Limitations of a controlled observation include:

It may be challenging to determine the validity of the study if participants know they are being watched.

2. Naturalistic observation

Naturalistic observation is another type of observation research method used by market researchers. This type of observation is when market researchers study the behaviors of participants in a natural surrounding. There are typically no predetermined behavioral codes. Instead, the researcher will take rigorous notes and code the data later.

Advantages and limitations of naturalistic observation

Some advantages of naturalistic observation include:

The study ensures validity when participants are in their natural setting.
This type of study can generate new ideas and research questions.
It opens researchers’ minds to possibilities they might not have considered before.
Researchers can collect authentic data and avoid any potential problems with self-reported data.

Some limitations include:

You can’t control different variables, making it difficult to replicate the study and test for reliability.
It may be challenging to conduct this type of study on a wide scale.
You have to use skilled researchers, so you don’t risk missing critical behavioral data.
You aren’t able to manipulate any variables.

3. Participant observation

The last type of observation method is participant observation. This is a type of naturalistic observation in the fact that market researchers will observe participants in their natural habitat. The difference is market researchers will insert themselves into the environment.

Advantages and limitations of participant observation

Some advantages of this type of observation include:

You can control some of the variables by being part of the natural environment.
You can still observe participants in their natural habitat, even if they know you are part of the study.
You can avoid incorrect self-reported data through this method of observation as well.

Here are some limitations to this type of study to consider:

It can be challenging to take notes openly without blowing your cover as the market researcher.
If you can’t take notes openly, you’ll have to rely on memory for note-taking, and memory can be faulty.
If a researcher becomes too involved in the study, they could become less objective. This could threaten the validity of the study.

Each type of study will help you gather insight into how customers and participants behave, but they also come with their own set of limitations.

If you are looking to conduct a reliable study and answer your research question more robustly, then one of the three types of observation research methods can help.

Remember, quantifying observation research doesn’t have to be difficult when you have the right tools to help you. For more information about observation research tools , request a Fuel Cycle demo today.

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What Is an Observational Study? | Guide & Examples

What Is an Observational Study? | Guide & Examples

Published on 5 April 2022 by Tegan George . Revised on 20 March 2023.

An observational study is used to answer a research question based purely on what the researcher observes. There is no interference or manipulation of the research subjects, and no control and treatment groups .

These studies are often qualitative in nature and can be used for both exploratory and explanatory research purposes. While quantitative observational studies exist, they are less common.

Observational studies are generally used in hard science, medical, and social science fields. This is often due to ethical or practical concerns that prevent the researcher from conducting a traditional experiment . However, the lack of control and treatment groups means that forming inferences is difficult, and there is a risk of confounding variables impacting your analysis.

Types of observation, types of observational studies, observational study example, advantages and disadvantages of observational studies, observational study vs experiment, frequently asked questions.

There are many types of observation, and it can be challenging to tell the difference between them. Here are some of the most common types to help you choose the best one for your observational study.


	The researcher observes how the participants respond to their environment in ‘real-life’ settings but does not influence their behavior in any way	Observing monkeys in a zoo enclosure
	Also occurs in ‘real-life’ settings, but here, the researcher immerses themselves in the participant group over a period of time	Spending a few months in a hospital with patients suffering from a particular illness
	Utilising coding and a strict observational schedule, researchers observe participants in order to count how often a particular phenomenon occurs	Counting the number of times children laugh in a classroom
	Hinges on the fact that the participants do not know they are being observed	Observing interactions in public spaces, like bus rides or parks
	Involves counting or numerical data	Observations related to age, weight, or height
	Involves ‘five senses’: sight, sound, smell, taste, or hearing	Observations related to colors, sounds, or music
	Investigates a person or group of people over time, with the idea that close investigation can later be to other people or groups	Observing a child or group of children over the course of their time in elementary school
	Utilises primary sources from libraries, archives, or other repositories to investigate a research question	Analysing US Census data or telephone records

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There are three main types of observational studies: cohort studies, case–control studies, and cross-sectional studies.

Cohort studies

Cohort studies are more longitudinal in nature, as they follow a group of participants over a period of time. Members of the cohort are selected because of a shared characteristic, such as smoking, and they are often observed over a period of years.

Case–control studies

Case–control studies bring together two groups, a case study group and a control group . The case study group has a particular attribute while the control group does not. The two groups are then compared, to see if the case group exhibits a particular characteristic more than the control group.

For example, if you compared smokers (the case study group) with non-smokers (the control group), you could observe whether the smokers had more instances of lung disease than the non-smokers.

Cross-sectional studies

Cross-sectional studies analyse a population of study at a specific point in time.

This often involves narrowing previously collected data to one point in time to test the prevalence of a theory—for example, analysing how many people were diagnosed with lung disease in March of a given year. It can also be a one-time observation, such as spending one day in the lung disease wing of a hospital.

Observational studies are usually quite straightforward to design and conduct. Sometimes all you need is a notebook and pen! As you design your study, you can follow these steps.

Step 1: Identify your research topic and objectives

The first step is to determine what you’re interested in observing and why. Observational studies are a great fit if you are unable to do an experiment for ethical or practical reasons, or if your research topic hinges on natural behaviors.

Step 2: Choose your observation type and technique

In terms of technique, there are a few things to consider:

Are you determining what you want to observe beforehand, or going in open-minded?
Is there another research method that would make sense in tandem with an observational study?
If yes, make sure you conduct a covert observation.
If not, think about whether observing from afar or actively participating in your observation is a better fit.
How can you preempt confounding variables that could impact your analysis?
You could observe the children playing at the playground in a naturalistic observation.
You could spend a month at a day care in your town conducting participant observation, immersing yourself in the day-to-day life of the children.
You could conduct covert observation behind a wall or glass, where the children can’t see you.

Overall, it is crucial to stay organised. Devise a shorthand for your notes, or perhaps design templates that you can fill in. Since these observations occur in real time, you won’t get a second chance with the same data.

Step 3: Set up your observational study

Before conducting your observations, there are a few things to attend to:

Plan ahead: If you’re interested in day cares, you’ll need to call a few in your area to plan a visit. They may not all allow observation, or consent from parents may be needed, so give yourself enough time to set everything up.
Determine your note-taking method: Observational studies often rely on note-taking because other methods, like video or audio recording, run the risk of changing participant behavior.
Get informed consent from your participants (or their parents) if you want to record: Ultimately, even though it may make your analysis easier, the challenges posed by recording participants often make pen-and-paper a better choice.

Step 4: Conduct your observation

After you’ve chosen a type of observation, decided on your technique, and chosen a time and place, it’s time to conduct your observation.

Here, you can split them into case and control groups. The children with siblings have a characteristic you are interested in (siblings), while the children in the control group do not.

When conducting observational studies, be very careful of confounding or ‘lurking’ variables. In the example above, you observed children as they were dropped off, gauging whether or not they were upset. However, there are a variety of other factors that could be at play here (e.g., illness).

Step 5: Analyse your data

After you finish your observation, immediately record your initial thoughts and impressions, as well as follow-up questions or any issues you perceived during the observation. If you audio- or video-recorded your observations, you can transcribe them.

Your analysis can take an inductive or deductive approach :

If you conducted your observations in a more open-ended way, an inductive approach allows your data to determine your themes.
If you had specific hypotheses prior to conducting your observations, a deductive approach analyses whether your data confirm those themes or ideas you had previously.

Next, you can conduct your thematic or content analysis . Due to the open-ended nature of observational studies, the best fit is likely thematic analysis.

Step 6: Discuss avenues for future research

Observational studies are generally exploratory in nature, and they often aren’t strong enough to yield standalone conclusions due to their very high susceptibility to observer bias and confounding variables. For this reason, observational studies can only show association, not causation .

If you are excited about the preliminary conclusions you’ve drawn and wish to proceed with your topic, you may need to change to a different research method , such as an experiment.

Observational studies can provide information about difficult-to-analyse topics in a low-cost, efficient manner.
They allow you to study subjects that cannot be randomised safely, efficiently, or ethically .
They are often quite straightforward to conduct, since you just observe participant behavior as it happens or utilise preexisting data.
They’re often invaluable in informing later, larger-scale clinical trials or experiments.

Disadvantages

Observational studies struggle to stand on their own as a reliable research method. There is a high risk of observer bias and undetected confounding variables.
They lack conclusive results, typically are not externally valid or generalisable, and can usually only form a basis for further research.
They cannot make statements about the safety or efficacy of the intervention or treatment they study, only observe reactions to it. Therefore, they offer less satisfying results than other methods.

The key difference between observational studies and experiments is that a properly conducted observational study will never attempt to influence responses, while experimental designs by definition have some sort of treatment condition applied to a portion of participants.

However, there may be times when it’s impossible, dangerous, or impractical to influence the behavior of your participants. This can be the case in medical studies, where it is unethical or cruel to withhold potentially life-saving intervention, or in longitudinal analyses where you don’t have the ability to follow your group over the course of their lifetime.

An observational study may be the right fit for your research if random assignment of participants to control and treatment groups is impossible or highly difficult. However, the issues observational studies raise in terms of validity , confounding variables, and conclusiveness can mean that an experiment is more reliable.

If you’re able to randomise your participants safely and your research question is definitely causal in nature, consider using an experiment.

An observational study could be a good fit for your research if your research question is based on things you observe. If you have ethical, logistical, or practical concerns that make an experimental design challenging, consider an observational study. Remember that in an observational study, it is critical that there be no interference or manipulation of the research subjects. Since it’s not an experiment, there are no control or treatment groups either.

The key difference between observational studies and experiments is that, done correctly, an observational study will never influence the responses or behaviours of participants. Experimental designs will have a treatment condition applied to at least a portion of participants.

Exploratory research explores the main aspects of a new or barely researched question.

Explanatory research explains the causes and effects of an already widely researched question.

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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4 Types of Observational Research

Observational research typically happens in the users’ home, workplace, or natural environment and not in a lab or controlled setting.

With this research, you can understand how people naturally interact with products and people and the challenges they face.

It can provide inspiration and ideas for opportunities for improvement and innovation.

While it may seem like observation is as simple and uniform as watching and taking notes, there are some subtle differences that can affect the type of data you collect. The role the observer plays forms a continuum from completely removed to completely engaged with the participant.

As you plan your next observational research project and choose the right type for it to be successful, consider the following:

Ethics of Observing . On both ends of the spectrum (a fully detached or fully engaged observer), you face ethical considerations, as those being observed aren’t aware of it. For that reason, most observational research you’ll conduct falls somewhere in between. Think about quantifying the results . While observational research is typically associated with qualitative methods, you can still quantify the occurrences of behaviors or statements made by the participants to get an idea about the frequency of customer attitudes and actions. Improve the reliability and validity of your observations. Consider having multiple independent researchers observe and code their notes. Using multiple observers with differing perspectives (e.g. product manager and researcher) helps identify areas of agreement and disagreement and makes your observational data more trustworthy and reliable.

Keep these caveats in mind as you chose a role for an observational research project. The four types of observational roles we discuss here are based on the distinctions made by the sociologist Raymond Gold in 1958 but apply to any field of research.

1. Complete Observer

This is a detached observer where the researcher is neither seen nor noticed by participants. It’s one way of minimizing the Hawthorne Effect as participants are more likely to act natural when they don’t know they’re being observed.

While this was once considered an objective role for the ethnographer, it’s fallen out of favor because it’s the role most likely to raise ethical questions about possible deception. How would you feel if you found out someone was watching you, but you didn’t know? Sort of Big Brotherish, most likely.

However, in public places like coffee shops, office building lobbies, airports, subway stations, or even public bathrooms the complete observer role may be the only means to collect the type of data you need. And with the ubiquity of video cameras, remote observation remains a viable option.

2. Observer as Participant

Here the researcher is known and recognized by the participants and in many cases, the participants know the research goals of the observer.

There is some interaction with the participants but the interaction is limited. The researcher’s aim is to play a neutral role as much as possible.

This approach is generally used when “following a customer home” to understand how someone uses software products to accomplish goals.

3. Participant as Observer

Here the researcher is fully engaged with the participants. She is more of a friend or colleague than a neutral third party. While there is full interaction with participants, they still known that this is a researcher.

This method is often used when studying remote indigenous populations or inner-city cultures. There’s an anthropologist joke [pdf] that a household photo of a native village consists of a married couple, their parents, and a graduate student.

4. Complete Participant

This is a fully embedded researcher, almost like a spy. Here the observer fully engages with the participants and partakes in their activities.

Participants aren’t aware that observation and research is being conducted, even though they fully interact with the researcher. This has sometimes been referred to as “going native,” in reference to performing indigenous fieldwork.

In customer research, this is like a secret shopper or the show Undercover Boss . The idea is that the best way to understand a type of role, people, or culture is to experience it firsthand. Want to understand Burning Man ? Then go as a complete participant.

Gathering authentic qualitative data can be a challenge in UX research; one way to do so is with observation outside of a controlled environment where participants are more likely to act natural.

There are four types of observational research you can do, ranging from detached observation with no participation on your part (complete observer) to immersing yourself completely in the environment (complete participant). Which you choose depends on your goals, timeframe, and properly balancing the ethical considerations.

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8 Observational Research

This chapter derived from 6.5 Observational Research by Paul C. Price, Rajiv Jhangiani, I-Chant A. Chiang, Dana C. Leighton, & Carrie Cuttler is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. [1]

Learning Objectives

By the end of this chapter, students must be able to:

Explain different types of observational research methods
Choose an appropriate type of method for a particular situation

WHAT IS OBSERVATIONAL RESEARCH?

The term observational research is used to refer to several different types of non-experimental studies in which behavior is systematically observed and recorded. The goal of observational research is to describe a variable or set of variables. More generally, the goal is to obtain a snapshot of specific characteristics of an individual, group, or setting. As described previously, observational research is non-experimental because nothing is manipulated or controlled, and as such, we cannot arrive at causal conclusions using this approach. The data that is collected in observational research studies are often qualitative in nature but they may also be quantitative or both (mixed-methods). There are several different types of observational research designs that will be described below.

NATURALISTIC VS CONTRIVED OBSERVATION

Naturalistic observation is an observational method that involves observing people’s behavior in the environment in which it typically occurs. Thus naturalistic observation is a type of field research (as opposed to a type of laboratory research). Jane Goodall’s famous research on chimpanzees is a classic example of naturalistic observation. Dr. Goodall spent three decades observing chimpanzees in their natural environment in East Africa. She examined such things as chimpanzees’ social structure, mating patterns, gender roles, family structure, and care of offspring by observing them in the wild. However, naturalistic observation could more simply involve observing shoppers in a grocery store, children on a school playground, or psychiatric inpatients in their wards. Researchers engaged in naturalistic observation usually make their observations as unobtrusively as possible so that participants are not aware that they are being studied. Such an approach is called disguised naturalistic observation. Ethically, this method is considered to be acceptable if the participants remain anonymous and the behavior occurs in a public setting where people would not normally have an expectation of privacy. Grocery shoppers putting items into their shopping carts, for example, are engaged in public behavior that is easily observable by store employees and other shoppers. For this reason, most researchers would consider it ethically acceptable to observe them for a study. On the other hand, one of the arguments against the ethicality of the naturalistic observation of “bathroom behavior” is that people have a reasonable expectation of privacy even in a public restroom and that this expectation was violated.

Contrived observation occurs in an artificial environment, such as a lab setting. For example, researchers may wish to measure people’s physiological responses to an ad that is being screened in the university researcher’s classroom.

Source: DW News. [2]

DISGUISED VS UNDISGUISED OBSERVATION

In cases where it is not ethical or practical to conduct disguised naturalistic observation, researchers can conduct undisguised naturalistic observation where the participants are made aware of the researcher’s presence and monitoring of their behavior. However, one concern with undisguised naturalistic observation is reactivity. Reactivity refers to when a measure changes participants’ behavior. In the case of undisguised naturalistic observation, the concern with reactivity is that when people know they are being observed and studied, they may act differently than they normally would. For instance, you may act much differently in a bar if you know that someone is observing you and recording your behaviors and this would invalidate the study. So disguised observation is less reactive and therefore can have higher validity because people are not aware that their behaviors are being observed and recorded. However, we now know that people often become used to being observed and with time they begin to behave naturally in the researcher’s presence. In other words, over time people habituate to being observed. Think about reality shows like Big Brother or Survivor where people are constantly being observed and recorded. While they may be on their best behavior at first, in a fairly short amount of time they are, flirting, having sex, wearing next to nothing, screaming at each other, and at times acting like complete fools in front of the entire nation.

PARTICIPANT VS MECHANICAL OBSERVATION

Another approach to data collection in observational research is participant observation. In participant observation , researchers become active participants in the group or situation they are studying. Participant observation is very similar to naturalistic observation in that it involves observing people’s behavior in the environment in which it typically occurs. As with naturalistic observation, the data that is collected can include interviews (usually unstructured), notes based on their observations and interactions, documents, photographs, and other artifacts. The only difference between naturalistic observation and participant observation is that researchers engaged in participant observation become active members of the group or situations they are studying. The basic rationale for participant observation is that there may be important information that is only accessible to or can be interpreted only by, someone who is an active participant in the group or situation. Like naturalistic observation, participant observation can be either disguised or undisguised. In disguised participant observation, the researchers pretend to be members of the social group they are observing and conceal their true identity as researchers. In contrast with undisguised participant observation, the researchers become a part of the group they are studying and they disclose their true identity as researchers to the group under investigation. Once again there are important ethical issues to consider with disguised participant observation. First, no informed consent can be obtained and second passive deception is being used. The researcher is passively deceiving the participants by intentionally withholding information about their motivations for being a part of the social group they are studying. But sometimes disguised participation is the only way to access a protective group (like a cult). Further, disguised participant observation is less prone to reactivity than undisguised participant observation.

One of the primary benefits of participant observation is that the researcher is in a much better position to understand the viewpoint and experiences of the people they are studying when they are a part of the social group. The primary limitation with this approach is that the mere presence of the observer could affect the behavior of the people being observed. While this is also a concern with naturalistic observation when researchers because active members of the social group they are studying, additional concerns arise that they may change the social dynamics and/or influence the behavior of the people they are studying. Similarly, if the researcher acts as a participant-observer there can be concerns with biases resulting from developing relationships with the participants. Concretely, the researcher may become less objective resulting in more experimenter bias.

Exhibit 1: Different types of equipment are used to study physiological/neurological responses in humans.

	Neuromorphic camera/sensor equipment

Eye-tracking equipment, Neuromorphic camera/sensor equipment © 2022 Western Sydney University taken by Sally Tsoutas Western Sydney University Photographer is licensed under an Attribution-NonCommercial-NoDerivatives 4.0 International

In many situations, the means of observation are mechanical rather than human. This involves video cameras, traffic counters, checkout scanners, smartphones, and a range of devices that measure physiological responses. These devices include eye-tracking monitors, pupilometers, psychogalvanometers, voice pitch analyzers, and instruments to measure neurological signals.

STRUCTURED VS UNSTRUCTURED OBSERVATION

In structured observation, the emphasis is on gathering quantitative rather than qualitative data. Researchers using this approach are interested in a limited set of behaviors. This allows them to quantify the behaviors they are observing. In other words, structured observation is less global than naturalistic and participant observation because the researcher engaged in structured observations is interested in a small number of specific behaviors. Therefore, rather than recording everything that happens, the researcher only focuses on very specific behaviors of interest. For example, a marketer may be interested in the number of people entering a mall, or the number of times people stop to take a look at a displayed ad. Unstructured observation, on the other hand, is flexible and more informal. There is no checklist for the researcher to follow. The researcher may observe all aspects of a phenomenon and then provides details about things that he/she found to be relevant in understanding a situation. This technique can be more subjective than the structured approach.

When the observations require a judgment on the part of the observers (e.g., do customers look happy while shopping in a store?) this process is often described as coding . Coding generally requires clearly defining a set of target behaviors. The observers then categorize participants individually in terms of which behavior they have engaged in and the number of times they engaged in each behavior. The observers might even record the duration of each behavior. The target behaviors must be defined in such a way that different observers code them in the same way. In one study, for example, researchers video-recorded a subset of their participants’ reactions and had two observers independently code them. The two observers showed that they agreed on the reactions that were exhibited 97% of the time, indicating good interrater reliability.

One of the primary benefits of structured observation is that it is far more efficient than naturalistic and participant observation. Since the researchers are focused on specific behaviors this reduces time and expense. Also, oftentimes the environment is structured to encourage the behaviors of interest which again means that researchers do not have to invest as much time in waiting for the behaviors of interest to naturally occur. Finally, researchers using this approach can clearly exert greater control over the environment. However, when researchers exert more control over the environment it may make the environment less natural which decreases external validity. It is less clear for instance whether structured observations made in a laboratory environment will generalize to a real-world environment. Furthermore, since researchers engaged in structured observation are often not disguised there may be more concerns with reactivity.

OBSERVATION OF PHYSICAL EVIDENCE

Market researchers are able to gather data by observing physical evidence which can provide key insights. Artefacts – such as food cans in garbage bins and counting of physical inventories are key methods that can be used. Content analysis of ads, newspapers, images, or memos can help researchers understand certain aspects of a phenomenon.

Price, PC, Jhangiani, R Chiang, ICA, Leighton, DC & Cuttler, C 2017, 'Observational research' in Research methods in psychology, Pressbooks, chapter 6.5, viewed 2 March 2022, <https://opentext.wsu.edu/carriecuttler/chapter/observational-research/>. ↵
DW News 2013, Market researchers observe where we look: made in Germany, online video, 4 September, viewed 3 March 2022, <https://www.youtube.com/watch?v=Hatmm84sqm0>. ↵

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Aug 14, 2024

What is an observational study? Examples, types & definitions

Insights • Aakash Jethwani • 8 Mins reading time

When it comes to understanding human behavior and interactions, researchers often rely on methods that go beyond mere statistics. One such method is the observational study. But what is an observational study?

At its core, it involves watching and recording individuals in their natural environments without manipulating any variables. This approach allows researchers to gather rich, qualitative data about how people behave and interact in real-world settings.

Observational studies are widely used across fields like psychology , sociology , and market research to uncover insights that might be missed in controlled experiments.

In this blog, we will explore what is an observational study, the different types of observational studies, and how they can be effectively used to gain valuable insights into human behavior.

Observational study definition

An observational study is a research method where the researcher observes and records behavior, events, or phenomena without intervening or manipulating any variables.

The goal is to gather data on how things naturally occur in their usual setting, providing insights into real-world conditions. This type of study can be descriptive, focusing on detailing characteristics or behaviors, or analytical, investigating relationships between variables.

Observational studies are valuable for capturing data in a natural context, but they have limitations, including establishing cause-and-effect relationships and potential biases in data collection and interpretation.

Overall, they are useful for exploring phenomena and generating hypotheses for further research.

Observational study examples

1. naturalistic observation.

In this type of observational study, researchers might observe wildlife in their natural habitats.

Let’s consider this observational study example: a biologist studying the social behaviors of elephants in the wild would document their interactions and movements without disturbing their environment.

This allows for a genuine understanding of the animals’ natural behaviors.

2. Participant observation

Here, researchers immerse themselves in the environment they are studying.

For instance, a sociologist might join a local community group to observe and participate in their activities.

This firsthand experience provides deeper insights into the group’s social dynamics and behaviors.

3. Case study

An example of a case study as an observational study might involve examining a single classroom to understand the effects of different teaching methods on student engagement.

Researchers can gather specific, detailed data on how teaching strategies impact learning by closely observing the classroom setting and interactions.

4. Longitudinal study

In a longitudinal observational study, researchers track the same individuals over a long period.

Consider this observational study example: a health researcher might follow a group of people over several years to observe the long-term effects of dietary habits on their health.

This type of study helps in understanding how changes and developments occur over time.

5. Cross-sectional study

An example of a cross-sectional observational study might involve surveying a population at a single point in time to assess current behaviors or opinions.

For example, a market researcher could survey consumers about their purchasing preferences during a particular season to capture a snapshot of trends and attitudes.

You may like to read about the difference between observational study and experimental study

How to conduct observational study research

Conducting a thorough and effective observational study provides valuable insight into the behaviors, events, or conditions you are investigating.

Here’s a step-by-step guide to show how to conduct an observational study :

1. Define your research question

Begin by clearly defining the research question you aim to answer. This question should guide the focus of your observational study and determine what specific behaviors, events, or conditions you want to observe.

For example, if you’re interested in understanding how students interact in a collaborative learning environment, your research question might be, “How do students engage in group discussions during collaborative activities?”

2. Choose your observational method

Based on your research question and objectives, select the appropriate observational method. Common methods include naturalistic observation , participant observation , case studies, longitudinal studies, and cross-sectional studies .

For instance, if you want to study classroom dynamics, you might choose participant observation to gain an insider’s perspective.

3. Develop an observation plan

Create a detailed observation plan outlining the procedures you’ll follow. This includes specifying the time and location of observations, identifying the subjects or settings to be observed, and determining the duration and frequency of observations.

Ensure your plan aligns with your research objectives and provides a structured approach to data collection.

4. Create an observation checklist

Design an observation checklist or coding scheme to record the behaviors or events you are interested in systematically. This tool helps ensure consistency and comprehensiveness in your observations.

For example, if you are observing classroom interactions, your checklist might include categories such as “student participation,” “teacher feedback,” and “group collaboration.”

5. Conduct the observations

Carry out your observations according to the plan you developed. Be sure to observe the subjects or settings without influencing or altering their natural behavior.

Take detailed notes or use recording tools to capture relevant data. Maintain objectivity and avoid introducing biases into your observations.

6. Analyze the data

After collecting your data, analyze it to identify patterns, trends, and relationships. Use statistical methods or qualitative analysis techniques, depending on the nature of your data.

For example, if you have observed classroom interactions, you might categorize and quantify different types of student behaviors and interactions.

7. Interpret the results

Analyze the findings and consider how they relate to your research topic. Consider how the observed data addresses your initial question and what insights can be drawn.

For instance, if your study reveals that students are more engaged during group activities, you might infer that collaborative learning techniques are effective in enhancing student participation.

8. Report your findings

Prepare a report presenting your findings in a clear and structured format. Include an introduction, methodology, results, discussion, and conclusions.

Use visual representations such as charts or graphs to illustrate key points. Ensure your report effectively communicates the significance of your findings and their implications.

9. Reflect and review

Reflect on the overall research process and review the effectiveness of your observational study.

Consider any limitations or challenges you encountered and how they may have impacted your findings. This reflection helps in identifying areas for improvement and refining future research methodologies.

Types of observational studies

Observational studies come in various forms, each offering unique insights into different aspects of behavior and phenomena.

Here are three common types:

1. Case-control observational study

In a case-control observational study, researchers compare individuals with a particular condition (cases) to those without the condition (controls). This type of study is often used to pinpoint factors that might be associated with the condition.

For instance, researchers might compare patients with a rare disease to a control group of healthy individuals to uncover potential risk factors or causes of the disease.

2. Cohort observational study

A cohort observational study involves following a group of individuals (a cohort) over time to observe how different exposures or factors affect their outcomes. This type of study is useful for examining the long-term effects of exposures on health or behavior.

Consider this observational study example; researchers might track a cohort of smokers and non-smokers over several decades to investigate the impact of smoking on the development of lung cancer.

3. Cross-sectional observational study

Cross-sectional observational studies provide a snapshot of a population at a single point in time. Researchers collect data on various variables to assess relationships and patterns within the population.

For example, a cross-sectional study could ask people about their eating patterns and overall health in order to find out how common obesity is and what factors are linked to it in a particular area.

Advantages of observational study

1. natural setting.

Observing subjects in their everyday environments provides a more accurate depiction of their real-life behaviors and interactions.

2. Real-world behavior

Captures genuine actions and conditions as they occur naturally, offering insights that are more relevant to everyday situations.

3. No experimental manipulation

It avoids altering variables, allowing researchers to study natural behaviors without interference.

4. Longitudinal data

Collects data over time, revealing trends and changes in behavior or conditions that develop over extended periods.

Disadvantages of observational study

1. lack of control.

Researchers cannot control or manipulate variables, limiting their ability to isolate specific factors affecting behavior.

2. Observer bias

Personal biases of the observer may influence how data is recorded and interpreted, potentially skewing results.

3. No causal inference

Observational studies can identify associations but cannot establish cause-and-effect relationships between variables.

4. Limited generalizability

The results might not apply to other groups or contexts if the study sample is too narrow or context-specific.

In conclusion, an observational study provides valuable insights into real-world behaviors and interactions by observing subjects in their natural settings.

While it captures genuine patterns and trends, it cannot establish causality and may be subject to bias. Despite these limitations, observational studies are crucial across various fields.

At Octet , we can help you design and execute effective observational research, ensuring accurate data collection and meaningful analysis to support your research objectives.

Frequently asked questions

1. what are the benefits of observational studies .

Observational studies offer several benefits, including the ability to study behaviors and interactions in natural settings without manipulating variables. They provide insights into real-world conditions, capture genuine actions, and can reveal long-term trends through longitudinal data. These studies are particularly useful when experimental manipulation is not feasible or ethical.

2. What is the objective of an observational study?

The primary objective of an observational study is to observe and describe behaviors, events, or conditions as they occur naturally. It aims to identify patterns, relationships, and trends without intervening or altering the environment. This approach helps researchers gain a deeper understanding of real-world phenomena.

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What Is Qualitative Observation? | Definition & Examples

What Is Qualitative Observation? | Definition & Examples

Published on March 18, 2023 by Tegan George . Revised on June 22, 2023.

Qualitative observation is a research method where the characteristics or qualities of a phenomenon are described without using any quantitative measurements or data. Rather, the observation is based on the observer’s subjective interpretation of what they see, hear, smell, taste, or feel.

Qualitative observations can be done using various methods, including direct observation, interviews , focus groups , or case studies . They can provide rich and detailed information about the behavior, attitudes, perceptions, and experiences of individuals or groups.

When to use qualitative observation, examples of qualitative observation, types of qualitative observations, advantages and disadvantages of qualitative observations, other interesting articles, frequently asked questions.

Qualitative observation is a type of observational study , often used in conjunction with other types of research through triangulation . It is often used in fields like social sciences, education, healthcare, marketing, and design. This type of study is especially well suited for gaining rich and detailed insights into complex and/or subjective phenomena.

A qualitative observation could be a good fit for your research if:

You are conducting exploratory research . If the goal of your research is to gain a better understanding of a phenomenon, object, or situation, qualitative observation is a good place to start.
When your research topic is complex, subjective, or cannot be examined numerically. Qualitative observation is often able to capture the complexity and subjectivity of human behavior, particularly for topics like emotions, attitudes, perceptions, or cultural practices. These may not be quantifiable or measurable through other methods.
You are relying on triangulation within your research approach. Qualitative observation is a solid addition to triangulation approaches, where multiple sources of data are used to validate and verify research findings.

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Qualitative observation is commonly used in marketing to study consumer behavior, preferences, and attitudes towards products or services.

During the focus group, you focus particularly on qualitative observations, taking note of the participants’ facial expressions, body language, word choice, and tone of voice.

Qualitative observation is often also used in design fields, to better understand user needs, preferences, and behaviors. This can aid in the development of products and services that better meet user needs.

You are particularly focused on any usability issues that could impact customer satisfaction. You run a series of testing sessions, focusing on reactions like facial expressions, body language, and verbal feedback.

There are several types of qualitative observation. Here are some of the most common types to help you choose the best one for your work.

Type	Definition	Example
	The researcher observes how the participants respond to their environment in “real-life” settings but does not influence their behavior in any way	Observing monkeys in a zoo enclosure
	Also occurs in “real-life” settings. Here, the researcher immerses themself in the participant group over a period of time	Spending a few months in a hospital with patients suffering from a particular illness
Covert observation	Hinges on the fact that the participants do not know they are being observed	Observing interactions in public spaces, like bus rides or parks
	Investigates a person or group of people over time, with the idea that close investigation can later be to other people or groups	Observing a child or group of children over the course of their time in elementary school

Qualitative observations are a great choice of research method for some projects, but they definitely have their share of disadvantages to consider.

Advantages of qualitative observations

Qualitative observations allow you to generate rich and nuanced qualitative data —aiding you in understanding a phenomenon or object and providing insights into the more complex and subjective aspects of human experience.
Qualitative observation is a flexible research method that can be adjusted based on research goals and timeline. It also has the potential to be quite non-intrusive, allowing observation of participants in their natural settings without disrupting or influencing their behavior.
Qualitative observation is often used in combination with other research methods, such as interviews or surveys , to provide a more complete picture of the phenomenon being studied. This triangulation can help improve the reliability and validity of the research findings.

Disadvantages of qualitative observations

Like many observational studies, qualitative observations are at high risk for many research biases , particularly on the side of the researcher in the case of observer bias . These biases can also bleed over to the participant size, in the case of the Hawthorne effect or social desirability bias .
Qualitative observations are typically based on a small sample size , which makes them very unlikely to be representative of the larger population. This greatly limits the generalizability of the findings if used as a standalone method, and the data collection process can be long and onerous.
Like other human subject research, qualitative observation has its share of ethical considerations to keep in mind and protect, particularly informed consent, privacy, and confidentiality.

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Student’s t -distribution
Normal distribution
Null and Alternative Hypotheses
Chi square tests
Confidence interval
Quartiles & Quantiles
Cluster sampling
Stratified sampling
Data cleansing
Reproducibility vs Replicability
Peer review
Prospective cohort study

Research bias

Implicit bias
Cognitive bias
Placebo effect
Hawthorne effect
Hindsight bias
Affect heuristic
Social desirability bias

Data analysis in qualitative observation often involves searching for any recurring patterns, themes, and categories in your data. This process may involve coding the data, developing conceptual frameworks or models, and conducting thematic analysis . This can help you generate strong hypotheses or theories based on your data.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

An observational study is a great choice for you if your research question is based purely on observations. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment , an observational study may be a good choice. In an observational study, there is no interference or manipulation of the research subjects, as well as no control or treatment groups .

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10 Observational Research Examples

Examples of Observational Research

2. Linguistic Development of Children

3. Consumer Product Design

4. Satellite Images of Walmart

5. Spying on Farms

6. Decision-making Group Dynamics

7. Case Studies

8. Infant Attachment

9. Ethnographic Research

10. Time and Motion Studies

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What is Observational Research in Marketing?

Observational Research Methods

Pros and Cons of Observational Research

Advantages of Observational Research:

Disadvantages of Observational Research:

Examples of Observational Research

In-store observation

Contextual inquiry

Eye tracking, heatmapping, and scrollmapping

Usability testing

Trace analyses

Social intelligence

Q&A sites

Keyword research

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The Business Owner's Guide to Conducting Observational Research

What is observational research?

What are the advantages of observational research?

What are the drawbacks of observational research?

Common use cases for observational research

Types of observational research

What are the steps to conduct observational research?

Step 2: Select your observation type

Step 3: Determine how many people to observe

Step 4: Create a run-of-show

Step 5: Train your observers and recruit participants

Step 6: Conduct your observational research

Step 7: Analyze the results

Step 8: Thank and follow up with participants

What biases do you need to control for observational research?

What tools should you use for online observational research?

Tips to get the most value from observational research

Common mistakes with observational research

Observational research examples

3. Hewlett-Packard

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Key Characteristics of Experimental Studies:

Types of Experimental Study

Example of an Experimental Study:

What is an Observational Study?

Key Characteristics of Observational Studies:

Types of Observational Studies:

Example of an Observational Study:

Difference Between Experimental vs Observational Studies

Choosing Between Experimental and Observational Studies

Use Experimental Studies When:

Use Observational Studies When:

Strengths and Limitations

Observational Studies

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Environmental Science

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