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Google Looking for Customer Experience Research Lead, Customer Experience Lab at New York, NY Full Time

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Atlanta, GA, USA; Chicago, IL, USA; New York, NY, USA; Los Angeles, CA, USA; Washington D.C., DC, USA . Minimum qualifications:

• MBA or Master’s degree with emphasis in quantitative survey research or qualitative research, or equivalent practical experience.
• 6 years of experience conducting quantitative research surveys or qualitative research.
• Experience with SQL and a statistical analysis package (e.g., SPSS, Stata, R, Python).

Preferred qualifications:

• 6 years of experience in market research companies or vendors.
• Experience in quantitative research and statistical methods, including sampling, weighting, statistical testing on discrete and continuous data, and experimental design.
• Experience in qualitative research and text analysis methods, including Natural Language Processing (NLP), supervised and unsupervised machine learning.
• Experience planning and managing at strategic and operational level.
• Knowledge of the digital advertising space and Google Ads products.
• Excellent messaging, storytelling, and written/verbal communication skills, with the ability to influence executive decision making.

About The Job

The Business Strategy & Operations organization provides business critical insights using analytics, ensures cross functional alignment of goals and execution, and helps teams drive strategic partnerships and new initiatives forward. We stay focused on aligning the highest-level company priorities with effective day-to-day operations, and help evolve early stage ideas into future-growth initiatives.

The goal of Customer Experience (CX) Lab is to understand and improve the Customer Experience by uncovering data driven actionable insights for Google’s Advertising products. We are a team of Researchers, Data Scientists, Program Managers and Operations Managers conducting research and data analytics. We measure customers across the Ads Ecosystem and work cross-functionally with Product, Marketing, Sales and Support organization to drive actionability.

In this role, you will define and lead global research among Google’s advertising ecosystem partnering with executives and cross-functional leaders across Google’s Support, Product, Engineering, Brand and Sales organizations to bring actionable insights to the business. You will develop an understanding of business objectives, risks, issues, and opportunities to ensure research efforts are supportive of business decision-making and are actionable by executive leadership.

The Go-to-Market Operations (GtM) team ensures Google’s complex and ever-evolving Ads business runs smoothly. We are instrumental in setting go-to-market strategy, and ensuring flawless execution and operations against the strategy. We have teams embedded in each of the major Ads business areas as well as global teams that work across the business areas. Team members are analytical and strategic, with a pragmatic sense of how to get things done.

The US base salary range for this full-time position is $126,000-$190,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

Responsibilities

• Build partnership with the leaders across Google’s Support, Product, Engineering, Brand and Sales organizations. Ensure actionability of insights through cross-functional collaboration.
• Lead end-to-end quantitative customer surveys and/or qualitative research projects, including study design, development, execution, analysis, insights development, and insights sharing.
• Ensure survey research studies measure and report on actionable metrics and insights yielded using the highest methodological and scientific standards for instrument design, assessment, quality control, and analysis.
• Message actionable insights through written reports, self-service dashboards, and stakeholder presentations.
• Contribute to the continuous improvement of existing survey research offerings, methods, and processes and to the development of new offerings that will create positive impact for Google and our Users.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .

Job Overview

• Date Posted: Posted 8 months ago
• Location: New York, NY
• Job Title: Google Looking for Customer Experience Research Lead, Customer Experience Lab at New York, NY

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Expanding resources and teams for customer success

John jester.

Vice President, Customer Experience at Google Cloud

At Google Cloud, our customers are at the forefront of digital transformation—launching entirely new businesses and products built in the cloud, redefining entire industries with data and artificial intelligence, delivering innovative new consumer experiences, or committing to sustainable new ways of doing business.

We’re committed to our customers’ success, and over the past two years we’ve invested significantly in providing ongoing and integrated support through our customer care portfolio, including launching new Premium and Mission Critical Support offerings that allow us to monitor, prevent, and mitigate impacts quickly, while delivering the fastest response times in the industry.

Today, I’m proud to unveil several new resources and offerings for our customers, including a new Custom AI Solutions practice, new Global Delivery Centers, expanded Executive Briefing Centers, and new leaders to help continue to drive our organization forward.

Helping businesses innovate with a new Custom AI Solutions practice

We are investing in services and offerings to help our customers innovate and drive innovative change to business processes, culture, and customer experiences with Google Cloud products and services. Artificial intelligence (AI) and machine learning (ML) technologies are foundational for many such digital transformations, and to help customers create real business value with these technologies, we’re excited to launch a Custom AI offering to address our customers’ most critical innovation needs. 

AI and ML technologies are foundational to digital transformations, yet they are not “one size fits all.” Each customers’ problems and opportunities are unique; a rideshare company will use AI differently than a brick and mortar retailer, or a healthcare company, or an insurance firm. To help organizations deploy AI and ML more effectively, we’re launching a new Custom AI Solutions practice, offering customers custom-built AI and ML solutions built into Vertex AI; access to Google’s engineering expertise; and predictable, subscription-based pricing. 

Our teams are already partnering closely with early customers to build and deploy custom AI solutions. For instance, USAA, the large North American insurer, is using Google Cloud ML to process near-real-time damage estimates based on digital images to create a streamlined operations experience.

Learn more about our Custom AI Solutions practice offering here , and how we work together with our customers here . To get in touch, please contact our sales team .

Launching new Global Delivery Centers

Our drive to digitally transform our customers’ businesses is often manifested through our Global Delivery Centers, which expand our professional consulting and emerging practices capabilities available to customers and partners around the world.

The teams at our Global Delivery Centers help customers get up-and-running on Google Cloud quickly and cost effectively, and consult with customers to rapidly build capacity in areas like data analytics, hybrid and multi-cloud, artificial intelligence, and machine learning. More importantly, they help customers successfully execute projects in support of their most mission-critical business objectives. Critically, these centers also help our global partner ecosystem quickly ramp their Google Cloud practices, and get fast, expert consultation for their customers too.

In 2022, we aim to triple the size of our Global Delivery Center teams in Argentina, Poland, and India. In addition, we’ll invest in building deep Google Cloud talent in Mexico and Portugal, furthering our commitment to the industry’s best expert consultation for customers and partners around the world.

Expanding our Executive Briefing Centers footprint

In addition to our Global Delivery Centers, we’re also pleased to expand our resources and facilities that enable digital and face-to-face meetings and working sessions with our customers. This year, we will launch four new Executive Briefing Centers, located on Google Cloud campuses in London, Paris, Singapore, and Munich. 

These centers provide an opportunity to listen to our customers, share the best of Google Cloud’s solutions, and inspire digital transformation, in conversations facilitated by Google Cloud leadership, engineers, and industry experts. By bringing this experience to our customers in-region we can foster deeper partnerships and develop cloud solutions that meet their requirements for security, privacy, and digital sovereignty without compromising on functionality or innovation. 

Adding new leadership to enable customer success

Finally, I’m excited to welcome two new leaders to Google Cloud on the Customer Experience team, who will help scale our Delivery Centers and deliver exceptional experiences for our customers.

Heading our Global Delivery Center experience is Sunil Rao. Sunil comes to Google Cloud from Accenture, where he spent 18-plus years working with large technology customers across many industry verticals and managed large global teams in Accenture Advanced Technology Center. Sunil will also lead our Technical Onboarding Center, which helps businesses around the world get up to speed with technologies that are critical to understanding customer and business process contexts, and delivering great experiences.

Additionally, Lee Moore is joining Google Cloud to lead Customer Experience in North America. Lee spent nearly 30 years at Accenture in various leadership positions, including services integration for complex problem-solving, product development across a number of industry verticals, and building long-term customer relationships.

You'll be hearing much more from us in the coming months, as we build out even more powerful and effective cloud-based services and offerings, work with customers to deliver new analytics- and AI-based tools and services, and work with our growing list of partners to help ensure customer success, across the globe.

Mission Critical Services: for the most demanding enterprise environments

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Everything You Need to Know About Customer Experience Research

Updated: January 20, 2023

Published: October 27, 2022

Think back to the last time you received amazing customer service . Remember how it made you feel and how you perceived that business before and after your experience. Compare that experience to the last negative encounter you had with a business, and the difference could not be more obvious.

With recent CX trends such as omni-channel marketing and support, along with the continued growth of e-commerce, it's necessary for companies to understand the customer experience (CX) from multiple angles to reduce pain points and improve customer satisfaction.

CX is not something that your company can just ignore, as nearly half of all customers report that CX is more important to them in 2021 than it was just a year ago. Given this surge in demand for a quality experience, how can your company pivot to meet your customers' rising expectations?

The answer lies in conducting extensive customer experience research. Keep reading to learn everything you need to know about CX research, or use the links below to jump ahead:

What is customer experience research?

Why is customer experience research important, customer experience research tips, customer experience research methods, start conducting your own customer experience research.

Customer experience is the summation of every interaction that a customer has with your company throughout their journey. From a cold call to a service inquiry or a coupon in the mail, each interaction between your company and a customer helps to create individual impressions, perceptions, and behaviors that together make up the customer experience.

Meanwhile, customer experience research represents the actionable steps that your company can take to understand CX. This includes collecting customer data — both pre-and post-sale — and then analyzing that data for trends that can lead to process, product, or service improvements.

Best practices in customer experience research programs include focusing on three core components:

• Development

Image source

Your company's CS research journey starts with a customer experience strategy that lays out your vision of your company's goals and maps out the customer journey as it stands and how you hope it to be.

Once you have a strategy in place, you can then put your ideas into action and develop tools and practices for measuring, organizing, and deciphering the data you'll need to validate any changes you make.

Finally, the research process ends with the tracking and implementation of findings that your company can use as a foundation for continuous improvements to CX design.

Customer Satisfaction vs. Customer Experience

To truly understand CX research, we must first take a moment to differentiate customer experience from customer satisfaction. Although the two terms are often used interchangeably, they are actually quite different and should not be conflated with one another.

Customer satisfaction is a measurement used to gauge how happy a customer is with your company's products, services, or brand overall.

It pays to have happy customers, with 89% of consumers admitting that they are more likely to make an additional purchase after a positive customer service experience.

While customer satisfaction aims to measure how a customer feels about your company — whether good, bad, or neutral — customer experience attempts to measure every interaction that your customers have throughout their entire relationship with your company.

Customer experience research can help you tease out key CX data points and measure your company's success against them. A few of those data points are highlighted in the image below.

All of these metrics and more combine to make up the customer experience. With carefully planned and executed customer experience research, your company can glean insights from these interactions that you can then use to enhance your CX design and raise client satisfaction.

There's nothing worse than losing a customer to a competitor due to a poor experience. Unfortunately, this reality is all too common, with 58% of American consumers reporting that they will switch companies because of a negative customer service experience.

Regardless of the industry, CX is highly correlated with brand loyalty, with the customers reporting the most positive experiences also scoring highest on surveys measuring brand loyalty.

On average, there is a 38% difference in likelihood to recommend a company between customers that rated a company's CX as "good" versus customers that rated that company's CX as "poor."

The ROI of conducting customer experience research is well worth the expense, especially when you stop to consider the alternatives.

After all, it's well known that lead generation is one of the most daunting tasks faced by any company. Yet, at the same time, it costs between 5 and 25 times more to acquire a new customer than to retain an existing one.

It's no wonder that 48% of customer service professionals state that creating a positive customer experience is a top priority for their team.

There are as many methods to conduct customer experience research as there are ways that customers interact with businesses.

Some companies will choose to use deductive reasoning and use commonly held assumptions and perceptions from the market and their customers to map out the customer experience and make changes from there.

On the other hand, other companies will opt to use inductive reasoning and take small sample sets of observable data and use that information to create their CX map and inform their decision-making.

Whatever route your company chooses, it's important to drill down and identify the essential aspects of what you're hoping to gain from this research.

The questions highlighted in the image below are a great place to start.

These questions and more need to be addressed before your company attempts to analyze a shred of evidence. If you skip the planning and strategizing phase of the CX research process, then you're doomed to fail before you begin, because your company won't know what customer experience research questions it's trying to answer.

Once you've settled on your questions, it's time to start organizing the tools and resources you'll need to actually conduct your research.

Customer Experience Research Tools and Resources

Depending on your goals, you may choose to collect qualitative data that provides in-depth CX insights. However, this type of data is not easy to quantify. For example, long-form customer interviews provide a wealth of information about how customers see your CX but the results are difficult to reduce to actionable insights.

Alternatively, your company may decide to focus on measuring and tracking CX key performance indicators and highlight the collection of quantitative data. Surveys are one of the most commonly used mediums to collect quantitative data, as they allow companies to easily sort and organize responses into groups that can be used for statistical analysis and comparison.

Whatever customer experience research method your company chooses, it's essential that leadership is all on the same page to embrace CX research as a key aspect of your business. With as many as 93% of CX initiatives destined to fail, you want to make sure you're doing everything you can to make sure the time you're investing into CX research is well-spent and not just more money down the drain.

Traditionally speaking, most customer experience research was carried out by large marketing research firms that conducted the interviews, focus groups, and surveys that companies used to make changes to their CX design.

Today, the research landscape also includes data collection firms that help companies collate and store their data for easy retrieval and analysis.

That said, many companies also choose to conduct their own research in-house using a variety of research methods for collecting, organizing, and interpreting data.

As shown in the image above, some of the most common methods of collecting CX research data include:

• Feedback Software

Let's discuss each in more detail.

1. Interviews

Interviews provide a wealth of qualitative data, while surveys are highly customizable, allowing your company to tailor its surveys to collect any type of quantitative data. However, these methods are often more time-consuming and labor-intensive than other methods, so are usually conducted by larger organizations with more resources and time.

Two of the most popular surveys are also among the easiest methods of conducting CX research: NPS and CSAT.

Net promoter score (NPS) is a benchmark used to determine how likely a customer is to recommend your business to someone. NPS surveys are useful, as they measure how a customer feels overall about your brand, which allows your company to gather lots of big-picture information.

Then there's customer satisfaction score (CSAT), which measures customer satisfaction with a particular interaction, product, or service. CSAT surveys allow your company to get quantifiable data concerning every little detail of your business that can then be used to design specific solutions.

3. Feedback Software

In addition, many companies now turn to feedback software to help them collect, organize, and track CX data from multiple sources. These applications make it easy for companies to conduct CX research by bringing sophisticated analysis software and technology support all within one system.

Each type of CX method provides valuable information to the table that your company can use to improve the customer experience. Still, you'll need to make sure that you're following CX research best practices to ensure that you get the most out of your efforts.

Customers are no longer willing to settle for a bad shopping experience to get the best price or a superior product.

The new normal requires successful companies to be sensitive to their customers' needs and smooth pain points when and where they emerge. To do this, companies need to invest in CX research that paints a portrait of the customer journey, identifies areas of improvement, and urges leadership to implement actionable changes.

If your company is serious about prioritizing the customer experience, then you need to do the requisite research. That way, you can turn your assumptions into meaningful solutions that let your customers know you care about them.

And we all know there's nothing better than a satisfied customer.

Don't forget to share this post!

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How leading marketers bring teams and technology together to better reach consumers

• Google Marketing Platform

Learn how leading brands are bringing ads and analytics together to make timely connections with customers.

Today’s customers are endlessly curious — and a bit impatient. How do brands connect with them at just the right moment? For today’s successful teams, it comes down to one major factor: timeliness.

Powered by insights from Bain & Company, this guide explores how successful teams are bringing ads and analytics technology together to deliver timely, relevant marketing. Learn how top brands like adidas paired brand and performance teams on Google Marketing Platform to create deeper customer connections — and how Fox used Google Cloud to deliver a box office smash.

Read the guide to discover four organizational strategies that lead to better customer experiences, and learn how they’re paying off for successful brands.

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Customer experience: fundamental premises and implications for research

• Review Paper
• Open access
• Published: 13 January 2020
• Volume 48 , pages 630–648, ( 2020 )

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• Larissa Becker 1 &
• Elina Jaakkola 1  

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Customer experience is a key marketing concept, yet the growing number of studies focused on this topic has led to considerable fragmentation and theoretical confusion. To move the field forward, this article develops a set of fundamental premises that reconcile contradictions in research on customer experience and provide integrative guideposts for future research. A systematic review of 136 articles identifies eight literature fields that address customer experience. The article then compares the phenomena and metatheoretical assumptions prevalent in each field to establish a dual classification of research traditions that study customer experience as responses to either (1) managerial stimuli or (2) consumption processes. By analyzing the compatibility of these research traditions through a metatheoretical lens, this investigation derives four fundamental premises of customer experience that are generalizable across settings and contexts. These premises advance the conceptual development of customer experience by defining its core conceptual domain and providing guidelines for further research.

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For the past decade, customer experience has enjoyed remarkable attention in both marketing research and practice. Business leaders believe customer experience is central to firm competitiveness (McCall 2015 ), and marketing scholars call it the fundamental basis for marketing management (Homburg et al. 2015 ; Lemon and Verhoef 2016 ). Such attention has also prompted calls for research (e.g., Ostrom et al. 2015 ) and special issues devoted to customer experience, with a resulting dramatic increase in academic publications pertaining to this concept across many different literature fields and significant advances in scholarly understanding.

Yet this trend has also produced considerable fragmentation and theoretical confusion. No common understanding exists regarding what customer experience entails. Some studies assert that customer experience reflects the offerings that firms stage and manage (Pine and Gilmore 1998 ), but others define it as customer responses to firm-related contact (Homburg et al. 2015 ; Lemon and Verhoef 2016 ; Meyer and Schwager 2007 ). The concept has been used to describe anything from extraordinary (Arnould and Price 1993 ) to mundane (Carú and Cova 2003 ) experiences. Some researchers delimit the scope of customer experience to a particular context, such as service encounters (Kumar et al. 2014 ) or retail settings (Verhoef et al. 2009 ), and others view it more broadly as emerging in customers’ lifeworlds (Chandler and Lusch 2015 ; Heinonen et al. 2010 ).

The lack of a unified view creates considerable challenges for theory development (Chaney et al. 2018 ; Kranzbühler et al. 2018 ). The diverse conceptualizations of customer experience mean that its operationalization differs from study to study, creating measurement and validity concerns. Confusion also prevails about the scope and boundaries of the customer experience construct, its antecedents, and its consequents. Researchers have difficulty defining which insights they can combine, thus limiting replication and generalization across contexts. These challenges also hinder researchers’ ability to disseminate meaningful implications for managers seeking to foster superior customer experience.

To mitigate these challenges and move the field toward a more unified customer experience theory, an integrative understanding is needed. With this article, we seek to develop a set of fundamental premises that reconcile contradictions and dilemmas in the current customer experience literature and provide integrative guideposts for future research in the field . As integrating such fragmented research requires understanding the distance between the phenomena addressed by different studies as well as the degree of compatibility in their underlying assumptions (Okhuysen and Bonardi 2011 ), we pose two research questions to guide our efforts: (1) What is the nature of the customer experience phenomenon and the underlying metatheoretical assumptions adopted in literature that addresses customer experience? (2) What are the common elements of customer experience that are applicable across contexts and literature fields?

To address these questions, we started with a systematic literature review to identify customer experience research in eight key literature fields: services marketing, consumer research, retailing, service-dominant (S-D) logic, service design, online marketing, branding, and experiential marketing. We then analyzed the compatibility of these fields with a metatheoretical approach, which supports comparisons across fragmented, scattered literature pertaining to a particular concept (Gioia and Pitre 1990 ; Möller 2013 ). On the basis of this comparison, we integrated these eight fields into two higher-order research traditions, defined by their approach to customer experience as either (1) responses to managerial stimuli or (2) responses to consumption processes. Through these analyses, we explicate the underlying assumptions of each research tradition and also provide a state-of-the-art description of how customer experience has been studied so far.

Furthermore, we identify commensurable elements that are applicable to both research traditions and across contexts to define four fundamental premises of customer experience that provide solutions to problems in the current research on this concept. These premises provide an integrative definition of customer experience, reveal a multilevel and dynamic view of the customer journey, highlight contingencies for customer experience, and determine the role of the firms in influencing customer experience. Each fundamental premise offers guidelines for future research as well as managerial practice. Our delineation of the conceptual domain of customer experience advances research by reconciling contradictions found in the literature and bridging different research fields and traditions, allowing them to speak the same language, and offering a more comprehensive view of the phenomenon (MacInnis 2011 ). This view complements existing reviews of customer experience (Table 1 ) that tend to focus on narrowly selected sets of articles, that seldom consider the metatheoretical underpinnings of the reviewed studies, and that do not integrate the dispersed studies. The fundamental premises proposed herein can support more rigorous studies, whose results will have more meaningful implications for firms.

The next section presents our research approach, followed by the results of the metatheoretical analysis, including a description of the key phenomena and metatheoretical assumptions embodied in each literature field, as well as a derived theoretical map of customer experience in marketing. Subsequently, we develop four fundamental premises of customer experience by integrating compatible assumptions across research traditions. In the conclusion, we detail the theoretical contributions and managerial implications of this study, as well as its limitations.

Research approach

Developing an integrative view of customer experience requires organizing the scattered literature into groups and analyzing their compatibility (MacInnis 2011 ). This analysis involved three phases: (1) a systematic literature review of customer experience that groups individual studies into eight distinct literature fields, (2) organization of the eight literature fields into two distinct research traditions on the basis of the customer experience phenomena addressed and the underlying metatheoretical assumptions adopted, and (3) forming an integrated view of customer experience by building on the compatible elements across research traditions.

Phase 1: identifying and grouping relevant customer experience research

We conducted a systematic literature review to select relevant articles that study customer experience in marketing, according to strict guidelines (e.g., Booth et al. 2012 ; Palmatier et al. 2018 ). A systematic literature review enables overcoming possible biases in comparison to traditional reviews because it uses explicit criteria and procedures for selecting and including articles in the sample (e.g., Littell et al. 2008 ). We identified 142 articles that we subjected to a two-step process: identification of literature fields and classification of the articles (see Appendix 1 ).

We started with four literature fields—S-D logic, consumer research, services marketing, and service design—that were previously identified as relevant domains for customer experience research (Jaakkola et al. 2015 ). When the articles did not fit these fields in terms of their primary research foci (the aspects of customer experience studied), we added a new category, ultimately resulting in four additional literature fields: retailing, online marketing, branding, and experiential marketing. For example, branding emerged as a clearly distinct field that focuses on brand stimuli, such as logo and packaging (e.g., Brakus et al. 2009 ).

We then classified the articles into these literature fields according to three criteria: the primary customer experience stimuli studied, the customer experience context, and the key references used to define customer experience (e.g., citing Arnould and Price ( 1993 ) to substantiate the definition of customer experience indicates an article is likely to belong to the literature field of consumer research) (Table 2 ).

To be classified into a specific literature field, an article had to meet at least two of these three criteria without considerable overlap between fields. We excluded 12 articles that did not fulfill these criteria. However, we added 6 additional papers, identified through a bibliography search (i.e., back-tracking) (Booth et al. 2012 ; Johnston et al. 2018 ), resulting in a total sample of 136 articles (see Web Appendix ). The iterative process of reading the articles, identifying the literature fields, and classifying the articles stopped when we reached theoretical saturation (i.e., the majority of articles could clearly be categorized in one of the fields).

Phase 2: Analyzing the nature of the customer experience phenomena and metatheoretical assumptions in the literature fields

Following Okhuysen and Bonardi ( 2011 ), we analyzed these eight literature fields in terms of the focal phenomena addressed and the ontological, epistemological, and methodological assumptions adopted (Table 3 ) (see Appendix 2 for a more detailed account of the analysis). Using these elements, we compared the literature fields and sought to identify broader groups. By situating the eight literature fields in a theoretical map, we could navigate across them and develop conclusions about their compatibility (Gioia and Pitre 1990 ; Möller 2013 ; Okhuysen and Bonardi 2011 ). In turn, we identified two distinct research traditions that encompass all eight literature fields.

Phase 3: Developing an integrated view of customer experience

To integrate the two research traditions, we used a method analogous to triangulation (Gioia and Pitre 1990 ). By juxtaposing the two research traditions from a metatheoretical perspective, we sought to identify customer experience elements that are common to the two traditions, distinct yet compatible elements, and unique elements that do not fit with the assumptions from the other research tradition (Gioia and Pitre 1990 ; Lewis and Grimes 1999 ). The integration of compatible elements resulted in the development of four fundamental premises of customer experience.

Results of the metatheoretical analysis

In this section, we first describe the nature of the phenomena addressed and the metatheoretical assumptions adopted in the customer experience literature. We then position each literature field on a theoretical map of customer experience to establish two higher-order research traditions.

Customer experience phenomena and metatheoretical assumptions in the literature fields

Table 4 presents the description of the key customer experience phenomena addressed and the metatheoretical assumptions adopted in the eight identified literature fields. A discussion on the similarities and contradictions between them follows (cf. Möller 2013 ; Okhuysen and Bonardi 2011 ).

Customer experience phenomena addressed

As Table 4 shows, there are considerable differences between the literature fields with regard to the scope and nature of customer experience as a research phenomenon. The literature on experiential marketing tends to view experience as the offering itself. However, the most prevalent view within other fields sees customer experience as a customer’s reactions and responses to particular stimuli. Some studies focus on customer responses to stimuli residing within the firm–customer interface , with the goal of understanding how firms can use different types of stimuli to improve customers’ responses along their customer journey, the series of firm- or offering related touchpoints that customers interact with during their purchase process (e.g., Patrício et al. 2011 ). For example, services marketing focuses on service encounter stimuli, such as the servicescape, employee interactions, the core service, and other customers (e.g., Grace and O’Cass 2004 ), the retailing literature focuses on retail elements, such as assortment and price (e.g., Verhoef et al. 2009 ), and online marketing focuses on the elements of the virtual environment (e.g., Rose et al. 2012 ).

In contrast, S-D logic and consumer research consider stimuli related to the customer’s overall consumption process , encompassing factors beyond dyadic firm–customer interactions (e.g., Chandler and Lusch 2015 ; Woodward and Holbrook 2013 ). These studies consider customer experience to also emerge through non-market-related processes (e.g., eating dinner at home; Carú and Cova 2003 ), affected by a range of stakeholders such as customer collectives (Carú and Cova 2015 ) and even institutional arrangements such as norms, rules, and socio-historical structures (e.g., Akaka and Vargo 2015 ).

Metatheoretical assumptions

In terms of the ontological, epistemological, and methodological assumptions present in the customer experience literature, our analysis reveals some clear divides (Table 4 ). On a general level, services marketing, retailing, service design, online marketing, branding, and experiential marketing assume that particular stimuli likely trigger a certain response from customers. Thus, their view resonates with the idea of an objective, external, concrete reality (Burrell and Morgan 1979 ). Researchers employ hypothetic–deductive reasoning to study the relationship between customer experience and other variables, typically with surveys and experiments (e.g., Srivastava and Kaul 2016 ). In theoretical models, contextual factors usually appear as moderating variables (e.g., Verhoef et al. 2009 ). These fields hence tend to adopt a positivist epistemological approach, seeking to explain an external, concrete reality by searching for regularities and causal relationships in an objective way (Burrell and Morgan 1979 ).

In contrast, consumer research and S-D logic take a subjective view and adopt an interpretive epistemology. Research in these fields sees the customer experience as embedded in each customer’s lifeworld and interpreted by that customer (Helkkula and Kelleher 2010 ). External reality does not exist but instead serves only to describe the subjective reality, which is a product of individual consciousness (Burrell and Morgan 1979 ; Tadajewski 2004 ). Neither S-D logic nor consumer research aims to generate universal, generalizable laws; instead, they seek to understand how customers in their unique situation experience an object (Addis and Holbrook 2001 ). Therefore, these researchers consider customer subjectivity, highlight the role of contextual factors, and prefer qualitative methods (e.g., ethnography, phenomenological interviews) (Schembri 2009 ). Most consumer research studies employ an interpretive and inductive approach that is used to capture the symbolic meaning of consumption experiences (Holbrook 2006 ). In S-D logic, empirical studies often adopt a phenomenological approach, aiming to understand how value emerges during service use in the customer’s context (Helkkula and Kelleher 2010 ).

Theoretical map of the customer experience in marketing

The preceding discussion highlights that the scope of the customer experience phenomena addressed in the research ranges from narrow and dyadic to a broader ecosystem view. In terms of metatheoretical assumptions, we identify a continuum from more positivist to more interpretive approaches. Footnote 1 Our comparisons of these elements produced a theoretical map of customer experience where we group the eight literature fields into two higher-order research traditions (Fig.  1 ), which we define as groups of studies that share general assumptions about the research domain (Laudan 1977 ; Möller 2013 ).

Theoretical map of customer experience

The first research tradition combines experiential marketing, services marketing, online marketing, retailing, branding, and service design. These fields view customer experience as responses and reactions to managerial stimuli . As noted, each literature field addresses different stimuli; for example, brand-related stimuli include packaging, advertising, and logos (Brakus et al. 2009 ), whereas retailing elements include price, merchandise, and store facilities (Verhoef et al. 2009 ). The general goal across this research tradition is to examine how firms can affect customer experience by managing different types of stimuli, typically focusing on firm-controlled touchpoints. To test these relationships, researchers usually adopt a positivist philosophical positioning.

The second research tradition comprises consumer research and S-D logic that view customer experience as responses and reactions to consumption processes . This tradition adopts a broad view on experience as it addresses any stimuli during the entire consumption process, potentially involving many firms, customers, and stakeholders, all of which can contribute to the customer experience but are not necessarily under the firm’s control. Research following this tradition tends to see customer experience as embedded in a customer’s lifeworld and interpreted by the customer, such that it reflects an interpretive philosophical positioning (e.g., phenomenology). Finally, service design lies at the intersection of the two research traditions as it is inherently managerially focused but recent studies increasingly incorporate a more systemic view of stimuli for customer experience.

By building on the common elements across traditions and reconciling the distinct but compatible elements, we next develop fundamental premises of customer experience that provide opportunities to extend research within both traditions.

Fundamental premises of customer experience

Many authors highlight the need to build bridges across research traditions to establish a comprehensive understanding of a research domain (e.g., Gioia and Pitre 1990 ; Lewis and Grimes 1999 ; Okhuysen and Bonardi 2011 ). The pivotal question for developing a more unified customer experience theory is: To what extent can the literature from these two traditions be combined?

Our analysis revealed two research traditions that differ in terms of their metatheoretical assumptions, affecting how customer experience is understood and studied. A juxtaposition of these research traditions allows us to identify common elements, distinct yet compatible elements, as well as elements that are incompatible. From this analysis we developed four fundamental premises of customer experience that build on the shared assumptions and help in solving the key discrepancies in the extant literature. These premises may generalize across settings, allowing each research tradition to offer complementary results that collectively provide a comprehensive understanding of the same phenomena (cf. Gioia and Pitre 1990 ). Together, these premises (P1-P4) cover the “big picture” of what customer experience is, what affects it, its key contingencies, and the role that firms can play in it (Fig.  2 ). For each of these premises, we delineate guidelines for future research to move the field forward.

Conceptual framework for customer experience

Definition of customer experience

The metatheoretical analysis conducted revealed a myriad of definitions for customer experience that ultimately suggest different phenomena (see Table 4 ). The current literature on customer experience does not agree on the definition of customer experience nor on its nomological network. Confusion prevails as to whether experience is response to an offering (e.g., Meyer and Schwager 2007 ) or assessment of the quality of the offering (e.g., Kumar et al. 2014 ). This means that in some studies, customer experience overlaps with outcome variables such as satisfaction or value, while in others it is an independent variable leading to satisfaction, for example. Furthermore, some studies view experience as a characteristic of the product rather than as the customer’s response to it (e.g., Pine and Gilmore 1998 ), which is in deep conflict with the interpretive tradition that always views experience as a subjective perception by an individual and even as synonymous with value-in-use (Addis and Holbrook 2001 ).

To resolve this confusion, we suggest customer experience should be defined as non-deliberate, spontaneous responses and reactions to particular stimuli. This view builds on the most prevalent definition across the two research traditions, but separates customer experience from the stimuli that customers react to as well as from conscious evaluation that follows from it. This view rejects suggestions that evaluative concepts such as satisfaction or perceived service quality could be a component of customer experience (Lemon and Verhoef 2016 ).

Another conceptual confusion in the extant literature relates to assumptions held regarding the nature of experiences. As Carú and Cova ( 2003 ) note, much of the marketing research assumes that good experiences are “memorable,” if not “extraordinary.” The extant research tends to treat ordinary and extraordinary experiences as different phenomena (e.g., Arnould and Price 1993 ; Klaus and Maklan 2011 ). However, these studies typically focus on the extraordinary or ordinary nature of the offering, such as river rafting or experiential events (Arnould and Price 1993 ; Schouten et al. 2007 ) or routine and mundane offerings (Carú and Cova 2003 ), rather than on the customer’s response to these stimuli. As customer responses can range from weak to strong (Brakus et al. 2009 ), we propose this intensity better marks the difference between an ordinary and extraordinary customer experience. It follows that this classification can be leveraged as a continuum instead of a dichotomy; the weaker the customer responses and reactions, the more ordinary the experience, and vice versa (cf. Carú and Cova 2003 ). A customer can thus have an extraordinary experience as a response to a mundane offering.

In sum, to reconcile confusion in the extant research, we propose the following:

Premise 1a:

Customer experience comprises customers’ non-deliberate, spontaneous responses and reactions to offering-related stimuli along the customer journey .

Premise 1b:

Customer experience ranges from ordinary to extraordinary representing the intensity of customer responses to stimuli.

Implications of Premise 1 for future research

Following Premise 1a, researchers should distinguish customer experience from stimuli (e.g., the offering) and evaluative outcomes (e.g., value-in-use). For example, when operationalizing customer experience, researchers should not build on evaluative scales or use satisfaction and service quality as proxies, as is currently often done (see, e.g., Kumar et al. 2014 ; Ngobo 2005 ). Instead, the operationalization of customer experience should focus on the customer’s spontaneous responses and reactions to offering-related stimuli. The current customer experience literature offers a few solid measures that can serve as a starting point for further development (e.g., Brakus et al. 2009 ; Ding and Tseng 2015 ). We recommend building the measures on the most common experience dimensions used in the extant research—cognitive, affective, physical, sensorial, and social responses (e.g., Lemon and Verhoef 2016 ; Schmitt 1999 ; Verhoef et al. 2009 )—to facilitate the accumulation of knowledge and eventually enable comparing the weight of each type of response across different contexts. The extant research implies that the relevance of different types of customer responses may vary across contexts (McColl-Kennedy et al. 2017 ), but a lack of a common definition and measures for customer experience has prevented building this knowledge effectively.

Defining customer experience as spontaneous responses and reactions suggests that the issue of timing is relevant for its measurement. According to our literature review, most studies use research instruments where the respondents have to rely on memory to report their experience (e.g., Trudeau and Shobeiri 2016 ). To improve the validity of the findings, we recommend research designs where customer responses are captured right after the interaction with the offering-related stimuli has taken place. Some methods and technologies for capturing customers’ reactions in real time have been developed, such as the real time experience tracking method (Baxendale et al. 2015 ) and wearable devices for emotion detection (Jerauld 2015 ). Surprisingly, none of the 136 studies in our review used such technology to investigate customer experience in real time. Future studies should further explore the applicability and consumer acceptance of such methods and technologies.

Following Premise 1b, researchers should also change the way they address extraordinary vs. ordinary experiences. The current literature tends to assume that the higher the score on a customer experience scale, the better the customer experience is (e.g., Brakus et al. 2009 ). Future studies should address contexts where ordinary experiences (i.e., weak or neutral responses) are desirable in order to complement current research that predominantly focuses on contexts where firms try to strengthen customers’ responses rather than to keep them to a minimum (e.g., Ding and Tseng 2015 ). Such studies would help firms in designing customer journeys that, at some points, minimize certain types of responses, while increasing particular responses at other times.

Stimuli affecting customer experience

Delineating the conceptual domain of customer experience also requires defining the stimuli that affect its formation. Key discrepancies in the current literature relate to the source of the stimuli considered and the level of analysis. Our review revealed that most studies focus on a particular set of firm-controlled touchpoints and an integrative view is missing. This is problematic in many respects: customer journeys in today’s markets are “multitouch” and multichannel in nature with new types of stimuli emerging every day, suggesting that firms need to understand a broad range of touchpoints within and outside firm control, both in offline and online settings (Bolton et al. 2018 ; Lemon and Verhoef 2016 ). Furthermore, empowered customers are increasingly in charge of selecting individual pathways to achieve their goals (Edelman and Singer 2015 ; Heinonen et al. 2010 ; Teixeira et al. 2012 ). This means that journeys become increasingly complex and individualized, and the current literature silos focusing on a selected set of stimuli and touchpoints will fail to capture what the customer really experiences. The literature fields that consider customers’ holistic experiences in their lifeworld take a broader view but lack precision and insight into how experiences related to particular offerings emerge.

To resolve this dilemma, we propose integrating the currently disparate perspectives into a multilevel framework that draws on different fields of the customer experience literature and considers the stimuli at multiple levels of aggregation: First, cues refer to anything that can be perceived or sensed by the customer as the smallest stimulus unit with an influence on customer experience, such as product packing and logo design (Bolton et al. 2014 ; Brakus et al. 2009 ). Second, touchpoints reflect the moments when the customer interacts with or “touches” the offering (Patrício et al. 2011 ; Verhoef et al. 2009 ). These contact points can be direct (e.g., physical service encounters) or indirect (e.g., advertising) and comprise various cues (Meyer and Schwager 2007 ). Third, the customer journey comprises a series of touchpoints across the stages before, during, and after service provision (Lemon and Verhoef 2016 ; Teixeira et al. 2012 ). Fourth, the consumer journey level captures what customers do in their daily lives to achieve their goals, implying a broader focus than that of the customer journey and accommodating consumer interaction with multiple stakeholders beyond touchpoints with a single firm (Epp and Price 2011 ; Hamilton and Price 2019 ; Heinonen et al. 2010 ).

The extant literature has tended to measure customer experience either in one touchpoint or as an aggregate evaluation of the brand. However, recent research indicates a need for a more dynamic view: Kranzbühler et al. ( 2018 ) argue that customer experience is based on an evolving evaluation of a series of touchpoints, Bolton et al. ( 2014 ) suggest that some stimuli have multiplier effects, and Kuehnl et al. ( 2019 ) state that the connectivity of stimuli across touchpoints is an important driver for positive customer outcomes. These findings suggest that customer experience emerges in a dynamic manner and benefits from a multilevel analysis.

We present Premise 2 that addresses these shortcomings in the existing research and integrates insights across research traditions:

Premise 2a:

Customer experience stimuli reside within and outside firm-controlled touchpoints and can be viewed from multiple levels of aggregation.

Premise 2b:

Customer experience stimuli and their interconnections affect customer experience in a dynamic manner.

Implications of Premise 2 for future research

Premise 2 guides future research to study diverse offering-related stimuli through multiple levels of aggregation. Most of the reviewed research has examined a narrow scope of stimuli and touchpoints (e.g., Grace and O’Cass 2004 ) and a lack of insight into touchpoints beyond firm control is particularly glaring. We recommend cross-fertilization between the two research traditions: Researchers within the managerial research tradition could expand their research foci by drawing from consumption process studies that offer a broad outlook on the various stakeholders contributing stimuli that affect customer experience (e.g., Akaka and Vargo 2015 ; McColl-Kennedy et al. 2015 ). The research tradition focusing on experience as responses to consumption processes could adopt the more detailed analysis on journey composition offered by the managerial tradition and “zoom in” on the journey, focusing on the meanings that emerge at specific touchpoints, for example.

As extant studies often focus on measuring customer experience on the cue or touchpoint level (e.g., Grace and O’Cass 2004 ), the literature is unclear about how the interplay of diverse stimuli affect customer experience. Future research should thus study the interaction between types of stimuli and their dynamic effect on customer experience. Longitudinal research designs would be particularly useful for creating new insight into the evolving effects of stimuli configurations for the formation of customer experience as well as the interaction between the types of customer responses at different touchpoints. In addition, future research could investigate how the combination of responses and reactions that emerge over time lead to evaluative outcomes such as satisfaction.

The effective study on the emergence of customer experience necessitates the development of more dynamic measurement instruments. Current measures of customer experience often only provide a snapshot (e.g., Brakus et al. 2009 ; Ding and Tseng 2015 ). Considering the multitude of potential relevant customer experience stimuli and the active role of customers in forming their own journey (Edelman and Singer 2015 ; Heinonen et al. 2010 ), a possible avenue for research would be the development of self-adaptive scales or surveys where respondents can self-select parts of the journey that they found relevant and the types of responses they experienced. Research supporting the development of such instruments is available (e.g., Calinescu et al. 2013 ) but has not as yet been applied in the customer experience context. While a measurement instrument that captures a complete multilevel framework of the customer journey would become unmanageable, a self-adaptive scale would allow respondents to focus on touchpoints and even on specific cues that are the most relevant for the customer experience. A more dynamic measurement of customer experience would also enable analyzing what types of customer responses emerge in different touchpoints or phases of the customer journey.

Key contingencies for customer experience

Researchers generally agree that customer experience is subjective and specific to the context. This means that contextual variables related to the customer and the broader environment influence customer responses to stimuli and evaluative outcomes of customer experience. However, the current research on these contingencies is fragmented and lacks a uniform view. Within the managerial research tradition, the role of contextual variables is rather peripheral. These studies often investigate a limited number of contextual variables or dismiss their effect altogether. Some typical contextual variables that are studied include consumer attitudes, task orientation, and socio-demographic variables (e.g., Ngobo 2005 ; Verhoef et al. 2009 ). The research tradition that views customer experience as responses to consumption processes places a greater emphasis on the customer context, acknowledging the role of complementary offerings and service providers, institutions and institutional arrangements, and the customer’s goals in the consumption situation (Akaka and Vargo 2015 ; Tax et al. 2013 ; Woodward and Holbrook 2013 ).

Again, insights across research traditions have seldom been combined. To reconcile this shortcoming, we categorize the contingencies used in the extant studies and identify the key ways in which they operate. Our literature review enabled the identification of three groups: (1) customer, (2) situational, and (3) sociocultural contingencies. Customer contingencies refer to the customer’s characteristics such as personality, values, and socio-demographic characters (e.g., Holbrook and Hirschman 1982 ), resources such as time, skills, and knowledge (e.g., Novak et al. 2000 ), past experiences and expectations (e.g., Verhoef et al. 2009 ), customer participation and activities during the journey (e.g., Patrício et al. 2008 ), motivations (e.g., Evanschitzky et al. 2014 ), and the fit of the offering with the customer’s lifeworld (e.g., Schmitt 1999 ).

Situational contingencies are those related to the immediate context, such as the type of store the customer is interacting with (e.g., Lemke et al. 2011 ), the presence of other customers and companions (e.g., Grove and Fisk 1992 ; Schouten et al. 2007 ), and other stakeholders that contribute to the customer experience, such as other firms (e.g., Tax et al. 2013 ). Sociocultural contingencies refer to the broader system in which customers are embedded, such as language, practices, meanings (e.g., Schembri 2009 ), cultural aspects (e.g., Evanschitzky et al. 2014 ), and societal norms and rules (e.g., Akaka and Vargo 2015 ; Åkesson et al. 2014 ).

Our literature review indicates that these contingency factors can affect the customer experience through two alternative routes. First, these factors can make some stimuli more or less recognizable; in other words, they play the role of a moderator between offering-related stimuli and customer experience (Jüttner et al. 2013 ). Second, such contingencies can affect the evaluative outcomes of particular customer responses (Heinonen et al. 2010 ). For example, a feeling of fear can have negative effects in a dentist’s office, but in a context such as river rafting, that response may have positive implications (Arnould and Price 1993 ). Therefore, any particular response to offering-related stimuli is not “universally good” or “universally bad”; its evaluation instead depends on its fit with the customer’s processes and goals.

Altogether, this discussion organizes the fragmented literature around contingencies for customer experience, as summarized in Premise 3:

Customer experience is subjective and context-specific, because responses to offering-related stimuli and their evaluative outcomes depend on customer, situational, and sociocultural contingencies.

Implications of Premise 3 for future research

While the extant literature agrees on the subjective nature of experiences and recommends that managers ensure their customer experience stimuli have a good fit with the customer’s situational context (e.g., Homburg et al. 2015 ; Kuehnl et al. 2019 ), it does not offer much guidance on the identification and role of key contingencies for customer experience. More systematic research is thus needed on the relevant contextual variables and their effects on the strength and direction of the relationships between offering-related stimuli, customer experience, and evaluative outcomes. The extant empirical research has addressed a relatively narrow set of contextual contingencies, and new insights can be generated, for example, by drawing from research within the interpretative research tradition that has placed a strong emphasis on sociocultural factors beyond the firm–customer interface (e.g., Akaka and Vargo 2015 ; Åkesson et al. 2014 ). In particular, researchers could study the role of institutions and institutional arrangements, as they direct the customer’s attention to particular stimuli in the environment (Thornton et al. 2012 ), but are seldom studied as contingency factors in empirical research on customer experience. Future research could look beyond customer experience research to identify potentially relevant contingencies for customer experience formation.

Customer experience research is often preoccupied with the question of how to provide “good experiences,” simply assuming that higher scores on a customer experience scale are always better (e.g., Ding and Tseng 2015 ). As Premise 3 suggests, it is more relevant to ask for whom a particular experience is good . Future studies should aim to identify relevant key contingences that drive particular customer responses to stimuli and influence a customer’s evaluation of their responses. This insight will aid managers in developing a more individualized set of offering-related stimuli for their different target groups and user personas, which is deemed important in current markets (Edelman and Singer 2015 ).

Role of the firm in customer experience

The fourth premise seeks to settle a seemingly profound discrepancy between the two research traditions: Can firms manage the customer experience? Some studies refer to the customer experience as something created and offered to customers (e.g., Hamilton and Wagner 2014 ; Pine and Gilmore 1998 ), but others emphasize its emergence in customers’ lifeworlds and suggest it cannot be managed directly (Heinonen et al. 2010 ; Helkkula and Kelleher 2010 ). This discrepancy can be solved by building on the common ground of the two research traditions that sees customer experience emerging as customer responses to diverse stimuli. As firms cannot control customer responses, they cannot create the customer experience per se, but they can seek to affect the stimuli to which customers respond.

Studies within the managerial tradition provide guidance on designing and integrating stimuli in firm-controlled touchpoints to ensure positive customer experience (e.g., Brakus et al. 2009 ; Grace and O’Cass 2004 ; Pine and Gilmore 1998 ). Although this research tradition acknowledges that touchpoints outside the firm’s control (e.g., other customers) might greatly influence customer experience (e.g., Grove and Fisk 1992 ), it says very little about what firms can do regarding these stimuli.

Studies that view customer experience as responses to consumption processes offer some guidelines for addressing the uncontrollable touchpoints. For example, Carú and Cova ( 2015 ) advise firms to monitor and react to customers’ collective practices with other consumers. Tax et al. ( 2013 ) suggest that firms should identify other firms that are part of the consumer journey, then partner with these organizations to improve the overall customer experience. Some authors suggest that firms should try to identify all stakeholders that influence the customer journey (e.g., Patrício et al. 2011 ; Teixeira et al. 2012 ). Mapping offering-related stimuli as holistically as possible helps firms design offerings that better fit into customers’ lives (Heinonen et al. 2010 ; Patrício et al. 2011 ). Thus, firms can use their knowledge of external stimuli and contextual factors to their advantage, even though they cannot control such factors.

In sum, to reconcile the disparate streams of extant research, we propose the following:

Firms cannot create the customer experience, but they can monitor, design, and manage a range of stimuli that affect such experiences.

Implications of Premise 4 for future research

Only few attempts have been made to delineate what customer experience management entails (e.g., Homburg et al. 2015 ), and this topic remains insufficiently understood despite its practical relevance. The extant research offers some guidelines for “well-designed journeys” (e.g., Kuehnl et al. 2019 ), but more research is needed to specify management activities that are suited to different types of touchpoints.

According to our literature review, a particularly critical gap in extant knowledge relates to the firm’s possibilities of affecting touchpoints outside of the firm’s control. Service design research offers tools for mapping a broader constellation of touchpoints, but there is scant research on how firms can deal with touchpoints external to the firm–customer interface. Potential future research topics include, for example, how firms can design touchpoints that are adaptive to stimuli residing in external touchpoints and whether firms can influence how customers respond to stimuli at external touchpoints along their journey.

We recommend that future research should ground customer experience management models on a more nuanced conceptual understanding of experience. These models should not consider “good experience” as the goal of customer experience management, but instead define the content of the intended customer experience (cf. Premise 1). In our sample, only a few studies address the specific responses and reactions that firms want to trigger: For example, Bolton et al. ( 2014 ) show three types of intended experiences (e.g., emotionally engaged experiences) and give suggestions on how to trigger them. By focusing on the “good vs. bad” dichotomy of customer experience, studies about customer experience management seem to skip this important step and focus directly on the stimuli to which customers respond (cf. e.g., Lemke et al. 2011 ). A focus on intended responses and reactions would complement this research and provide more precise implications on the management of firm-controlled stimuli.

Another critical gap in the research knowledge on customer experience management relates to the issue of contextual factors. The effect of managerial action depends on how well it resonates with the customers, their situation, and sociocultural context (Heinonen et al. 2010 ); hence, insights into the environment where customers interact with the offering-related stimuli are critical. The extant knowledge on the relevance and fit of particular management activities with particular contexts, situations, and types of customers is very scarce. For example, future research could explore how customer contingencies for customer experience formation (see Premise 3) can be used in segmentation and how management processes should be adapted to ensure the desired effects.

Table 5 summarizes the developed premises that conceptualize customer experience as well as guidelines and suggestions for future research.

Conclusions

Theoretical contributions.

This study undertakes a rigorous development of an integrative view of customer experience, captured in four fundamental premises that can anchor future customer experience research. We highlight four specific conceptual contributions. First, this study differentiates the customer experience concept and the bodies of research that study it (MacInnis 2011 ) (Table 4 ). Then it defines two distinct research traditions that study customer experience: customer experience as responses to managerial stimuli and customer experience as responses to consumption processes (Fig. 1 ). This differentiation facilitates comparisons across research streams and creates the conditions for their integration (MacInnis 2011 ). The metatheoretical analysis makes different assumptions underpinning customer experience research visible and articulates the key differences between literature fields and research traditions, providing a state-of-the-art description of research in the customer experience domain (cf. Palmatier et al. 2018 ). This helps researchers make sense of the conflicting research findings in the previous literature, position their research, and take note of the conceptual boundaries of their chosen literature field.

Second, we integrate the customer experience literature and draw connections among entities, then provide a simplified, higher-order synthesis that accommodates this knowledge (MacInnis 2011 ). Specifically, our analysis provides four fundamental premises of customer experience that integrate common and distinct yet compatible elements across the previously distinct bodies of research, solving key conflicts in the existing research (Table 5 ). Previous literature reviews (Table 1 ) have highlighted differences across customer experience characterizations (Helkkula 2011 ), contextual lenses (Lipkin 2016 ), and theoretical perspectives (Kranzbühler et al. 2018 ), but our study is unique in that it seeks to transcend these individual differences and reconcile the disparate literature. The integration of extant knowledge in a conceptual domain is an important step for advancing science (Palmatier et al. 2018 ); it is particularly valuable for the fragmented customer experience domain hosting a great variety of definitions, dimensions, and analysis levels that create considerable challenges for researchers and hamper the conceptual advancement of the field (Chaney et al. 2018 ; Kranzbühler et al. 2018 ; McColl-Kennedy et al. 2015 ).

Third, the fundamental premises we propose delineate the customer experience concept; they “describe an entity and identify things that should be considered in its study” (MacInnis 2011 , p. 144). The proposed premises serve to reconcile and extend the research domain, as well as resolve definitional ambiguities (Palmatier et al. 2018 ), by delineating what customer experience is, what it is not, how it emerges, and to what extent it can be managed. We argue that the four premises establish the core of the conceptual domain of customer experience and are generalizable across settings and contexts. Few, if any, earlier studies have offered general guidelines for the rapidly growing field of customer experience research, let alone such that are based on a systematic, theoretical analysis of the body of experience research.

Fourth, this paper provides clear guidelines and implications for continued research on customer experience (Table 5 ). Each premise explicates the constituents and boundaries of the customer experience concept and what they mean for its study. We also explicate how researchers within each research tradition can enrich their studies by learning from previously somewhat overlooked experience research conducted within the other tradition.

Applying the premises developed in this study in continued research should facilitate the advancement of science and the generalization of the findings by enabling the different fields and research traditions to speak the same language and establish a more complete view of the conceptual domain. Naturally, customer experience researchers from various fields will continue to hold different assumptions about the nature of reality and how customer experience should be studied; however, these differences should not mean that the concept of customer experience means different things in the marketing literature. The integrative understanding offered in this study is the needed step toward the development of a more unified customer experience theory.

Managerial implications

A better delineation and integration of customer experience research also benefits managerial practice. We determine that customer experience comprises many types of customer responses and reactions that can vary in nature and strength (Premise 1). Instead of just seeking to create “positive” or “memorable” customer experiences, firms should define their intended customer experience with finer nuances. Depending on their value proposition, firms can determine which customer responses and reactions they hope to trigger. For some firms, a weak or mitigated response will be preferable for some touchpoints, such as a hassle-free cleaning service that the customer does not need to think about, or a dentist’s office that reduces excitement and fear. Other value propositions may aim to trigger strong, extraordinary emotional or sensorial experiences, as in the case of an amusement park (Zomerdijk and Voss 2010 ). Firms should thus develop unique customer experience measures to capture different types of customer responses. Using perceived quality or customer satisfaction as proxies to measure customer experience limits the understanding of the true nature of the customer experience that the offering evokes.

After establishing the intended customer experience, firms should map the consumer journey to identify which offering-related stimuli are likely to influence these customer responses and reactions. We propose an integrated view of versatile sources of stimuli along this journey, which is broader than what any single literature field can provide. A useful starting point would be to analyze offering-related stimuli at multiple levels of aggregation (Premise 2). Firms should be careful not to focus exclusively on individual touchpoints (e.g., a physical service encounter) or cues (e.g., website functionality) but rather should consider the multiplicity of and connectivity between stimuli and touchpoints customers encounter along their journeys. Such an effort may require collaborative collections of customer data with partners in the service delivery network. Ethnographic research can be used to understand stimuli in external touchpoints, and ultimately how offerings fits with customers’ lifeworlds. For example, Edvardsson et al. ( 2005 ) describe how IKEA designers observe customers in their houses, then create offerings that match those customers’ everyday experiences.

When mapping the consumer journey, firms should be aware that customer responses to stimuli also depend on customer, situational, and sociocultural contingencies (Premise 3). Therefore, customers in different situations and positions, with different resources, will likely react to particular stimuli in varied ways. Moreover, contextual factors may influence the evaluative outcomes of particular stimuli, such as the degree to which a particular reaction leads to satisfaction and loyalty. We urge firms to conduct customer research to learn about the connections among customer personas, usage situations, and responses to stimuli. These insights can be used as a basis for segmentation and to design different types of journeys for distinct customer types and situations.

Firms should also consider how norms, practices, and values in the customer’s context affect their experiences (cf. Akaka and Vargo 2015 ). Presenting offering-related stimuli that clash with such higher-order institutional arrangements will likely trigger strong reactions because they deviate from norms. The famous Benetton UnHate campaign is an example of an advertising stimulus that triggered strong affective and cognitive responses by creating surprising confrontations with prevailing institutions (cf. Hill 2011 ).

Determining intended customer responses and relevant stimuli for achieving them thus are prerequisites for managing customer experiences (Premise 4). The integrative view of customer experience offered in this study highlights the importance of both controllable stimuli (e.g., servicescape; Grace and O’Cass 2004 ) and those that exist outside the firm’s control (e.g., customer goals, ecosystems; Akaka and Vargo 2015 ). Firms should make an effort to design controllable touchpoints to facilitate the intended customer experience, but also develop methods to understand, monitor, and respond to stimuli their customers face in touchpoints that are beyond firm control. Firms can potentially adopt a facilitator role in some external touchpoints, for example, by providing platforms where customers can interact (e.g., Trudeau and Shobeiri 2016 ) or partnering with stakeholders that control external touchpoints (e.g., Baron and Harris 2010). Firms should constantly monitor the stimuli their customers confront in external touchpoints—for example in social media—and consider opportunities for adapting firm-controlled touchpoints accordingly, to leverage external stimuli supportive of the intended experience and mitigate stimuli causing dissonance.

Limitations

The results should be understood in light of some limitations. First, our systematic literature review did not capture studies that might address customer experience-related phenomena but that use different terminology or that focus on particular customer responses without connecting them to customer experience. However, the procedure of back-tracking articles reduced the risk of excluding seminal research on customer experience. Second, the decision to adopt strict criteria for article inclusion may have limited the results (e.g., excluding book chapters or papers published in languages other than English). Although this approach allowed us to analyze the 136 articles with greater rigor, we also acknowledge that the results may have differed if we had considered related concepts or adopted looser inclusion criteria. Despite these limitations, we are confident that the development of these fundamental premises of customer experience and their research implications will help scholars address this extremely important managerial priority.

We recognize that this is a simplistic division. We do not categorize researchers as positivists or interpretivists but approximate researchers’ assumptions as more positivist or more interpretive to varying degrees.

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Acknowledgements

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Appendix 1: Conducting the systematic literature review

Figure 3 presents an overview of the systematic literature review process.

Systematic literature review process

After reading articles about customer experience to familiarize ourselves with the phenomenon and help us decide on the methodological procedures (Booth et al. 2012 ; Littell et al. 2008 ), we established the criteria for the systematic literature review. We searched articles in the EBSCO Business Source Complete and Science Direct databases with the following keywords, separated by the term “OR”: “experiential marketing,” “service experience,” “customer experience,” “consumer experience,” and “consumption experience.” One of these keywords had to be present in the title, abstract, or keywords (e.g., Danese et al. 2018 ). We conducted the search in early May 2016 and did not set any temporal limits.

In the screening phase, we excluded all articles that were written in a language other than English, were outside the marketing scope, were not published in peer-reviewed journals, and were editorials, comments, or repeated articles. Then, we evaluated the relevance of each article to our study according to three criteria, such that it had to (1) refer to business-to-customer or general customer experience, (2) include customer experience (or related terms) as a central concept (Danese et al. 2018 ), and (3) provide a definition and/or characterization of customer experience (Helkkula 2011 ). In applying these criteria, we first reviewed the title and abstract, and, if necessary, skimmed or read the full article (Booth et al. 2012 ; Littell et al. 2008 ). These processes resulted in 142 articles to be analyzed.

Appendix 2: Metatheoretical analysis

We used content analysis to analyze the articles (Booth et al. 2012 ), reading them in chronological order within each literature field. The first step involved extracting material from the articles and transferring it to a codebook (Littell et al. 2008 ). To increase coding objectivity, we developed a frame of reference with explicit detailed procedures and coding rules (Littell et al. 2008 ). The codebook included variables that operationalized the key elements of the metatheoretical analysis; that is, phenomena and metatheoretical assumptions (see Table 3 ). To code the articles, we constantly went back and forth between the studies being analyzed and the frame of reference.

In the second step, we extracted material from the codebook to describe the phenomena and metatheoretical assumptions. To analyze the phenomena , we grouped similar codes to form theoretical dimensions. These theoretical dimensions aided our understanding of what customer experience is and how it is characterized in each literature field. For the ontological , epistemological, and methodological assumptions , we counted instances of codes to describe the metatheoretical assumptions in each literature field (contextualizing according to the understanding obtained by reading articles in each literature field).

Next, we developed a theoretical map, which we defined as a spatial allocation of different literature fields according to particular theoretical criteria. The description and comparison of the phenomena and metatheoretical assumptions in each literature field (i.e., the theoretical criteria) resulted in two higher-order research traditions: customer experience as responses to managerial stimuli and customer experience as responses to consumption processes.

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Becker, L., Jaakkola, E. Customer experience: fundamental premises and implications for research. J. of the Acad. Mark. Sci. 48 , 630–648 (2020). https://doi.org/10.1007/s11747-019-00718-x

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DOI : https://doi.org/10.1007/s11747-019-00718-x

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We have integrated MST into a range of Google products , such as Search, Google Photos, and others. We also open sourced MST, published our research , described our annotation practices , and shared an example dataset to encourage others to easily integrate it into their products. The Responsible AI UX team continues to collaborate with Dr. Monk, utilizing the MST across multiple product applications and continuing to do international research to ensure that it is globally inclusive.

Consulting & guidance

As teams across Google continue to develop products that leverage the capabilities of GenAI models, our team recognizes that the challenges they face are varied and that market competition is significant. To support teams, we develop actionable assets to facilitate a more streamlined and responsible product design process that considers available resources. We act as a product-focused design consultancy, identifying ways to scale services, share expertise, and apply our design principles more broadley. Our goal is to help all product teams at Google connect significant unmet user needs with technology benefits via great responsible product design.

One way we have been doing this is with the creation of the People + AI Guidebook , an evolving summative resource of many of the responsible design lessons we’ve learned and recommendations we’ve made for internal and external stakeholders. With its forthcoming, rolling updates focusing specifically on how to best design and consider user needs with GenAI, we hope that our internal teams, external stakeholders, and larger community will have useful and actionable guidance at the most critical milestones in the product development journey.

If you are interested in reading more about Responsible AI UX and how we are specifically thinking about designing responsibly with Generative AI, please check out this Q&A piece .

Acknowledgements

Shout out to our the Responsible AI UX team members: Aaron Donsbach, Alejandra Molina, Courtney Heldreth, Diana Akrong, Ellis Monk, Femi Olanubi, Hope Neveux, Kafayat Abdul, Key Lee, Mahima Pushkarna, Sally Limb, Sarah Post, Sures Kumar Thoddu Srinivasan, Tesh Goyal, Ursula Lauriston, and Zion Mengesha. Special thanks to Michelle Cohn for her contributions to this work.

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How 1 retailer’s data strategy powers seamless customer experiences

Crate and Barrel Chief Technology Officer Nari Sitaraman shares how the retailer uses data analytics technology to create a strategic advantage through its digital customer experience. An earlier version of this story appeared on CIO.com.

The past year’s disruptions were unparalleled and unexpected, driving lightning-fast pivots in strategy and execution to meet customers where and how they wanted to shop. Organizations had to accelerate digital transformation initiatives to survive, allowing them to bypass former barriers and reach long-term goals much sooner than expected. At Crate and Barrel, where online sales already accounted for more than half of our business, we’ve seen online sales jump more than 40% since the start of the pandemic. Currently, they make up more than 65% of our overall business.

As we look ahead, we see an even bigger revolution on the horizon, one marked by digital and physical engagement fused together to form an entirely seamless and highly personalized e-commerce experience. This is made possible by our use of data analytics technology , which offers more personalized, immersive experiences for our customers, with embedded machine learning to help our company navigate this dynamic retail world.

Organizations had to accelerate digital transformation initiatives to survive, allowing them to bypass former barriers and reach long-term goals much sooner than expected.

The distinctions between online and offline experiences are increasingly blurring. For example, curbside pickups of digital sales are one way the store and online experiences are connected. Similarly, our physical shopping catalogs have become more personalized, thanks to rich online customer data that allows us to customize direct mailers for different target consumer groups.

Still, customer interaction in each domain is different. Physical stores offer more inspirational experiences, inviting shoppers to come in and explore, spontaneously discover and physically interact with products, and imagine design possibilities for their own homes. Digital retail, on the other hand, is generally more personalized and guided, though it currently lacks the tactile discovery that gives life to in-person shopping trips.

Joining the inspirational nature and knowledge of physical retail with the richness and personalization of online retail is the future of online shopping.

This speaks to one of the most significant challenges retailers have when crafting a digital customer experience: bridging the gap between browsing a website and walking through a physical store. It’s been a constant evolution as technology and capabilities have changed. Early websites tried to replicate the store experience by using search to help people find products, categories to guide discovery, and navigation to direct visitors to specific pages. And while website design has been aesthetically modernized and new customer engagement features are constantly being introduced, the structure itself has remained relatively unchanged.

As external influences and new technologies come into play, companies should take advantage of the opportunity to completely reimagine the digital customer experience. Joining the inspirational nature and knowledge of physical retail with the richness and personalization of online retail is the future of online shopping.

Cloud technology powers the revolution of seamless retail experiences

We are at the start of a new era of retail experiences that go beyond using digital to simply reinforce physical experiences. Instead, the new focus will be on maximizing design and data to construct more inventive, creative, and inspirational experiences, both online and offline, and finding ways to bring the best of both together.

A big part of this digital shopping revolution is being powered by cloud computing . The cloud makes it easier to gather and analyze large amounts of data from diverse sources, like customer traffic information in a physical store, mobile shopping patterns, and other online purchasing behaviors, all in an effort to help us better understand customer pain points and how we can remove friction to continuously improve the modern shopping experience.

The speed and flexibility of the cloud, particularly when breaking down traditional data silos, is a clear advantage. To achieve a rich, personalized customer experience, it’s critical that organizations gather the right data in real time from their various touchpoints and then create a single data source that represents a full view of the customer.

At Crate and Barrel, we rely heavily on Google Cloud’s BigQuery data warehousing and analysis tool to save time preparing data sources. Thanks to its ease of use, we draw on 10X more information sources compared to a few years ago, which are then analyzed and transformed into actionable insights that can be used to influence the customer’s next interaction. And this, in turn, drives revenue. In addition, BigQuery’s machine-learning capabilities enable us to develop more models and recommendations at scale without raising costs or overloading resources.

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For instance, by mining omnichannel data about our customers’ shopping habits, we successfully shifted direct mail investment into personalized digital advertising with little friction and double-digit incremental returns. Digital ads allow us to gain rich insights about current and prospective customers that we can leverage to refine messaging strategies and drive omnichannel customer relationship management. We have created a complete view of our customers using online and offline data to constantly improve the customer journey at key interaction points, weaving throughout digital as well as offline experiences.

The speed and flexibility of the cloud, particularly when breaking down traditional data silos, is a clear advantage.

The data synergies across Google platforms have allowed us to better use contextual data to optimize and improve our ad effectiveness as we continue to scale our investments, which helped us double our return on ad spend while increasing our investment by 20%.

What’s coming next?

The future of shopping places more emphasis on technology teams, as well as designers and marketers, to innovate at a pace faster than today’s modern consumer. Fortunately, moving data among different repositories in different clouds or deploying data analytics technology enables teams to be nimble and react quickly.

Beyond marketing, we’ve already started using BigQuery to reveal more customer insights and opportunities for improvement throughout the ordering process. Whether it’s at product origination or last-mile delivery, we are striving to create transparency and frictionless experiences throughout the product life cycle. How organizations use data to augment both digital and physical business operations is set to transform all industries, not just retail. We have an opportunity to create a strategic advantage in our customer experience — and it all starts with data.

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