case study in consumer behavior

• SUGGESTED TOPICS
• The Magazine
• Newsletters
• Managing Yourself
• Managing Teams
• Work-life Balance
• The Big Idea
• Data & Visuals
• Reading Lists
• Case Selections
• HBR Learning
• Topic Feeds
• Account Settings
• Email Preferences

Consumer behavior

• Sales and marketing
• Business management
• Market research

What Psychological Targeting Can Do

• Sandra Matz
• From the March–April 2023 Issue

Research: Why We're Incentivized by Discounts and Surcharges

• Alicea Lieberman
• Kristen Duke
• February 13, 2020

Unblocking Women's Paths to the Boardroom

• Monique Valcour
• October 31, 2012

“Actually,” She Said, “He Works for Me.”

• Karen Firestone
• April 09, 2013

Understanding China’s Young Consumers

• Zak Dychtwald
• June 11, 2021

How Companies Can Meet the Needs of a Changing Workforce

• Avivah Wittenberg-Cox
• December 18, 2020

Global Team Leaders Must Deliberately Create "Moments"

• Tsedal Neeley
• March 22, 2012

Advice on Launching a Tech Startup When You’re Not a White Man

• Cheryl Contee
• October 08, 2019

B2B Sales Culture Must Change to Make the Most of Digital Tools

• Prabhakant Sinha
• Arun Shastri
• Sally E. Lorimer
• March 15, 2023

Research: How Our Class Background Affects the Way We Collaborate

• Andrea G. Dittmann
• Nicole M. Stephens
• Sarah S. M. Townsend
• July 20, 2021

How 6 Countries Compare on Executive Gender Balance

• July 18, 2014

Looking Ahead: Implications of the Present

• Peter F. Drucker
• Esther Dyson
• Charles Handy
• Peter M. Senge
• From the September–October 1997 Issue

How Unnecessary Paper Packaging Creates the Illusion of Sustainability

• Aradhna Krishna
• Tatiana Sokolova
• April 21, 2023

Research: Bringing Up Past Injustices Make Majority Groups Defensive

• Ivona Hideg
• Anne Wilson
• February 05, 2020

Case of the Profitless PC (HBR Case Study and Commentary)

• Andy Blackburn
• Matt Halprin
• Ruth Veloria
• Donna Dubinsky
• Larry Keeley
• George Quesnelle
• Philip Pifer
• Geoff Moore
• From the November-December 1998 Issue

Hiring Algorithms Are Not Neutral

• Gideon Mann
• Cathy O'Neil
• December 09, 2016

Women: Let's Stop Allowing Race and Age to Divide Us

• Ancella Livers and Trudy Bourgeoi
• August 15, 2013

Price-Sensitive Customers Will Tolerate Uncertainty

• Rafi Mohammed
• March 26, 2015

Just in Time for the Holidays (HBR Case Study and Commentary)

• Eric McNulty
• M. Eric Johnson
• Horst Brandstatter
• Warren H. Hausman
• From the December 2005 Issue

Social Media’s Next Important Job

• Roger O. Crockett
• September 17, 2010

The London 2012 Olympic Games

• John T. Gourville
• Marco Bertini
• September 02, 2009

Branding and Bollywood: The Behavioral Route to Branding Films

• S. Ramesh Kumar
• Unnikrishnan Dinesh Kumar
• January 01, 2017

Super Shampoo Products and the Indian Mass Market

• Nitya Guruvayurappan
• November 30, 2010

New York Life and Immediate Annuities

• Julio J. Rotemberg
• November 02, 2009

J.C. Penney's "Fair and Square" Pricing Strategy

• September 21, 2012

RogersCasey Alternative Investments: Innovative Response to the Distribution Challenge

• Josh Lerner
• September 27, 1995

Rock Pharmacy: Rocked?

• Harish Kumar
• February 13, 2022

Data Science at Target

• Srikant M. Datar
• Caitlin N. Bowler
• October 04, 2017

Lemonade: Disrupting Insurance with Instant Everything, Killer Prices, and a Big Heart

• Danielle Golan
• August 02, 2019

Struggling to Make the Best Buy

• Seung Hwan (Mark) Lee
• April 26, 2010

Consumer Behavior Exercise (A)

• John Deighton
• Susan Fournier
• August 25, 1995

Glossier: Co-Creating a Cult Brand with a Digital Community

• January 08, 2019
• David E. Bell
• Natalie Kindred
• December 06, 2020

Chantal Cookware Corp.

• H. Kent Bowen
• Paul W. Marshall
• October 09, 1998

Helping Chinese Consumers Making the Informed Choices: the Challenge of Trust

• February 01, 2014

Walt Disney Internet Group Japan's Dimo Project

• Philip Sugai
• November 16, 2004

Great Dakota Bank: Online Banking

• Frances X. Frei
• Youngme Moon
• Hanna Rodriguez-Farrar
• August 07, 2002

Apex Ski Boots

• Kate Barasz
• August 26, 2019

Aqualisa Quartz: Simply a Better Shower

• Kerry Herman
• January 16, 2002

Freemark Abbey Winery

• William S. Krasker
• August 01, 1980

Popular Topics

Partner center.

Understanding the ever-evolving, always-surprising consumer

For many consumers around the world, a return to normalcy feels so close, yet so far away, in light of the alarming spread of COVID-19 variants. Although it’s unclear what the next 12 to 24 months will bring, what’s almost certain is that consumers won’t simply revert to doing exactly what they did in 2019. In this episode of the McKinsey on Consumer and Retail podcast, three consumer-behavior experts share their insights into how consumers’ spending patterns and purchasing behaviors are changing, and what companies should do given those changes. An edited transcript of the conversation with executive editor Monica Toriello follows. Subscribe to the podcast .

Monica Toriello: Over the past several weeks, people in some parts of the world have resumed their prepandemic habits. Maybe you’ve recently seen a movie at a theater, or flown on an airplane, or even just stopped for a cup of coffee on your way to the office for the first time in over a year. But a return to “normal” won’t look the same for everyone. Today, we’ll hear from three people who intensively study consumer behavior. They’ll share fascinating insights into how consumers are changing and what companies should do about it.

Kari Alldredge is a McKinsey partner based in Minneapolis. Kari has been advising consumer-goods companies for more than 20 years on a variety of topics, and she leads McKinsey’s work in consumer-goods growth transformation. She is an author of several articles, including a recent one on COVID-19’s impact on demand and costs in the consumer-packaged-goods [CPG] industry .

Anne Grimmelt is a senior knowledge expert in McKinsey’s Consumer Packaged Goods Practice. She is based in Stamford, Connecticut. Anne has been one of the driving forces behind McKinsey’s consumer-sentiment survey , which was launched in 2008 and during the pandemic has expanded to 45 countries. It provides a rich fact base for how consumers are feeling about their finances and how their buying behavior is changing.

And our third guest is Anjali Lai, a senior analyst at Forrester. Anjali, who is based in New York, helps chief marketing officers [CMOs] and other business leaders to understand the shifts in consumer behavior and consumer decision making and then to figure out what these changes mean for the future of brands and industries.

[To comply with Forrester’s Citation Policy, this transcript excludes Anjali Lai’s comments. Listen to the full episode on McKinsey.com or on Apple, Google, and other podcast platforms.]

A ‘reversal of fortune’ for big brands

Monica Toriello: Kari, Anne, Anjali, it’s great to have you here today. All three of you have been keeping your fingers on the pulse of consumers, both before and throughout the pandemic. Have there been any surprises? Are consumers doing things that you didn’t expect? Or is there anything that seemed to be going one way in, say, March or April 2020 but is going in a different direction today?

Kari Alldredge: In 2019 or early 2020, the topic on the minds of large branded consumer-packaged-goods manufacturers was portfolio shaping: how to reimagine their portfolios, how to move away from center-of-store food products and big brands and instead engage with consumers in very different, more targeted, niche-oriented ways. The degree to which the pandemic pushed people back toward big brands in the center of the store, and toward cooking at home, has been a complete turnaround, a reversal of fortune, for large CPG companies.

Some of those changes could have been anticipated, but others are quite shocking: the notion that bread baking would become a phenomenon among millennials, or that pet ownership would skyrocket to the extent that it has, and that those same millennials would be willing to spend more than they spend on their daily Starbucks to feed their new pets.

So, many of those companies that were desperately searching for growth 18 months ago now have the opposite problem: their supply chains can’t keep up . The big question for all of them is which of those consumer behaviors are truly going to persist  and be “sticky” coming out of this pandemic? Certainly, the dog that you adopted is likely to stay at your home. But when you go back to ordering your daily Starbucks and spending $7 a day on a coffee, are you going to spend the same amount to feed your pet? Those are the questions that are on many company leaders’ minds.

Anne Grimmelt: As Kari said, we saw a complete shift. Prepandemic, the growth was in smaller, niche brands, but early in the pandemic, it was large CPG players that really gained scale because their products were available on the shelf. They were also brands that were trusted by consumers, so consumers felt good buying them. If you look at point-of-sale data from IRI or Nielsen, you see that large companies—those with more than $2.5 billion in retail sales in the US market—picked up most of the share growth early in the pandemic, whereas smaller and midsize companies, as well as private label, were really not picking up growth.

In the second half of 2020 and in early 2021, small and midsize companies are regaining their sales growth. And we expect that private label is going to be powerful again , because if you dive into the why—why did consumers pick a new brand, and why did they pick the brands they chose?—it was about availability, it was about purpose, but it was also about value . It was about price points. Going forward, value is going to be even more important, and private label will gain strength in the future.

Trust as a strategic imperative

Monica Toriello: All three of you to some extent have written about customer loyalty: how to win it and how to retain it, particularly in an environment where people are willing to try new brands. Anne and Kari, you found that 39 percent of consumers tried new brands during the pandemic. And Anjali, in your research, you found that small brands are particularly good at earning consumers’ trust and consequently their loyalty. In a recent blog post, you wrote, “Now is the time for companies to embrace trust as a strategic imperative.” What does that mean? How should companies do that?

Even relatively mundane CPG companies are thinking about the end-to-end consumer journey, including consumer experience pre- and postpurchase. Kari Alldredge

Kari Alldredge: I’m seeing two interesting things in response to the trends you just talked about, Anjali. One is the degree to which even relatively mundane CPG companies are thinking about the end-to-end consumer journey, including consumer experience pre- and postpurchase, as they try to understand how to serve their existing consumers but also look for new ways to better meet consumer needs. The notion that there is a pre- and postpurchase experience related to a can of soda or a can of soup is a relatively novel idea, right? But, increasingly, the most forward-thinking companies are doing research across that entire journey to be able to understand the needs of consumers as they’re considering the range of options that are available to them—all the way through to satisfaction with usage and even disposal of the packaging of products.

Another interesting thing I’m seeing is a recognition that marketing is a dialogue, and a recognition of the degree to which consumers now “own” or shape the narratives of many brands. This, too, was happening before the pandemic but was vastly accelerated during the pandemic. The notion that a marketer positions the brand and delivers a message and a promise to consumers is really becoming quite an antiquated one, I think, as consumers themselves—through reviews, ratings , blogs, videos, and social-media posts—shape the identity of many of these brands. Recommendations from friends and family become part of the brand’s identity and are critical to shaping both loyalty and consumer trust.

We found in our research that about 33 percent of millennial and Gen Z consumers say they choose to buy a brand from a company that has their values, versus about 12 percent of baby boomers. Anne Grimmelt

Anne Grimmelt: Our research corroborates that. We found in our research that about 33 percent of millennial and Gen Z consumers  say they choose to buy a brand from a company that has their values, versus about 12 percent of baby boomers. But every demographic group is leaning toward that.

Another finding from our research is the reasons why consumers change to a new brand. It is definitely the younger generation that more often indicates that it’s because of purpose. It’s because of what the company stands for, how it treats its employees, et cetera.

Purpose: More than just a buzzword

Monica Toriello: We’ve been hearing a lot about purpose and values, but I also hear some skepticism in certain pockets of the corporate world as to whether an emphasis on corporate purpose  actually pays off. Because there is an attitude–behavior gap, right? What’s your response to a CEO who says, “Consumers like to say they care about purpose and values, but when they’re at the point of deciding to buy something, they truly only care about convenience or price or quality. Purpose is just a buzzword.”

Kari Alldredge: It’s necessary but not sufficient. I think there’s an increasing recognition that alignment with a consumer’s values may put you in the consideration set but won’t drive you over the line to purchase. You still have to have product superiority, whether that’s taste superiority, functional superiority, or a price-to-value equation that works for that particular consumer.

We talk a lot about the pandemic, which definitely shone a light on health in general, but there are other crises—like social justice  and climate change —that have come to light over the past year and a half and that have really shaken the corporate community. These crises have helped companies understand that some of these factors are fundamental in how consumers perceive themselves and the world around them, to the point where we now actually see some change happening.

One of the things that I was struck by was the speed and seriousness with which many of the household-cleaning companies responded to the pandemic and the heroic efforts to convert production capacity to manufacture things like wipes and sanitizer. Yes, some of that was for financial gain, but I think there really was an almost wartime mentality that I saw companies get new energy from.

I think about center-of-store food manufacturers who, prepandemic, maybe viewed themselves as being a bit sleepy and not exciting in terms of attracting the best talent. Now when you hear them talk about what they do, there’s real pride in the fact that they fed America, or they kept America safe. It really changed the way they think about the importance of what they do.

Subscribe to the McKinsey on Consumer and Retail podcast

Sources of insight.

Monica Toriello: All three of you are experts in consumer behavior. But consumers are changing fast and they’re changing constantly. Anjali, in another recent blog post, you wrote, “Rather than expect consumers to settle into a defined postpandemic normal, CMOs should prepare for a constant evolution of consumer needs and expectations over the next 12 to 24 months.” So beyond reading the latest consumer research and analysis, what are the best ways for CMOs and CEOs to understand where consumers are and where they’re headed?

Kari Alldredge: One of the best sources of insights is their online channel partners and their own D2C [direct to consumer] sites . Companies should mine online data to get a quick pulse on the way consumers are thinking or feeling. They should look at ratings and reviews using advanced analytics to understand and see trends and what’s selling on sites like Kroger.com, Walmart.com, or Amazon.com. They could even develop products that they can quickly test in an online environment and then change and adjust, as opposed to thinking about mass development of a product that gets pushed out to thousands and thousands of brick-and-mortar retail stores.

Consumers don’t always know what they want, and they can’t predict how their behavior will change. So traditional consumer research—which asks consumers how likely they are to purchase something—is becoming less relevant or reliable than actual data in market. That’s why data from e-commerce sites can be so valuable.

Anne Grimmelt: Another very powerful way to understand consumers  is by looking at what your peer companies do. You can go to industry conferences like the CAGNY [Consumer Analyst Group of New York] conference and hear a company like L’Oréal talk about how they use their D2C and their online-sales platform to see what type of color lipstick people try—not buy , but try —on their online platform. That information is critical for them to know where to innovate. What are the colors that people want and what are the products that people like to try out on the digital platform?

Similarly, I think it’s very important to keep an open mind beyond your own borders, to realize what’s happening elsewhere in the world. Going back to the topic of purpose, for instance, it is very much alive in the US but it’s also very much alive in Europe. Learning about the power of what consumers demand and how purpose is driving consumer decisions about CPG companies—and what companies in Europe are doing to meet consumer demand—can be valuable, wherever you are in the world.

Kari Alldredge: I think we also shouldn’t underestimate the resilience of consumers and the gravitational pull of life as we knew it before the pandemic. One thing that surprised me even in the past several weeks is the degree to which behaviors have bounced back. If there’s anything I’ve learned over the past 18 months it’s that I don’t have a crystal ball, or if I did, it is certainly broken—because there is no part of this last 18 months that I ever could have in a million years predicted.

At the beginning of the pandemic, one company I work with asked every board member, “When you look back, what’s the one thing that will be blazingly obvious that we either should always have done or never have been doing?” And one of the things that came up was shaking hands: “We’re never going to shake hands again.” But I attended a graduation ceremony in the beginning of June—so, early into the recovery—and what was striking to me is that the dean of that school shook the hand of, and physically embraced, every single one of the thousand students who crossed that stage. And this was at an institution that had been, like most educational institutions, incredibly thoughtful and conservative about their public-health response. Literally days after restrictions were lifted, the urge to connect was so strong that it looked as if the pandemic had never happened.

People are resilient. Hundreds of years of behavior certainly have been meaningfully changed by the past 18 months, but I think a lot of the old behaviors will bounce back pretty quickly.

Monica Toriello: So if you could gather all the CEOs and CMOs of consumer companies in one room and leave them with one message, what would it be? What is the one thing they need to do to position themselves for success in 2021 and 2022?

Anne Grimmelt: My one-liner would be, “Be open to change and be agile .”

Kari Alldredge: I would say, “Listen; don’t tell.”

Kari Alldredge is a partner in McKinsey’s Minneapolis office, and  Anne Grimmelt is a senior knowledge expert in the Stamford office.  Monica Toriello is an executive editor in the New York office.

Explore a career with us

Related articles.

McKinsey on Consumer and Retail Podcast: Insights from experts on business and management

Global surveys of consumer sentiment during the coronavirus crisis

COVID-19’s impact on demand and costs in the CPG industry

• Featured Manufacturing Retail Health and wellness E-commerce Sustainability SMB Innovation Artificial Intelligence
• Assortment and Merchandising Consumer and shopper insights Market performance measurement Marketing, media and personalized offers Operations and supply chain BASES product offer management Revenue growth management Route-to-market
• Small and medium-sized businesses (SMB) SMB solutions for North America SMB solutions for International
• Featured industries Beauty and Personal Care Beverage Alcohol Non-Alcoholic Beverage Financial Services Government Grocery Health and wellness Media+Adtech Packaging Perishables Pet Retail
• Company News
• Diversity, Equity, and Inclusion
• Search Careers
• Early Careers

How can we help you?

Consumer Behavior Research

Exploring the Depths of Consumer Insights for Strategic Business Growth

In an era where understanding consumer behavior is more than a competitive edge, it’s a survival imperative, NielsenIQ (NIQ) and GfK emerge as pivotal allies. This expertise is essential for businesses in B2C commerce, retail, and beyond, aiming to navigate the complex consumer landscape for informed, strategic decision-making.

Definition and Importance of Consumer Behavior Research

Consumer behavior research is the study of how individuals make decisions to spend their resources on consumption-related items. It involves understanding the what, why, when, and how of consumer purchases. This field is crucial for businesses as it sheds light on consumer preferences, buying patterns, and decision-making processes. By understanding these aspects, companies can tailor their products and marketing strategies effectively, ensuring alignment with consumer needs and market trends, ultimately leading to increased customer satisfaction and loyalty.

Overview of the Impact of Consumer Behavior Research on Marketing Strategies

The insights from consumer behavior research are instrumental in shaping targeted marketing strategies. By understanding consumer motivations and behaviors, businesses can create more relevant and engaging marketing messages, leading to improved customer engagement and retention. This research helps in segmenting the market, identifying potential customers, and understanding the factors that drive consumer decisions. It also aids in predicting future trends, enabling companies to stay ahead of the curve. Effective use of consumer behavior research can lead to the development of products and services that meet the evolving needs of consumers, thereby enhancing brand loyalty and market share.

Consumer and shopper insights

Understand consumer and shopper behavior, demographics, and loyalty with modern, representative consumer panels and customer survey capabilities.

Understanding Consumer Behavior

These diverse influences combine to form unique consumer profiles, which businesses must understand to effectively target their marketing efforts..

Factors Influencing Consumer Behavior

Consumer behavior is influenced by a complex interplay of psychological, social, cultural, and personal factors. Psychological factors include perceptions, attitudes, and motivation, which guide consumers’ emotional and cognitive responses. Social factors encompass family, friends, and societal norms that shape buying habits through peer influence and social trends. Cultural factors involve the broader societal beliefs, values, and customs that dictate consumer behavior in a particular region. Personal factors such as age, occupation, lifestyle, and economic status also significantly impact consumer choices. These diverse influences combine to form unique consumer profiles, which businesses must understand to effectively target their marketing efforts.

The Role of Consumer Behavior in Decision Making

Consumer behavior plays a critical role in the decision-making process. It involves understanding how consumers decide upon their needs and wants, choose among products and brands, and determine their purchase methods. This knowledge is vital for businesses to design and position their offerings in a way that resonates with the target audience. Understanding consumer behavior helps in predicting how consumers will respond to marketing messages and product features, enabling businesses to tailor their strategies to meet consumer needs effectively. It also assists in identifying opportunities for new product development and market expansion.

Consumer Behavior Theories and Models

Consumer behavior theories and models provide frameworks for understanding and predicting consumer actions. The Stimulus-Response Model, for instance, illustrates how marketing stimuli and environmental factors influence consumer responses. Maslow’s Hierarchy of Needs explains consumer motivation in terms of fulfilling basic to complex needs. The Theory of Reasoned Action and the Theory of Planned Behavior focus on the relationship between attitudes, intentions, and behaviors. The Consumer Decision Model outlines the cognitive process involving need recognition, information search, evaluation of alternatives, purchase decision, and post-purchase behavior. These models help businesses in developing strategies that align with consumer psychology and behavioral patterns. They also assist in segmenting the market and targeting consumers with personalized marketing approaches, enhancing the effectiveness of marketing campaigns and product offerings.

Research Methods in Consumer Behavior Research

Customer analytics is vital for businesses across various sectors, including FMCG, sales, and e-commerce. It enables companies to create personalized experiences, improve customer engagement, and boost retention, ultimately leading to increased revenue. By understanding consumer behavior through data analysis, businesses can make informed decisions that resonate with their target audience.

Quantitative Research Methods

Quantitative research methods in consumer behavior research involve structured techniques like surveys and questionnaires to collect numerical data. These methods are useful for gauging consumer attitudes, preferences, and behaviors across larger populations. Statistical analysis of this data helps in identifying trends, testing hypotheses, and making generalizations about consumer behavior. Quantitative research is valuable for businesses as it provides measurable and comparable insights that can guide strategic decision-making. It helps in understanding the magnitude of consumer responses to various marketing stimuli and in assessing the potential market size for new products or services.

Qualitative Research Methods

Qualitative research methods in consumer behavior focus on understanding the deeper motivations, thoughts, and feelings of consumers. Techniques like in-depth interviews, focus groups, and observational studies provide rich, detailed insights that are not typically captured through quantitative methods. This approach is crucial for exploring the underlying reasons behind consumer choices, preferences, and attitudes. Qualitative research helps businesses in gaining a deeper understanding of consumer experiences, emotions, and perceptions, which can be invaluable in developing more effective marketing strategies, product designs, and customer service approaches. It allows companies to explore new ideas and concepts with consumers, gaining insights that can lead to innovation and differentiation in the market.

Experimental Research in Consumer Behavior

Experimental research in consumer behavior involves manipulating one or more variables to observe the effect on another variable, typically consumer behavior or attitudes. This method is used to establish cause-and-effect relationships, providing insights into how changes in product features, pricing, or marketing strategies might influence consumer behavior. Controlled experiments, often conducted in laboratory settings or as field experiments, allow researchers to isolate the effects of specific variables. This type of research is particularly valuable for testing new products, pricing strategies, and marketing messages before full-scale implementation. It helps businesses in making informed decisions based on empirical evidence, reducing the risks associated with new initiatives.

Factors Affecting Consumer Behavior

Psychological factors.

Psychological factors play a significant role in shaping consumer behavior. These include individual motivations, perceptions, attitudes, and beliefs. Motivation drives consumers to fulfill their needs and desires, influencing their buying decisions. Perception, how consumers interpret information, can significantly impact their choices, as it shapes their understanding of products and brands. Attitudes and beliefs, formed through experiences and social influences, guide consumer preferences and loyalty. Understanding these psychological factors is crucial for businesses as they influence how consumers view and interact with products and services. By aligning marketing strategies with consumer psychology, businesses can more effectively influence purchasing decisions and build stronger customer relationships.

Social Factors

Social factors significantly influence consumer behavior, encompassing the impact of society, family, and peer groups. Family members and friends can influence buying decisions through recommendations or shared experiences. Social groups, including social networks and communities, also play a role in shaping consumer preferences and behaviors. The influence of social media has become particularly significant, as it not only connects consumers but also serves as a platform for sharing opinions and experiences about products and services. Understanding these social dynamics is important for businesses as they can leverage social influences through targeted marketing strategies, influencer partnerships, and social media campaigns. Recognizing the power of social factors can help businesses in building brand awareness and loyalty among consumer groups.

Cultural Factors

Cultural factors are deeply ingrained elements that influence consumer behavior, including values, beliefs, customs, and traditions. These factors vary across different regions and societies, affecting how consumers perceive and interact with products and services. Cultural influences can determine consumer preferences, buying habits, and brand perceptions. For instance, color symbolism, dietary preferences, and language can all vary significantly between cultures, impacting marketing strategies and product development. Businesses must understand and respect these cultural nuances to effectively cater to diverse consumer markets. Adapting products and marketing messages to align with cultural values and norms can significantly enhance a brand’s appeal and acceptance in different markets.

Personal Factors

Personal factors, including age, gender, occupation, lifestyle, and economic status, also significantly influence consumer behavior. These factors determine individual needs, preferences, and purchasing power. For example, younger consumers may prioritize trendy and innovative products, while older consumers might value functionality and durability. Lifestyle choices, such as health consciousness or environmental awareness, can also drive consumer preferences and choices. Economic factors, such as income and economic conditions, influence consumers’ ability to purchase and their sensitivity to price changes. Understanding these personal factors is crucial for businesses to segment their market effectively and tailor their products and marketing strategies to meet the specific needs of different consumer groups.

Consumer Purchase Decision Making

Stages of the consumer purchase decision-making process.

The consumer purchase decision-making process typically involves several key stages: problem recognition, information search, evaluation of alternatives, purchase decision, and post-purchase behavior.

In the problem recognition stage, consumers identify a need or desire.

During the information search, they seek out information about products or services that can fulfill their need. In the evaluation stage, consumers compare different options based on attributes such as price, quality, and brand reputation.

The purchase decision involves choosing a product and making the purchase. Finally, in the post-purchase stage, consumers evaluate their satisfaction with the purchase, which can influence future buying decisions and brand loyalty.

Understanding these stages is essential for businesses to effectively influence consumers at each step, from raising awareness to ensuring post-purchase satisfaction.

Influences on Consumer Purchase Decisions

Consumer purchase decisions are influenced by a multitude of factors, including product attributes, brand reputation, marketing messages, social influences, and personal preferences. Product features such as quality, price, and usability are key determinants of consumer choices. Brand reputation, built over time through consistent quality and marketing efforts, also significantly impacts purchase decisions. Marketing messages and advertising play a crucial role in shaping consumer perceptions and driving demand. Social influences, including recommendations from family and friends, as well as online reviews and influencer endorsements, can sway consumer decisions. Personal factors such as individual needs, preferences, and financial constraints also play a critical role. Businesses must consider these diverse influences when developing products and crafting marketing strategies to effectively appeal to their target audience.

Impulse Buying Behavior

Impulse buying behavior refers to unplanned purchases made by consumers, often driven by emotional factors rather than rational decision-making. This type of behavior is typically triggered by external stimuli such as attractive product displays, promotional offers, or persuasive sales tactics. Emotional responses, such as excitement or the desire for instant gratification, also play a significant role in impulse buying. Retailers often leverage this behavior by strategically placing impulse items near checkout areas or using limited-time offers to create a sense of urgency. Understanding the triggers of impulse buying can help businesses in designing marketing strategies and store layouts that encourage such purchases, potentially increasing sales and customer engagement.

Online Shopping and Consumer Behavior

Impact of online shopping on consumer behavior.

The rise of online shopping has significantly impacted consumer behavior, offering convenience, a wider selection of products, and often competitive pricing. Online shopping has changed the way consumers research products, compare prices, and make purchasing decisions. The ease of access to a vast array of products and the ability to shop at any time have increased the frequency and diversity of purchases. Online reviews and ratings have also become important factors in the decision-making process, as consumers increasingly rely on the opinions of others. Additionally, the personalized shopping experiences offered by many online retailers, through targeted recommendations and tailored marketing messages, have further influenced consumer buying habits. Understanding these shifts in consumer behavior is crucial for businesses to adapt their strategies for the digital marketplace, ensuring they meet the evolving needs and expectations of online shoppers.

Factors Influencing Online Buying Behavior

Several factors influence online buying behavior, including website usability, product variety, pricing, customer reviews, and the overall shopping experience. A user-friendly website with easy navigation and a seamless checkout process is crucial for attracting and retaining online shoppers. A diverse product range and competitive pricing are also key factors in attracting consumers. Customer reviews and ratings significantly impact purchase decisions, as they provide social proof and reduce perceived risk. The overall shopping experience, including customer service, delivery options, and return policies, also plays a vital role in influencing online buying behavior. Security and privacy concerns are additional considerations, as consumers are increasingly aware of data protection and online fraud. Businesses must address these factors to create a compelling online shopping experience that meets consumer expectations and drives online sales.

Comparison of Online and Offline Consumer Behavior

Online and offline consumer behaviors exhibit distinct differences, influenced by the unique aspects of each shopping environment. Online shopping offers convenience, a broader selection, and often more competitive pricing, leading to different purchasing patterns compared to offline shopping. Consumers tend to spend more time researching and comparing products online, while offline shopping is often driven by immediate needs and sensory experiences. The tactile experience and instant gratification of offline shopping are not replicable online, but the online environment offers personalized recommendations and a wealth of product information. Offline shopping also provides opportunities for personal interaction and immediate problem resolution, which can enhance customer satisfaction. Understanding these differences is crucial for businesses to tailor their strategies for each channel, ensuring a cohesive and complementary shopping experience that meets the needs and preferences of consumers in both online and offline environments.

Consumer Satisfaction and Loyalty

Importance of customer satisfaction in consumer behavior research.

Customer satisfaction is a critical component of consumer behavior research, as it directly impacts repeat purchases and brand loyalty. Satisfied customers are more likely to become repeat buyers, recommend the brand to others, and provide positive reviews. Customer satisfaction is influenced by various factors, including product quality, customer service, and overall shopping experience. Understanding and measuring customer satisfaction helps businesses identify areas for improvement, enhance customer experiences, and build long-term relationships with consumers. High levels of customer satisfaction lead to increased customer loyalty, which is essential for business growth and sustainability.

Factors Influencing Customer Satisfaction

Customer satisfaction is influenced by a range of factors, including product quality, price, service quality, brand image, and customer expectations. Product quality is a primary determinant of satisfaction, as consumers expect products to perform as advertised. Price also plays a role, as consumers evaluate the value they receive relative to the cost. Service quality, encompassing customer service interactions and the overall shopping experience, significantly impacts satisfaction levels. A positive, helpful, and efficient service experience can enhance satisfaction, while negative experiences can lead to dissatisfaction. Brand image, shaped by marketing communications and past experiences, influences consumer expectations and perceptions. Meeting or exceeding these expectations is key to achieving high levels of customer satisfaction. Additionally, personal factors such as individual needs, preferences, and past experiences also influence satisfaction. Businesses must consider these diverse factors to effectively meet consumer needs and enhance satisfaction levels.

Relationship Between Customer Satisfaction and Loyalty

The relationship between customer satisfaction and loyalty is strong and direct. Satisfied customers are more likely to develop a sense of loyalty to a brand, leading to repeat purchases and positive word-of-mouth recommendations. Loyalty is not just about repeat buying; it also involves an emotional connection and a preference for the brand over competitors. Satisfied customers are also more likely to be forgiving of minor issues and are less sensitive to price changes. Conversely, dissatisfied customers are more likely to switch to competitors and share negative experiences with others. Building customer loyalty requires consistently meeting or exceeding customer expectations, providing high-quality products and services, and maintaining positive customer relationships. Loyal customers are valuable assets to businesses, as they tend to have a higher lifetime value, lower acquisition costs, and can become brand advocates, promoting the brand through their networks.

Consumer Research and Marketing Strategies

Utilizing consumer research to develop effective marketing programs.

Consumer research is a vital tool for developing effective marketing programs. By understanding consumer needs, preferences, and behaviors, businesses can create targeted marketing strategies that resonate with their audience. Consumer research helps in identifying market segments, understanding consumer pain points, and uncovering opportunities for product development or enhancement. It also provides insights into the most effective channels and messages for reaching the target audience. Utilizing consumer research in marketing program development ensures that strategies are data-driven and customer-centric, increasing the likelihood of success. It enables businesses to tailor their marketing efforts to the specific needs and preferences of different consumer segments, improving engagement and response rates. Additionally, ongoing consumer research allows businesses to adapt their marketing strategies in response to changing consumer trends and market conditions, ensuring continued relevance and effectiveness.

Targeting Specific Consumer Segments Based on Research Findings

Targeting specific consumer segments based on research findings is a key strategy for effective marketing. Consumer research provides detailed insights into different consumer groups, including their demographics, psychographics, behaviors, and preferences. By analyzing this data, businesses can identify distinct segments within their target market, each with unique needs and characteristics. Targeting these segments with tailored marketing messages and product offerings increases the relevance and appeal of the brand to each group. For example, a segment characterized by health-conscious consumers would respond more positively to marketing messages emphasizing the health benefits of a product. Segment-specific targeting allows businesses to allocate marketing resources more efficiently, focusing on the most promising segments with the highest potential for conversion and loyalty. It also enhances the customer experience by providing consumers with products and marketing messages that are more closely aligned with their individual needs and preferences.

Adapting Marketing Strategies to Consumer Behavior Trends

Adapting marketing strategies to consumer behavior trends is essential for businesses to stay relevant and competitive. Consumer behavior is constantly evolving, influenced by factors such as technological advancements, cultural shifts, and economic changes. By staying attuned to these trends, businesses can anticipate changes in consumer needs and preferences, and adjust their marketing strategies accordingly. This may involve adopting new marketing channels, such as social media or influencer marketing, to reach consumers where they are most active. It could also mean developing new products or services that align with emerging consumer trends, such as sustainability or personalization. Adapting marketing strategies to consumer behavior trends requires a proactive approach, with ongoing research and analysis to identify emerging patterns. Businesses that successfully adapt to these trends can capture new market opportunities, enhance customer engagement, and maintain a competitive edge.

Case Studies in Consumer Behavior Research

Analysis of real-life examples and their implications.

Real-life case studies in consumer behavior research provide valuable insights into the practical application of theoretical concepts and the effectiveness of different marketing strategies. For example, a case study in the automotive industry might analyze how consumer preferences for eco-friendly vehicles have influenced car manufacturers’ product development and marketing strategies. In the retail sector, a case study could examine the impact of online shopping on brick-and-mortar stores and how these businesses have adapted to the digital era. These case studies offer concrete examples of how businesses have successfully navigated changes in consumer behavior, providing lessons and strategies that can be applied in other contexts. They also highlight the importance of consumer research in identifying market trends, understanding consumer needs, and developing effective marketing strategies. By analyzing real-life examples, businesses can gain a deeper understanding of consumer behavior, learn from the successes and challenges of others, and apply these insights to their own strategies.

Examination of Successful Marketing Campaigns Based on Consumer Behavior Research

Examining successful marketing campaigns that are based on consumer behavior research can provide valuable insights into effective marketing practices. These case studies demonstrate how a deep understanding of consumer needs, preferences, and behaviors can be leveraged to create impactful marketing campaigns. For instance, a campaign that effectively uses consumer data to personalize messages and offers can result in higher engagement and conversion rates. Another example might be a campaign that taps into current consumer trends, such as sustainability or wellness, to resonate with the target audience. Analyzing these successful campaigns can reveal key strategies and tactics that businesses can adopt, such as the use of specific channels, messaging techniques, or promotional offers. These case studies also highlight the importance of data-driven decision-making in marketing, showing how consumer research can inform and guide successful marketing initiatives.

Motivating Consumers and New Product Adoption

Strategies to motivate consumers to adopt new products.

Motivating consumers to adopt new products is a critical challenge for businesses. Effective strategies for encouraging new product adoption include leveraging social proof, offering free trials or samples, and creating educational content. Social proof, such as customer testimonials or influencer endorsements, can reduce perceived risk and increase consumer confidence in trying a new product. Free trials or samples allow consumers to experience the product firsthand, reducing barriers to adoption. Educational content, such as how-to guides or product demonstrations, can help consumers understand the value and benefits of the new product. Additionally, businesses can use targeted marketing campaigns to reach early adopters and innovators who are more likely to try new products and spread the word to others. Creating a sense of urgency or exclusivity around the new product, through limited-time offers or exclusive access, can also motivate consumers to adopt the product more quickly.

Innovations in Consumer Behavior Research for New Product Development

Innovations in consumer behavior research are playing a crucial role in new product development. Advanced analytics and data mining techniques allow businesses to analyze large datasets and uncover deep insights into consumer needs and preferences. Social listening tools enable companies to monitor social media and online conversations, gaining real-time insights into consumer opinions and trends. Virtual reality (VR) and augmented reality (AR) technologies are being used to test consumer reactions to new products in simulated environments, providing valuable feedback before market launch. Behavioral economics principles, such as understanding cognitive biases and decision-making processes, are also being applied to better predict consumer responses to new products. These innovations in consumer behavior research provide businesses with more accurate and comprehensive data, enabling them to develop products that are closely aligned with consumer needs and preferences, increasing the likelihood of market success.

Social Media and Consumer Behavior

Influence of social media on consumer behavior.

Social media has a profound influence on consumer behavior, shaping how consumers discover, research, and share information about products and services. Platforms like Facebook, Instagram, and Twitter serve as important channels for brand communication and engagement. Consumers use social media to seek recommendations, read reviews, and gather opinions from their networks, which significantly influences their purchasing decisions. Brands leverage social media for targeted advertising, influencer partnerships, and content marketing, creating opportunities for direct interaction and engagement with consumers. Social media also facilitates the spread of trends and viral content, quickly influencing consumer preferences and behaviors. The interactive and dynamic nature of social media means that consumer opinions and trends can rapidly change, requiring businesses to be agile and responsive in their social media strategies. Understanding the influence of social media on consumer behavior is essential for businesses to effectively engage with their audience and influence purchasing decisions.

Role of Social Media in Shaping Consumer Perceptions and Purchase Decisions

Recap of the importance of consumer behavior research.

Consumer behavior research is essential for businesses seeking to understand and effectively respond to the evolving needs and preferences of their target audience. It provides valuable insights into why consumers make certain choices, what influences their purchasing decisions, and how they interact with brands. This research is crucial for developing effective marketing strategies, creating products that meet consumer needs, and enhancing the overall customer experience. By staying informed about consumer behavior trends and applying these insights, businesses can improve customer engagement, increase brand loyalty, and drive growth. In today’s competitive marketplace, a deep understanding of consumer behavior is a key differentiator, enabling businesses to create more personalized, relevant, and impactful marketing initiatives.

Future Directions and Emerging Trends in Consumer Behavior Research

The future of consumer behavior research is marked by rapid advancements in technology and data analytics, leading to more sophisticated and nuanced understanding of consumer preferences and behaviors. Emerging trends include the use of artificial intelligence (AI) and machine learning to analyze consumer data, providing deeper and more predictive insights. The integration of biometric data, such as eye tracking and facial recognition, offers new ways to understand consumer responses to marketing stimuli. The growing importance of sustainability and ethical considerations is also influencing consumer behavior, leading to increased demand for eco-friendly and socially responsible products. Additionally, the rise of the experience economy is shifting focus from product features to customer experiences, requiring businesses to create more immersive and engaging customer interactions. Staying abreast of these trends and continuously innovating in consumer behavior research will be crucial for businesses to remain relevant and competitive in the changing market landscape.

How NIQ and GfK Can Help

In the complex world of consumer behavior, NIQ and GfK offer the expertise and tools necessary to navigate this landscape effectively. With comprehensive solutions like:

• NielsenIQ’s Homescan : Track, diagnose, and analyze consumer behavior from more than 250,000 households across 25 countries.
• Consumer analytics : Go deeper and create more clarity around shopper behavior with custom surveys and segmentation.
• Consumption moments : Reveal the true motivations behind customer consumption behavior and usage to guide product innovation and marketing strategy .
• gfknewron marke t : Create the right opportunities with gfknewron market
• gfknewron predict : Plan your future using the world’s most comprehensive sales tracking data for Tech & Durables.
• gfknewron Consumer : Understand your consumers’ behavior to redefine your success

By leveraging these tools, businesses can gain a competitive edge, adapting to market changes and consumer trends with agility and precision.

This page does not exist in [x], feel free to read the page you are currently on or go to the [x] homepage.

Burberry Case Study about Consumer Behavior

15 Pages Posted: 10 Feb 2020

Chenoy Ceil

Independent

Date Written: May 12, 2018

Consumer behavior is an essential part of the marketing for brands that are trying to influence the purchasing behavior of consumers. Burberry as a brand has been able to influence the purchase decisions of consumers by utilizing motivational, perception, personality and lifestyle strategies. This paper looks at the various factors that are utilized by Burberry that act as marketing stimulus for influencing the purchasing decision of their consumers. Some recommendations dealing with the brand perception of Burberry are also provided to help Burberry improve their sales and create a unique fashion brand for itself. Motivation, personality and emotion are important factors that affect consumer decision making, especially in the case of high fashion products. Looking at all these various factors in detail, this paper concludes that motivation, perception, personality and lifestyle have been carefully utilized by Burberry to reposition its brand for the modern age.

Keywords: chenoy ceil, consult corportes, consumer behaviour, purchasing decision, fasion brand

Suggested Citation: Suggested Citation

Chenoy Ceil (Contact Author)

Independent ( email ), do you have a job opening that you would like to promote on ssrn, paper statistics, related ejournals, microeconomics: intertemporal consumer choice & savings ejournal.

Subscribe to this fee journal for more curated articles on this topic

Decision-Making in Economics & Finance eJournal

Decision-making & management science ejournal, social & personality psychology ejournal, cognitive psychology ejournal.

Chapter 13 – Swiggy: A Consumer Behavior Case Study

We have already studied the theory of consumer behavior. You can find the full list of chapters here. It is now time to conclude with a bang!  This is a…

We have already studied the theory of consumer behavior. You can find the full list of chapters here . It is now time to conclude with a bang!  This is a bonus chapter to discuss a consumer behavior case study.

When you ask someone if they want to order food at home, the most common response is, “Chal Swiggy karte hain.” Founded in 2014 as an online food delivery service, Swiggy has become one of the most popular apps in India today. 

No business can succeed without pleasing its customers. What better way to satisfy consumers than by studying consumer behavior? 

It is common to see Swiggy sway us toward ordering food instead of eating at home with its eye-catching notifications about delicious food. But how does Swiggy know exactly what you’re craving each and every time?

This consumer behavior case study will try to demystify Swiggy’s success in India, how it has managed to defeat the competition, and how it deploys consumer behavior analytics to its advantage.

Let us begin with a quick history lesson.

Swiggy’s history

There is no better way of starting a case study than understanding how the organization started and how it has grown. In this consumer behavior case study, we will use the same method.

Swiggy was founded in 2014 by two BITS Pilani graduates, Sriharsha Majety and Nandan Reddy. It first tied up with some eateries in Bangalore and started delivering food to customers in under forty minutes in spite of the Bangalore traffic! 

At that time, there was no established business that was catering to this particular sector. Swiggy’s competitors were struggling, and at the beginning, so was Swiggy. 

It was difficult to get restaurants to partner with it. So, Swiggy made its logistics network faster, easier, and streamlined with a widespread and strong network of local delivery boys to make it stand apart in the online food delivery scenario. Soon, restaurants saw the perks of joining Swiggy (increased sales) and joined forces with it.

Swiggy raised $80 million in funding by 2015. After investors began to invest in the startup, the platform began to experience great heights. The food platform had partnered with over 100 restaurants by the end of 2015, and it was delivering over 70,000 orders each month.

Swiggy experienced losses 65 times in March 2016. Swiggy made the decision to focus on cost-cutting and bolstering the logistics network in April 2016. In order to better understand its customers' needs and improve its operations, Swiggy made investments in core engineering, automation, data sciences, machine learning, and personalization in 2017.

By the end of December 2017, Swiggy had expanded to more than ten cities, had partnerships with more than 20,000 restaurants, and was recording a staggering 4+ million transactions per month on their balance sheet. Swiggy acquired Scootsy in 2018 to expand its operations in industries like groceries, fashion, stationery, and other necessities, as well as to better serve its customers' needs and to improve its operations in 2017.

By 2019, Swiggy had a daily order volume of about 1.4 million, a delivery team of 45,000 agents, 1,30,000+ restaurant partners, and a presence in more than 325 Indian cities.

In 2020, when the pandemic hit, we all had massive cravings for restaurant food. The few of us who were still not using online food delivery platforms downloaded our only savior - Swiggy. The relief when the shahi paneer and butter naan got delivered…

The next step in studying the consumer behavior case study of Swiggy is understanding its consumer behavior strategies. Let’s take a look at them.

Swiggy’s strategy for customer retention

If you compare the notifications/ads that you and your friend get from the Swiggy app about four to five times a day, you will find some similarities. However, if you and your friend like completely different cuisines, you will notice the differences too.

For example, when I get a notification from Swiggy, it usually advertises burgers or fries. If you are an avid consumer of Indian food, you might get ads for samosas or chhole bhature, if you like Chinese food, you might get ads for manchurian and noodles, and so on.

In this way, Swiggy uses a hyperlocal marketing strategy . One definition of hyperlocal marketing is “a strategy that targets potential customers who are close to your business location and looking for products and services like yours.” ( PlotProjects ) 

This location is very specific. Swiggy tracks your location and suggests restaurants within a few kilometers radius. For example, if you live in North Delhi, you would rarely be suggested a restaurant in South Delhi. If so, you will be informed in advance that delivery fees would be higher than normal due to increased distance.

Swiggy uses machine learning to track users’ past purchases, search history, and even where they usually order from to make super-personalized ads. The ads are usually followed by a coupon if the consumer taps on the ad and visits the suggested restaurant’s page.

Using machine learning and these super-personalized ads, Swiggy was able to significantly reduce its customer acquisition cost.

Swiggy’s promotional strategies

Let’s talk about those push notifications again. Swiggy uses these notifications to retain your interest in its services and to increase your time spent on the app.

But what about Swiggy’s promotional campaigns? We won’t just discuss what Swiggy does to retain old customers in this consumer behavior case study. In this section, we will discuss how Swiggy promotes its services.

Swiggy’s promotional campaigns are both engaging and participatory . The posts are humorous, appealing, of outstanding quality, and lighthearted. Ingenious puns and one-liners were used in campaigns like #EatYourVeggies, #SuperSwiggy, and #EarnYourCheatMeal to promote healthy eating.

Apart from these campaigns, Swiggy also gets its services promoted by influencers . Across the board, Swiggy is active on social media. They also publish humorous blogs that make fun of current events in order to promote the company's goals and services.

Daily emails are sent by Swiggy to its clients. They use eye-catching images, smart slogans, and mind-blowing deals to grab customers' attention. Customers like us then increase Swiggy’s CTR by clicking on the links and notifications to enter the sweet sweet world of tasty food.

How Swiggy reads customer experience

When you log on to Swiggy from a different location, you first choose a delivery address, decide the cuisine you would like to have, scroll through the endless list of available restaurants, and finally scroll through the menus of these restaurants. 

You do all this while keeping in mind your budget for both time and money. As a result, you end up spending too much time deciding what to eat and ultimately settling for something that can reach you within less than half an hour. Wouldn’t you love it if Swiggy just offered you some pre-customized carts that you can order in a jiffy?

Well, this is not only true in this consumer behavior case study. Swiggy is actually planning to offer these pre-customized carts with two items each ! It is planning to incorporate these changes in upcoming versions of the mobile application.

With the machine learning tools already in place to create echo chambers of recommended restaurants with your favorite cuisines, Swiggy will use Food Intelligence (FI) technology to make consistent combinations of two dishes each. Consumers will be able to order these directly without having to give too much thought to what to eat.

For example, if Swiggy has the data to show that you like Chinese food, it might show you a pre-made cart with noodles and manchurian. If you like North Indian food, it might offer you a cart with shahi paneer and butter naan.

How Swiggy facilitates online consumer behavior

SInce the pandemic in 2020, we have all started craving good experiences. As an Indian, I feel like no experience is superior to having good food and good company. Swiggy solves one of these pressing issues - providing good food at your convenience.

However, we also love the comfort of knowing that we have a single trustworthy medium to fulfill at least a few of our basic needs. Apart from delivering food, Swiggy ventured into grocery delivery, in-city courier services, and even delivering items from small businesses .

The pandemic made us realize how fickle the physical environment is. It didn’t take us long to try new grocery delivery apps like Big Basket and Grofers. However, we wanted a guarantee from the application, and we also wanted free space in our phones. 

When Swiggy ventured into the grocery division, it was a huge respite for some. Swiggy had already established its network and customer base. All it needed to do was partner with supermarkets and our favorite kiranas.

With the guarantee to deliver groceries to the comfort of our homes in less than half an hour, Swiggy quickly became one of our favorite apps for ordering groceries. Since we could get rid of apps that solely delivered groceries, we didn’t mind the free space on our phones either!

The second division Swiggy got into was the intra-city courier service, which Swiggy named Swiggy Genie. You can order food from a restaurant, get your groceries, and even send items to someone you’re too busy to meet in the same city.

This service was especially helpful for people who worked late hours and missed their mom’s rajma chawal. Their moms could easily send lunch to them without having to travel.

Swiggy has another division now called Swiggy Minis. It supports small businesses in major cities in India by facilitating delivery to customers, giving them an online store feel with its own mobile application interface, and making it easier for customers to discover them.

Since it’s a consumer behavior case study, we will now conclude by analyzing what a huge role consumer behavior plays in Swiggy’s strategies. 

Analyzing the role of consumer behavior

In a nutshell, Swiggy observed online consumer behavior and converted its application into a one-stop shop for almost all the daily needs of Indian consumers. It understood the need for trust and credibility for consumers in India while also understanding the need for comfort even when shopping online.

Slowly, step by step, Swiggy created a platform for consumers to order food, groceries, and meat, send and receive intra-city couriers, and order items from their favorite small businesses. It shaped its promotional strategies to suit the needs of the young Indian consumer. Its promotions are flashy and engaging, and its offers are irresistible.

It is great at retaining customers, not only because of the variety and convenience it offers but also because of its quick and satisfactory customer service. With the pre-customized carts, it will ensure that even more customers are retained.

In all, Swiggy is one of the biggest food delivery giants in the country because of its exceptional use of consumer behavior data it collects and consumer trends prevalent in the market.

Conclusion and key takeaways

In this chapter, we discussed the consumer behavior case study of one of the biggest food delivery giants in the country - Swiggy. To recap, we looked at how Swiggy uses consumer behavior in its following strategies:

• Customer retention strategy
• Promotional strategy
• Reading customer experience
• Facilitating online consumer behavior.

• Free Resources

5 mini case studies about understanding and serving the customer

This article was originally published in the MarketingSherpa email newsletter .

Mini Case Study #1: 34% increase in conversion for powdered health drink company by helping customers come to their own conclusions

A single-product company that sells high-quality, all-natural, powdered health drinks engaged MECLABS Institute to help better understand their potential customers and increase the conversion rate of prospects reaching the homepage.

The original homepage took a claims-driven approach – it provided several bold statements about what the product would do for a customer with no information about the product to help the customer understand why it would work for them. Here is a look at the upper left of the original homepage.

Creative Sample #1: Upper left of original homepage for health drink company

The MECLABS team created a version of the homepage that took a conclusion-driven approach – instead only trying to convince potential customers with only bold claims about the product, the homepage copy included information about the product to help customers understand why the product would help them.

Creative Sample #2: Upper left of treatment homepage for health drink company

The team tested this version as the treatment against the original homepage (the control) to help better understand what communication style customers would respond to.

The treatment generated a 34% increase in conversion rate.

This experiment highlights a classic disconnect between customers and marketers. If you work in a company or with a client, you have intimate knowledge of the product and believe in its effectiveness. You spend all day thinking about it. You personally know some of the people who designed it. Your paycheck depends on the success of the product.

A customer does not have this same understanding or belief in the product. They have a significant gap in their knowledge about your product. Bold claims alone are not enough to close that gap. They have to understand why the product will work and come to their own conclusions about the company’s ability to deliver on its promises.

You can learn more about this experiment in The Conversion Heuristic Analysis: Overcoming the prospect’s perception gap from MarketingExperiments (MarketingSherpa’s sister publication).

Mini Case Study #2: Bags company increases conversion 191% by adding clarity to homepage

“I'm the CEO of Doubletake , a tennis and pickleball bag company, but I spent the majority of my career focused on messaging and research, consulting as a strategist for top brands for the last 10 plus years, and in-house prior to that. I'm almost embarrassed that I have this example to share, but I thankfully came to my senses!,” Shawna Gwin Krasts told me.

“It is interesting that crafting messaging/copy for products that aren't ‘your baby’ is so much easier – there is just more distance to see it for what it is. If this wasn't so near and dear to my heart, I would have caught it in a second.”

The team launched its homepage with only the headline “Sports Meets Style” over a photo of a bag. The headline was meant to differentiate the brand from competitors that were either only sporty or fashionable. Below the headline was a call-to-action (CTA) button with the word “shop.”

Creative Sample #3: Previous homepage copy for bag company

Internally it seemed obvious that the company sells tennis and pickleball bags since a bag was in the photo.

But they came to realize that it might not be as clear to website visitors. So the team added the subhead “Gorgeous Yet Functional Tennis and Pickleball Bags.” They also added the word “bags” to the CTA so it read “shop bags.”

Creative Sample #4: New homepage copy for bag company

These simple changes increased the website's conversion rate by 191%.

“It is so important for marketers to get out of their own heads,” Krasts said. “I suppose this is why I struggle with messaging so much for Doubletake. I am the target customer – I have the answers in my head and I suppose my natural curiosity isn't as strong. But clearly, I also have to remember that I've seen my homepage 10,000 more times than my customers, which means things that seem obvious to me, like the fact that Doubletake is a tennis brand not a reseller, might not be obvious.”

Mini Case Study #3: Online motorcycle gear retailer doubles conversion with personalized emails

There are ways to better tap into what customers perceive as valuable built into certain marketing channels. Email marketing is a great example. Marketers can build off information they have on the customer to send more relevant emails with information and products the customer is more likely to value.

"Very early in my marketing career I was taught, 'You are not the target audience' and told to try to see things from my customer's perspective. Empathizing with customers is a good start towards seeing products from the customers' perspective, but marketers really need to focus on quantifiable actions that can help identify customers' needs. That means continuous testing across messaging, price points, packaging, and every other aspect of a product. This is where personalization can really shine. Every time a marketer personalizes a message, it brings them closer to their customer and closes that gap," said Gretchen Scheiman, VP of Marketing, Sailthru.

For example, 80% of the email messages RevZilla sent were generic. But the website sells motorcycle parts and gear to a wide range of riders, each with their own preference in brand and riding style. The online motorcycle gear retailer partnered with Sailthru to better connect with customer motivations. The team started by upgrading the welcome series for new customers by personalizing the email messages based on the customers’ purchases and preferences.

The company has tested and added many new triggers to the site, and now has 177 different automation journeys that include triggers for browse and cart abandonment as well as automations for different product preferences, riding styles and manufacturer preferences.

The conversion rate from personalized email is double what RevZilla was getting for generic batch-and-blast sends. Automated experiences now account for 40% of email revenue. Triggered revenue is up 22% year-over-year and site traffic from triggers has increased 128% year-over-year.

"Customizing the buyer journey isn't about one long flow, but about lots of little trigger points and tests along the way. For any marketer that is intimidated about getting started with personalization, it's important to realize that it's more like a lot of small building blocks that create a whole experience. We started with a custom welcome series using testing and built from there. We're still adding new tests and new trigger points, but it's with the same concept that we started with,” said Andrew Lim, Director of Retention Marketing, RevZilla.

Mini Case Study #4: Pet protection network increases revenue 53% thanks to survey feedback

Huan makes smart tags for pets to help owners find their pets if they go missing. Initially, the company focused on the technical features in its homepage copy. For example, the tags don’t emit harmful radiation, are water-resistant and have a replaceable one-year battery.

From customer feedback surveys, the team discovered that customers purchased the product because they were worried they wouldn’t be able to find their pet if the pet went missing. This discovery prompted the team to change its messaging.

The new messaging on the homepage read, “Keep your pet safe and prevent heartbreak. Huan Smart Tags help you find your missing pet automatically.”

Revenue increased 53% increase following the change in messaging. “We immediately saw an increase in engagement on our website, with a lower bounce rate, higher click-through rate and a higher conversion rate. There were also a few people who messaged us on social media saying how our new message resonated with them,” said Gilad Rom, Founder, Huan.

Mini Case Study #5: Talking to new customers leads SaaS to change strategy, increase sales 18%

When Chanty launched, the marketing messages focused on pricing since the Saas company is 50% less expensive than the best-known competitor. However, when the team started talking to customers, they discovered most people had switched from the competitor for different reasons – ease of use, better functionalities in the free plan, better experience with the customer support team, and a better mobile app.

The team changed its marketing to focus around these product attributes and only listed pricing in the end as an additional benefit.

“It turned out that this was the way to go because we attracted people who wanted a better experience, rather than just customers who wanted to save money. After six months of implementing this new marketing and sales strategy, our sales grew by 18%,” said Jane Kovalkova, Chief Marketing Officer, Chanty.

Related resources

The Prospect’s Perception Gap: How to bridge the dangerous gap between the results we want and the results we have

Customer-First Marketing: Understanding customer pain and responding with action

Marketing Research Chart: How customer understanding impacts satisfaction

Improve Your Marketing

Join our thousands of weekly case study readers.

Enter your email below to receive MarketingSherpa news, updates, and promotions:

Note: Already a subscriber? Want to add a subscription? Click Here to Manage Subscriptions

Get Better Business Results With a Skillfully Applied Customer-first Marketing Strategy

The customer-first approach of MarketingSherpa’s agency services can help you build the most effective strategy to serve customers and improve results, and then implement it across every customer touchpoint.

Get headlines, value prop, competitive analysis, and more.

Marketer Vs Machine

Marketer Vs Machine: We need to train the marketer to train the machine.

Free Marketing Course

Become a Marketer-Philosopher: Create and optimize high-converting webpages (with this free online marketing course)

Project and Ideas Pitch Template

A free template to help you win approval for your proposed projects and campaigns

Six Quick CTA checklists

These CTA checklists are specifically designed for your team — something practical to hold up against your CTAs to help the time-pressed marketer quickly consider the customer psychology of your “asks” and how you can improve them.

Infographic: How to Create a Model of Your Customer’s Mind

You need a repeatable methodology focused on building your organization’s customer wisdom throughout your campaigns and websites. This infographic can get you started.

Infographic: 21 Psychological Elements that Power Effective Web Design

To build an effective page from scratch, you need to begin with the psychology of your customer. This infographic can get you started.

Receive the latest case studies and data on email, lead gen, and social media along with MarketingSherpa updates and promotions.

• Your Email Account
• Customer Service Q&A
• Search Library
• Content Directory:

Questions? Contact Customer Service at [email protected]

© 2000-2024 MarketingSherpa LLC, ISSN 1559-5137 Editorial HQ: MarketingSherpa LLC, PO Box 50032, Jacksonville Beach, FL 32240

The views and opinions expressed in the articles of this website are strictly those of the author and do not necessarily reflect in any way the views of MarketingSherpa, its affiliates, or its employees.

McCombs School of Business

• Español ( Spanish )

Videos Concepts Unwrapped View All 36 short illustrated videos explain behavioral ethics concepts and basic ethics principles. Concepts Unwrapped: Sports Edition View All 10 short videos introduce athletes to behavioral ethics concepts. Ethics Defined (Glossary) View All 58 animated videos - 1 to 2 minutes each - define key ethics terms and concepts. Ethics in Focus View All One-of-a-kind videos highlight the ethical aspects of current and historical subjects. Giving Voice To Values View All Eight short videos present the 7 principles of values-driven leadership from Gentile's Giving Voice to Values. In It To Win View All A documentary and six short videos reveal the behavioral ethics biases in super-lobbyist Jack Abramoff's story. Scandals Illustrated View All 30 videos - one minute each - introduce newsworthy scandals with ethical insights and case studies. Video Series

Case Study UT Star Icon

Buying Green: Consumer Behavior

Do purchasing green products, such as organic foods and electric cars, give consumers the moral license to indulge in unethical behavior?

Green consumer products, such as organic food, fair trade coffee, or electric cars, represent a fast-growing segment of the consumer market. In the area of organic food alone, data from the Organic Trade Association reveals that consumer demand in the United States has seen double-digit growth every year since 1990. In 2014, the organic food market reached almost $40 billion in sales. Consumers of these products tend to be seen in a more positive light—they are deemed more ethical, more altruistic, and kinder than people who do not buy green products. But is there another side to this kind of consumer behavior?

In a series of experiments comparing consumption of green and “conventional” products, psychologists Nina Mazar and Chen-Bo Zhong demonstrated that those people who bought green products—like eco-friendly laundry detergent or organic yogurt—were less likely to share money with a stranger, more likely to cheat on a task in which they could earn money, and more likely to steal money when they thought they would not get caught. As the psychologists stated, “purchasing green products may license indulgence in self-interested and unethical behaviors.”

Mazar and Zhong, whose study received considerable media attention in their native Canada, as well as in American and British publications, said the results surprised them. Initially, they expected green products to provide a halo effect, whereby the positive impressions associated with green consumption would lead to positive outcomes in other areas. “Given that green products are manifestations of high ethical standards and humanitarian considerations, mere exposure [to them would] activate norms of social responsibility and ethical conduct,” said Mazar and Zhong in an interview.

But as the results indicate, the opposite can be true. “The message of this research is that actions which produce a sense of self content and moral glow can sometimes backfire,” Mazar stated in another interview.

These patterns have been shown to extend to other shopping scenarios. For example, one study tracked scanner data and shopper receipts at a California grocery store. Those shoppers who brought reusable grocery bags with them were more likely to buy environmentally friendly products, like organic food. But they were also more likely to buy indulgent products, like ice cream, cookies, candy, and cake. The researchers followed up this study with a series of experiments that showed these moral licensing effects only happened when the decision to bring the reusable bags was at the shopper’s discretion. When shoppers were told that the store required customers to use cloth bags, licensing effects disappeared and customers chose not to buy indulgent products. Only when consumers felt like using cloth bags was their own idea did the moral licensing effects hold.

Discussion Questions

1. Beyond green consumption, what other types of products might bring about similar kinds of moral licensing effects? Can you think of instances in your own life when your purchase choices have licensed you to make decisions that were less than ethically ideal? Explain.

2. Do you think these moral licensing effects are common across all kinds of green consumers? Or are there other factors (i.e. demographics, psychographics) that might either exacerbate or weaken the effects? Why or why not?

3. The authors of the study, Mazar and Zhong, initially thought green consumption would have a positive spillover effect and encourage positive behaviors. Why do you think they found the opposite?

4. What steps do you think can be taken to help minimize or mitigate these types of moral licensing effects among green consumers? Explain.

5. If you were the brand manager for a green product, for example an organic food item or an energy-efficient appliance, how would you go about marketing the product knowing these licensing effects were possible?

Related Videos

Moral Equilibrium

When we do something good we get to thinking of ourselves as pretty good people, and can then give ourselves license to fail to live up to our own ethical standards. This phenomenon is known as moral equilibrium.

Bibliography

Organic Market Analysis – Organic Trade Association https://www.ota.com/resources/market-analysis

Research: Reusable Shopping Bags May Encourage an Unhealthier Diet http://www.fuqua.duke.edu/news_events/news-releases/bollinger-shopping-bags/

How going green may make you mean https://www.theguardian.com/environment/2010/mar/15/green-consumers-more-likely-steal

Goodies behaving badly https://www.theguardian.com/commentisfree/cif-green/2010/mar/16/green-consumers-lie-more-ethics

Are green consumers more unethical? http://www.torontosun.com/news/columnists/thane_burnett/2010/03/16/13246791.html

When buying in means selling out: Sustainable consumption campaigns and unintended uncivic boomerang effects http://www.comm.ucsb.edu/faculty/rrice/Atkinson.pdf

Stay Informed

Support our work.

Impact of the new middle class on consumer behavior: a case study of Delhi-NCR

Journal of Asian Business and Economic Studies

ISSN : 2515-964X

Article publication date: 1 June 2021

Issue publication date: 29 August 2022

The paper examines the increase in annual income of the new middle-class (The NMC) of Delhi-NCR and its impact on their investment habits, consumption habits and lifestyle. The paper aims to look into the transformation of the new middle-class into the NMC in emerging economies and its potential to the companies and investors.

Design/methodology/approach

This study draws insight from 558 new middle-class consumers in Delhi-NCR. ANOVA, post hoc tests , and hierarchical multiple linear regression model are applied to test the proposed hypotheses.

The NMC living in India's megacities imitates the lifestyle of their counterparts living in the West. To maintain their status and present themselves different from those living in middle or lower-middle-class categories, they spend audaciously, even though the income is low. When they enter the new middle class, their consumption, saving and lifestyle diversify positively.

Research limitations/implications

This study has limitations. First, the authors do not apply any behavioral theory or marketing model such as the theory of reasoned action (TRA), Engel-kollat-Blackwell (EKB) model or theory of normative model of target markets. Second, the research is limited to the NMC of only one emerging economy, i.e., India. Third, the research sample is limited to only one megacity of India, i.e., Delhi. Finally, this research used only one factor, i.e., AI, to study the consumption pattern.

Practical implications

The results suggest that considering the buying habits and lifestyle of Indian the NMC, consumers would prove helpful to the companies in product decision-making. Furthermore, understanding change in investment habits across different income levels would be advantageous to financial institutions, investment planners and marketers while designing their products to attract investment.

Originality/value

The research holds significance from the point of view of understanding Indian consumers encompassing the the NMC and predicting their implications on consumer goods-producing industries, which shall, in turn, facilitate producers and government in formulating policies and strategies.

• New middle class (NMC)
• Middle class (MC)
• Consumer behavior (CB)
• Annual income (AI)
• Investment habits (IH)
• Buying/ spending habits (B/SH)
• Lifestyle (LS)

Chaudhary, A. and Khatoon, S. (2022), "Impact of the new middle class on consumer behavior: a case study of Delhi-NCR", Journal of Asian Business and Economic Studies , Vol. 29 No. 3, pp. 222-237. https://doi.org/10.1108/JABES-07-2020-0080

Emerald Publishing Limited

Copyright © 2021, Asiya Chaudhary and Sabiha Khatoon

Published in Journal of Asian Business and Economic Studies . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

In the last 2 decades, the developing economies have witnessed a remarkable shift in their growth and per capita income. Based on the surge in per capita income, the World Development Report (WDR) in 1978 introduced a grouping of “low income” and “middle income” countries using a threshold of $250 per capita income ( Prydz and Wadhwa, 2019 ). In 1989, a new category was introduced as a “high income” group ( Prydz and Wadhwa, 2019 ), which led to a remarkable change in the world economic scenario. With the swell in FDI during 2001–2018, countries categorized as low-income countries (hereafter LIC) entered middle-income countries (hereafter MIC) status ( Steinbach, 2019 ). Rapid economic growth, low poverty and increased real income trimmed the number of LIC to 31 in 2010 from 64 in 2001 ( Ravallion, 2010 ) and augmented the high-income countries to 80 ( Fantom and Serajuddin, 2016 ). The metamorphosis of LIC into MIC added new ranks between the rich and the poor by facilitating global mass consumption and shifted many households to the “middle class” (hereafter MC) in developing countries. Birdsall et al. (2000) encapsulate MC under the relative income approach as households with a per capita income range of 75 and 125% of the median household per capita income. Banerjee and Duflo (2008) wrap MC in developing countries under absolute approach as two groups of households: one with daily per capita expenditure between $2 and $4 and the other between $6 and $10. Besides income patterns, few scholars define MC as a class having access to different resources. Mainly concentrated in urban areas, MC consumers are well-educated and young ( Cavusgil et al. , 2018 ) whose motives are not accompanied by property but by other resources such as human capital ( Fernandes and Heller, 2006 ), education, organizational position or ownership of some exceptional occupational skill ( Dhawan, 2010 ).

1.1 New middle-class

Fernandes and Heller (2006) evidenced that the new middle class (hereafter the NMC) is a real and significant phenomenon and a “class-in-practice” whose boundaries are continually being defined and tested. Recently, there has been an eye-catching expansion in the radius of the NMC in emerging economies (hereafter EEs), particularly India and China, because of significant growth in annual disposable income ( Ozturk, 2016 ). Parker (2009) estimated that the NMC increased from nearly a third of the population in 1990 to more than half today in EEs. In India, the national economic policy 1991 scaled-down rural poverty from 94% in 1985 to 61% in 2005 and is projected to reduce further to 26% by 2025 ( Beinhocker et al. , 2007 ). According to a study conducted by McKinsey Global Institute (MGI), if India continues the same economic growth, the average household income will triple in the next 2 decades and will become the fifth-largest consumer market in the world by 2025 [1] . The new economic reform resulted in a boom in jobs and entrepreneurial opportunities for middle-class Indians ( Harriss, 2006 ) and improved disposable income. Not to mention, Delhi-NCR [2] , too, achieved an increase in annual disposable income (hereafter AI) which resulted in a voluminous change in consumption, savings and investment pattern of the bourgeoisie living there. Prime Minister Narendra Modi dubbed them the “neo middle class” as they helped the government move to power ( Mandhana, 2014 ). Delhi-NCR were chosen for the present study because Delhi is a “sui generis.” Being the national capital of India and a megacity with the highest share of inter-state migrants in its total population ( Kawoosa, 2019 ), Delhi continues to dominate the economy ( Beinhocker et al. , 2007 ). Jeelani (2019) quotes the report of economic survey of Delhi, which estimated that the capital's economy has grown at a rate of 8.60% in 2018–2019, and per capita income has increased to Rs. 3,65,529 (5336.72 US$), which is three times the national average, i.e., Rs. 1,25,397 (1830.79 US$). NCR, the first master plan of Delhi ( Nitesh, n.d. ), is rising briskly as a global economic hub, embracing a considerable percentage of the new urban middle class. In recent years, because of the increase in household consumption and expansion in the NMC, Delhi-NCR has become a hub of large, medium and small enterprises.

Some researchers affirmed that in India, economic reform expanded the radius of consumption and new desires for education, investment, employment and leisure, which revived the middle class as the “new middle class” ( Mathur, 2010 ; Varma, 2007 ) in megacities such as Delhi, Mumbai, Bangalore and Hyderabad, accounting for about 35% of the country's the NMC ( Ahmed et al. , 2016 ). In urban India, the NMC consists of the households having doctors, professors, engineers and entrepreneurs earning within a range of Rs. 55, 000.00 to Rs. 200,000.00 per month (US$ 781–US$ 2840) ( Beinhocker et al. , (2007) also support the researchers' observation), with at least one family member working abroad and at least one child studying in universities of the UK and US ( Khandekar, 2013 ). They practice a Western lifestyle ( Cavusgil and Kardes, 2013 ) and follow bourgeoisie values to distinguish themselves from those living in the middle-class. Parallel to this, there exists a group within the Indian the NMC that, in their lifestyle pattern, rejects bourgeoisie values and attitudes ( Fadaee, 2014 ). Class and status relationship has always been an issue in India ( Jaffrelot and van der Veer, 2008 ), leading to different consumption behavior across different income groups ( Kardes, 2016 ). Therefore, it would be interesting to know how far the increased disposable income impacted the consumer behavior of the Indian the NMC residing in megacities.

In this study, we took variables used in analyzing consumer behavior, including annual disposable income, investment habits, buying/spending habits and lifestyle. These variables are also relevant in assessing emerging markets' economic growth ( Belbağ et al. , 2019 ; Cavusgil and Kardes, 2013 ; Cavusgil et al. , 2018 ). Furthermore, income is one of the demographic factors which has a direct bearing on consumption patterns of different social classes ( Ahmed et al. , 2016 ; Durmaz and Durmaz, 2014 ; Isozaki et al. , 2017 ) and directly influences the living standards and decisions whether to spend or save for the future good ( Avadhani, 1968 ; Bishnoi, 2014 ; Kumarasinghe, 2017 ).

What is the difference in investment habits (hereafter IH), buying/spending habits (hereafter B/SH) and lifestyle (hereafter LS) of the NMC of Delhi-NCR across various income levels?

What is the impact of an increase in AI on IH, B/SH and LS of the NMC living in Delhi-NCR ?

The present study is structured on a sample of the NMC of one of India's megacities, Delhi-NCR. The study has applicability in the ambiance that aims to analyze the changes in IH, B/SH and LS of the NMC of Delhi-NCR because of the increase in their AI that they achieved due to the economic reform of 1991. Various scholars in different academic fields have extensively studied the consumption patterns of the middle-class in EEs, including India. However, limited work has been conducted to investigate the consumption pattern of the NMC living in megacities of India such as Delhi, Mumbai and Bangalore (e.g. van Holstein, 2019 ; Jana and Sarkar, 2018 ; Kaur et al. , 2016 ; Khandekar, 2013 ; Narayan et al. , 2015 ; Nijman, 2006 ; Schindler, 2014 ). There is a paucity of literature providing insight into the impact of the change in AI on the consumption pattern of the NMC living in Delhi-NCR (e.g. Schindler, 2014 ). The purpose of the current study is to fill the gap and add to the existing literature by measuring the impact of an increase in AI on the consumption pattern of the NMC of Delhi-NCR.

The paper's remainder is structured as follows: after presenting different definitions of MC and the NMC, we reviewed ( Section 2 ) the existing literature in the context of the NMC and its consumption pattern in EEs. In Section 3 , we discuss the sampling and data framework adopted in this paper. Section 4 justifies the methodology. In Section 5 , we present the results and discussion, and in the last ( Section 6 ), we discuss the conclusion, practical implications, limitations and future direction.

2. Literature review

2.1 characterizing the nmc in ees.

In EEs, the NMC is characterized by its Western lifestyle, high disposable income, discretionary consumption, consumption of leisure commodities, education, career orientation, profession/employment, cultural features and mentalities ( Cavusgil et al. , 2018 ; Chevalier, 2015 ; Fernandes, 2009 ; Iqani, 2017 ; Kharas and Gertz, 2010 ; Kaplan, 2013 ; Kapur et al. , 2002 ; Kardes, 2016 ; Krishnan and Hatekar, 2017 ; Varma, 2007 ). the NMC in EEs, such as India, China and Indonesia, is considered the offspring of economic development of the 1980 and 1990s ( Ansori, 2009 ; Tsang, 2014 ). They are often considered consumerist and politically anti-poor groups ( Fadaee, 2014 ; Nijman, 2006 ). Most EEs are characterized by their educated, growing new middle-class households, which have experienced significant enhancements in living standards and economic situation ( Belbağ et al. , 2019 ). They play a vital role in economic growth, wealth creation ( Goodman, 2012 ) and entrepreneurial development in EEs ( Cavusgil and Kardes, 2013 ). In China, they are called “new social strata,” consisting of professionals, managers, self-employed and private business owners − few of them with higher education and higher income ( Wu and Cheng, 2013 ). In Turkey, the NMC consists of the households that have attained increased disposable income and have experienced lifestyle changes since market liberalization reforms after the 1980s ( Uner and Gungordu 2016 ). Even though they experienced a decline in wages in Brazil, their discretionary spending surpasses their counterparts living in India, China and Russia ( Kardes and Chueke, 2017 ). In India, the economic growth allowed the NMC to adopt the change in lifestyle and learn to display the newly achieved wealth and confidence ( Brosius, 2012 ).

2.2 Consumption Pattern and annual income of the NMC

There is a significant difference in the IH (H1a), B/SH (H1b) and LS (H1c) across income levels of the NMC of Delhi-NCR.

There is a significant impact of change in AI (increase) on IH (H2a), B/SH (H2b) and LS (H2c) of the NMC.

3. Sampling and data

3.1 inclusion criteria.

The participants were randomly selected from banks, universities, professionals, self-employed groups, business people, etc., based on their annual income ranging from Rs. 4,50,000 to Rs. 25,00,000 (US$ 6391 to US$ 35508 as per 2019 average exchange rate) and the age group between 21 and 62 years. The selection criterion of income was based on the studies conducted by the National Council of Applied Economic Research (NCAER) [3] , McKinsey Global Institute (2007) [4] , Birdsall (2015) [5] and Isozaki et al. (2017) [6] . A total of 1,000 questionnaires were distributed, out of which 558 were found appropriate for analysis. Respondents were approached personally and through e-mail.

3.2 Measures

The constructs' definition and measurement were adapted mostly from existing literature to ensure the research quality. Each construct item was scored on a Five-Point Likert Scale (from “strongly disagree” to “strongly agree”). The questionnaire comprises two sections. The opening section included general questions to capture respondents' demographic profile, and the second section measured the constructs used in our study. Statements were modified as per the requirement of the current study ( Table 2 ).

4. Methodology

Model 1: Y = β 0 + β 1 GENDER + β 2 EMPLOYMENT + ε

Model 2: Y = β 0 + β 1 GENDER + β 2 EMPLOYMENT + β 3 ANNUAL INCOME + ε

5. Results and discussion

5.1 reliability and validity.

A preliminary data analysis was conducted first, wherein the accuracy of data, outliers, reliability and missing values of all the variables were checked. IBM-SPSS 20 has been used to derive the results, and the reliability of the measures was checked by using Cronbach's alpha ( Table 3 ). The validity of the model was measured by structural equation modeling (SEM), using AMOS 20. Cronbach's alpha of B/SH and LS surpasses the minimum threshold of >0.70, indicating the scale's relatively high reliability. IH's value was a bit low; however, in many studies, researchers have considered and accepted reliability of between 0.50 and 0.60 as minimally sufficient ( Peter, 1979 ; Shim et al. , 1989 ). Composite reliability (CR) for IH, B/SH and LS surpasses the widely agreed threshold of >0.7 for satisfactory convergent validity. Average variance extracted for IH and B/SH is greater than 0.5, indicating acceptable convergent validity, but AVE for IH is below the threshold. Fornell and Larcker (1981) suggest that CR alone can be used to conclude that the convergent validity of the construct is adequate ( Table 3 ). Correlation between factors is less than 0.7, indicating satisfactory discriminant validity.

5.2 Descriptive statistics

There are a total of 558 respondents, wherein 70.3% of the respondents are male, and 29.7% are female. Among them, 76.7% fall in the age group of 21–40 years. Further, 42.7% of respondents are graduates, 69% of them are in services, whereas 23.7% are self-employed. In the overall sample, 74.2% earn between Rs. 4,50,000–9,00,000 (US$ 6391–US$ 12783) annually, and 72% are married, while 28% are unmarried ( Table 4 ).

5.3 H1 : Measure of significant difference in the IH, B/SH and LS across various income levels

One way ANOVA results ( Table 5 ) showed that all three hypotheses ( H1a, H1b and H1c ) were rejected at 5% level of significance, it was needed to work out a post hoc test. Post hoc test ( Table 6 ) indicates that respondents of income category I and III and category II and III possess significantly different IH ( p  < 0.05) than their counterparts in other income groups. Respondents in income category II and III show significantly different B/SH ( p  < 0.05) in comparison to people in other income groups. People in income category I and II show significantly different LS ( p  < 0.05) than people in other income groups. To sum up, people in income category III have robust IH and B/SH than their counterparts in other income levels ( Table 7 ). People in income category I follow strong lifestyle patterns than people in other income levels.

5.4 H2 : Measure of the impact of change in AI (increase) on IH, B/SH and LS

For the development of the model, control variables are included in model 1 of IH, B/SH and LS ( Table 8 ). For IH, the model is statistically significant and explains 1.6% of the variance. The introduction of income in step 2 explains an additional 1% of the variance in IH after controlling for gender and employment. In step 1 of B/SH, the model is statistically significant and explained a variance of 4.8%. In step 2, the introduction of income with gender and employment explains an additional 1.3% variance in B/SH after controlling for gender and employment. In step 1 of LS, the model is statistically significant and explains a variance of 3.4% in LS. In step 2, when income is included, the model as a whole explains an additional 0.9% of variance after controlling for gender and employment. Gender and income are the statistically significant predictors of IH ( p  < 0.05), B/SH ( p  < 0.001) and LS ( p  < 0.001), while employment is a non-significant predictor. Gender proves to be the best predictor of IH ( β  = −0.08), B/SH ( β  = −0.22) and LS ( β  = −0.19) than employment and income. To sum up, gender and AI have more impact on spending patterns and lifestyle of the NMC than on investment patterns.

5.5 Discussion

As households persistently save a considerable portion of their disposable income, the sector always remains the net supplier of funds to the deficit sectors ( RBI, 2018 ). Our results confirm that investment decisions of the NMC change with change in AI depending on the preferences and priorities. The NMC, with relatively higher income, prefers to save more than their counterparts with low income. When annual income increases, they shift their investment choices from financial assets, e.g., shares, mutual funds, LIC, etc., to real estate, house and gold. Avadhani (1968) , Das (2012) , and NSO (2019) support our results that the NMC households prefer to invest in small savings, bank deposits, real estate and gold, followed by government securities and other financial assets. The results are also consistent with the studies of Bishnoi (2014) and Samudra and Burghate (2012) , which provided evidence that change in income brings inconsistency in investment behavior of the different income groups concerning the features of investment instruments.

The NMC consumers in megacities like Delhi are engaged in a shopping spree, spending on entertainment and merry-making. Respondents agreed that they prefer cars, brands or malls either because their peer groups did so or to symbolize their status in society. The rise in income affected their consumption of various categories of goods differently. They spend a large proportion of their increased income on “high-frequency” items, such as food, beverages, personal-care products, cars, entertainment, telecom products and services, in comparison to medium-frequency (apparel, home furnishings and tourism) and low-frequency items (such as consumer durables and appliances or any other luxury items) ( Singhi et al. , 2017 ). Hubacek et al. (2005) and later Narayan et al. (2015) reflected that economic success in countries like India and China has enhanced the middle class's annual income, resulting in a shift in consumption expenditure to more luxury goods. This shows evidence that the upper-middle class's preference in India's megacities such as Mumbai is mainly driven by credit card acceptance, shorter store distance and higher vehicle ownership. Thus, it is observed that as income increases, consumers get more open-handed, brand-conscious and aspire for anything that makes their life easier and comfortable.

There is a difference in the lifestyle of the NMC across AI, and our results verify that income impacts the lifestyle. Preference strengthens personal houses, branded cars, clothes, smart televisions, smart mobile phones, celebrity-endorsed products, etc. Respondents who moved to the layer of wealthy class plan vacations more vigorously. Our results are in conformity with the case study conducted by Brosius (2012) that vacations like a weekend trip to Thailand or Singapore, dining-out at five-star hotels and admitting children in elite private schools add to the quality of lifestyle. Hubacek et al. (2005) and Mathur (2010) show evidence that Indian NMC, within an AI range of Rs. 2,00,000- Rs. 10,00,000, prefer to enjoy higher-quality life as compared to their counterparts in a lower-income category. Many respondents favored imported products over domestic products, further supported by Lee et al. (2010) , concluding that Indian consumers prefer American brands over local brands for their uniqueness and good quality. As we checked on education preferences, Indian NMC is spending a significant percentage of their disposable income on good quality schools and colleges for their children. Our finding is similar to previous studies' results and confirmed that the importance of education for Indian NMC has increased in past years ( Roche et al. , 2011 ; Varma, 2007 ).

6. Conclusions

It is evident that consumption pattern varies with change in AI across cities and economies. When people move to the upper-income bracket, they spend a large portion of their disposable income on improving the quality of living standards and save some for a better life for their offspring ( Javalgi and Grossman, 2016 ). Given the lifestyle and consumption pattern, our results conform with the lines of Sheth (1999) quoted by Jaffrelot and van der Veer (2008) that membership of today's NMC is associated with new lifestyle patterns, ownership of economic assets and self-consciousness of belonging to the middle class. The NMC living in India's megacities enjoys a lifestyle similar to their counterparts living in developed countries. Based on the results, we could observe that high-income individuals in the NMC spend robustly on discretionary consumption and save a portion for the future than individuals with low income.

6.1 Practical implications

Our study's main contribution is that increase in AI after the economic reform resulted in a transformation of the MC to the bourgeois class and shifted their consumption behavior to discretionary items. The rapidly expanding radius of the NMC in EEs such as India has been attracting Western companies' focus ( Belbağ et al. , 2019 ; Kardes, 2016 ), which are well prepared to grab this augmented class to give tough competition to domestic companies. The positive factor with domestic companies is that they have the advantage of already established relations with local consumers and an understanding of their nature, which international companies might lack. Therefore, managers of domestic and international companies are required to strategize and innovate in the light of the diverse consumption behavior of the NMC in emerging economies ( Cavusgil and Kardes, 2013 ; Cavusgil et al. , 2018 ). In megacities, Delhi, in particular, there is a crisis of proper housing societies. There are mainly two reasons behind this crisis, either the houses are very distant from the workplace, or the prices are beyond the pocket of the NMC. At the same time, housing developers are also facing financial losses as the stock remains unsold. Therefore, to fill this gap, developers should come with housing schemes that match the priorities of the NMC. Our results should inspire corporate and policymakers. For a sustainable market economy, the policymakers cannot overlook the the NMC's role as entrepreneurs, teachers, professors, doctors, engineers, skilled workers and their role in bringing political parties into power. The policymakers should consider the effects of monetary and fiscal policies on those residing in the middle strata in EE. Hence, in the Indian context, the corporate sector and policymakers need to focus on two critical aspects: megacities' unique urbanization pattern and the fast-growing the NMC consumer market. Both play a pivotal role in reducing poverty and enhancing the country's economy.

6.2 Academic implications

For the academic implication, the researchers should consider that increase in income is one of the factors that directly influence the consumer behavior and lifestyle of people of different income categories. Therefore, researchers should be clear about making a distinction between the middle-class and new middle-class consumers. It should also be considered that an increase in income is an indicator of the growth of the NMC in EEs. Ozturk (2016) , in his study, mentions that growth in consumption in EEs is due to an increase in income of the upper-middle class.

6.3 Limitations and direction for future research

Our study has limitations. First, we do not apply any behavioral theory or marketing model such as the theory of reasoned action (TRA), Engel-Kollat-Blackwell (EKB) model or theory of normative model of target markets, which may be applied to study consumer behavior of THE NMC in emerging markets. Furthermore, we do not apply any social class theory, such as the Marxist theory or Weber's theory of class. This may prove to be a potential direction for future research. Second, the research is limited to the NMC of only one EE, i.e., India. Third, the research sample is limited to only one megacity of India, i.e., Delhi. Future researchers could consider the NMC of other megacities like Mumbai, Kolkata, Bangalore and Chennai and might compare their consumption patterns. Moreover, the NMC living in the countryside could also be considered for future studies.

Finally, in our study, the value of R 2 is low. In our study, we added gender and employment as control variables, which did not contribute much to improve the model, but as per the study's requirement, we have to stick to the same predictors only. However, previous studies show that the value of R 2 might be low (e.g., Kara et al. (2018) ). There may be other relevant variables that may be included in future studies as control variables to improve the value of R 2 . The use of more than one predictor might improve the value of R 2 ( Nau, 2014 ; Frost et al. , 2017 ). However, other factors such as age, qualification and marital status might influence consumer behavior and could be considered as control variables for future studies.

Hypotheses summary