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Editor's note: Jeofrey Bean is the principal of Del Mar Research and Consulting and is an adjunct professor at the University of California San Diego Extension. 

With so many choices of data and other types of inputs available for developing customer experience insights, it can be challenging to explain to clients or employers how inputs can be used together to create effective customer experience intelligence (CXI). 

Working with business and health organization clients and teaching customer experience leadership at UC San Diego Extension, I’ve found a portfolio approach to customer experience intelligence to be an effective way to explain it and to improve the acceptance and quality of customer experience intelligence and related decisions. I hope the approach explored in this article will help you do the same. 

An inside track

Time after time the customer experience leaders – small or large, business-to-business or business-to-consumer – seem to have an inside track to customers and the experiences they want. How do they do it? It’s not by accident. Most of the leaders have repeat success stories of determining, developing and delivering customer experiences that inspire people to advocate for them.

Is it some secret intelligence available only to these CX leaders? Partly yes and partly no. Yes, because companies have their own qualitative and quantitative data views just from being in business. No, because some of their methods of gathering customer experience intelligence can be used by almost any business. 

These intelligence-driven customer experiences effectively make companies with well-developed and -applied CXI better and different for customers. They increase revenues and profitability with improved customer retention, double-digit customer advocacy rates and declining cost of acquiring new customers. These are just some of the hallmarks of a CXI-centric business. CX leaders are committed to defining multiple inputs that feed their portfolio of information that is converted to customer experience insights. These insights enable effective customer experience decision-making.

Transformed into insights 

What is customer experience intelligence? CXI is the cultural and systematic combination of internal and external inputs from customers about all the interaction experiences they have with your business, on the internet and off, directly and indirectly. These inputs are then transformed by the company into insights that are prescriptive and predictive, resulting in effective decision-making to improve and innovate the customer experience. 

It starts with developing a deep understanding of customers in a professional and personalized way, going beyond the traditional customer profile for your product or service. This deep and contextual understanding allows you to apply the ingredients of customer experience (including your messages, people, processes, technologies and products and services) in a way that the customer adopts your company’s people, products and services as their own, integrated into their life and their business.

I have worked with many businesses that do not understand the real experience their customers have with most or all company interactions. An internal and external view is needed. It has been extremely helpful for many businesses to start by creating a specific internal view of what the customer is experiencing at every interaction. We start where they discover the business, through all the interactions of becoming a customer, including buying again, interacting with customer service and, in the best cases, becoming an advocate. The next stage is to define and evaluate the external customer-based view of their interactions with the business based on customer experience intelligence.

Before you begin, it is important to decide what are the minimally acceptable categories of information about each (and all) interaction(s) that are likely to be insightful for decision-making. New businesses have an advantage as they can learn this when using customer experience intelligence to help determine and develop what the experience should be.

Being practical, all businesses have constraints of time, money, customer dynamics and the ability to transform information into insights for decision-making. So, what are the minimum types of intelligence we should know about each interaction a person has with the company to make effective decisions? 

That minimum is the customer experience four or CX4. The CX4 are the leading indicators to be understood for each interaction a customer has with the company, on the internet or off, from the time a person has their first interaction and discovers the company to when they might be an advocate. With accurate information about each one of the CX4 from various types of customers, decisions on improving or innovating specific interactions become more successful.

The CX4:

1. The value of the interaction – how valuable was it for the customer?
2. The range of emotions people experience during an interaction. Having positive emotional outcomes may be the most critical factor in securing the ultimate value in a consumer or business relationship. As explained by Don Norman, author of “Emotional Design: Why We Love (or Hate) Everyday Things,” “It is all about the emotions you have. More important than the emotions you have … are the emotions that you remember. How long is the experience? It is an instant. It goes away. But in our memories, it is forever. And so it is much more important that people walk away with positive impressions, feeling good.” These feelings will weigh heavily in deciding whether to have that interaction again.
3. Customer perception of how the interaction used their time. When customer time and company time are aligned it increases the likelihood of repeat purchase and formal or informal customer advocacy.
4. The do-for/do-to effect. No matter what type of interaction people have, they are concerned about what it does for them or what it does to them. This is an instance where there is usually no middle. Listen to some people describe their past or anticipated interactions with their cable company or bank and it becomes evident that do-to is dominant. Customers of USAA, Workday and TurboTax (Intuit) tend to recount or anticipate their interactions more on the do-for side. In our book, “The Customer Experience Revolution – How Companies Like Apple, Amazon and Starbucks Have Changed Business Forever,” my co-author Sean Van Tyne and I wrote that do-fors, “are what products or services actually do for customers that they highly value. They answer the questions: What will that do for me? and Why should I care? Delivering the do-fors well with an extraordinary customer experience can create advocates and additional revenue.”

Figure 1: A partial view of the customer, client, guest or patient journey experience evaluation template tool. What will “finished” look like at this stage? The blank spaces will be filled in with words and data from CXI/PXI inputs, as in patient interaction number 14 in the chart. The completed journey evaluation, based on inputs (findings) will be the basis of an end-to-end patient experience assessment specific to one patient type.

The minimum set of dimensions for each interaction can vary by industry. For example, in health care (Figure 1), the minimally acceptable categories of information about interactions are likely to include a fifth leading indicator: physical experience. Be mindful that too many dimensions can make the process unwieldy, particularly if you only have the chance to have a single look.

Think what finished for this stage means to you. Potential information inputs into the CXI or patient experience intelligence (PXI) portfolio will be discussed later in this article. 

Continuing to build your model, add words and number ratings from an internal perspective for the CX4 or (or in the case of a health care example, the patient experience five or PX5) about each interaction. Compare the results for internal and external. Where are there differences and why? Where do the internal and external views align well? 

Flow of insights 

Insights allow you to make better, more effective customer experience-impacting decisions. The aim of customer experience intelligence is to have a flow of insights that allows you to improve existing interactions and anticipate and innovate new ones. Over time your goal is to be able to predict customer behavior. But where does customer experience intelligence come from?

Basically, customer experience intelligence comes from unbiased information inputs from customers and select company resources about customer interactions with a company. The data, words and observation inputs are analyzed specifically for insights that will help make effective decisions to improve or innovate the customer experience interactions and strategies for those customers.

There are businesses that think numbers and words from or observations of customers do not need interpretation to create insights or they leave the interpretation exclusively to computers. While it is fine to use automation for a portion of your analysis, it takes thoughtful, objective human input along the way to give the context of the human experience to the insights. In turn, this helps improve the effectiveness of the decisions based on CXI about interactions and determining new customer experiences likely to create advocates.

At experience-maker companies, this process is ongoing and is combined with the day-to-day activities and the experiences people at the company have for fixing, improving and innovating customer experiences.

Like an investment portfolio A group of carefully selected quality inputs from customers, users and influencers is the basis for good customer experience intelligence and resulting insights and decisions. This is a portfolio approach somewhat like an investment portfolio. The value or equity from the different inputs will be created when insights are created to guide decisions to fix, improve or innovate customer interactions or to determine what the experience should be. It may take some testing to get inputs (a hybrid, not a mongrel) in the portfolio that complement each other and allow the creation of valuable insights. The success of the group of inputs depends not only on their quality but also on how well the insights are derived and the willingness of your organization to change and take action. Emmy-winning actor Alan Alda, now a podcaster and founder of Alda Communications Training, has a definition of listening that offers tremendous meaning for organizations working with customer experience intelligence: “I have this radical idea that I’m not really listening unless I’m willing to be changed by you.”1  Consistent and dynamic

Figure 2: An example of the sources of inputs that can be included in the customer experience intelligence portfolio. Having thick data from inputs like in-person interviews or ethnography is an important partner with other input types for adding human depth and context to insights from the CXI portfolio. The project for this example found that thick data accounting for approximately 20% of the portfolio insights improved the effectiveness of the customer experience intelligence from it.

Leading-edge companies have integrated the flow of customer experience intelligence in a consistent and dynamic way. It is part of how they work and what makes them successful experience-makers.

There are many input methods a company can choose from to understand customer experience. Selected methods need to blend with the culture of the company as well as fit with the budget and other resources available. Yours can include listening, watching and accumulating qualitative and quantitative data. Unless your organization is willing to be changed and improve customer interactions from the insights that come from the process, you aren’t really listening to customers and can’t improve and innovate their experience with your company.

Whichever information sources you select to stay smart about customers, be sure to include those that give you a powerful combination of practical and innovative insights into the context of the multiple ways that people experience interactions. 

That means including thick data. Thick data is information that comes directly from humans, with nothing in between. It is a focusing lens when properly combined with big data, internal data and other data not gathered directly from people. Thick data adds important context about how people experience interactions. It can help make information that is gathered about people, both qualitative and quantitative, relatable to humans. 

Sources of meaningful thick data include in-person interviewing of people (not to be confused with surveying), careful and ethical observation (also known as ethnography) and focus groups. It starts out typically as qualitative and can have quantitative attributes attached to it. 

Non-thick data source examples include: online surveys; telephone interviewing; paper-based and internet surveys; web site analytics; customer support and customer service documentation; in-app feedback; customer idea portals; customer relationship management and customer experience management software systems; artificial intelligence; machine learning; data from the Internet of Things; internal data; predictive analytics; unstructured data; dark data and more.

Tricia Wang, an expert at developing business insights and effective results with ethnography and a fellow at Berkman Klein Center for Internet & Society at Harvard University, defined thick data in her landmark speech, “The Human Insights Missing From Big Data,” as “data from humans, like stories, emotions and interactions that cannot be quantified,” adding “…it comes in the form of a very small sample size but delivers an incredible depth of meaning.” 

Thick data combined with other types of data such as big data or internal data is the concentrate that helps make resulting insights and decisions more effective than big data or internal data alone. Wang emphasized this point, saying, “Thick data grounds our business questions in human questions and that’s why integrating big and thick data forms a more complete picture.”

Thick data does not need to be large in scale to ground other types of inputs in the context and depth of a human experience. Think of it as a potent seasoning to be considered with other data and insight creation. High-quality thick data makes its contribution when it is objectively integrated with these other types of data to help give insights in a combination that includes context and human dimensions such as emotions, do-for, do-to and the perception of how time is used in an interaction.

Only a small subset of the companies that use thick data combine it with non-thick data types to get highly effective customer insights to their decisive advantage. Thick data needs to be added to effectively understand these attributes and others that are vital to the human experience. Integrating thick data with other types of information increases the likelihood that a more exacting narrative pattern or set of insights will be revealed, answering the question: What’s the story (and outcome) with this type of person and that interaction? And why? By including thick data, the narrative pattern will reveal points and insights that otherwise would be missed.

Create insights

The goal of transforming customer data, words, visuals and other inputs is to create insights. Insights might stand alone as the basis for decisions or they might be combined with the decision maker’s prior experience and innovation success for effective customer experience decision-making.

Ultimately, with a combination of thick data and non-thick data inputs about customer interactions flowing into the company you will have insights to help people at the company make effective decisions about the interactions that make up customer experiences. 

A CXI portfolio rooted in but not limited to the customer interaction level will create insights for customer experience strategies too. New input sources will continue to be discovered and tested. For example, the qualification and quantification of text that people put into social media text analytics.

Many companies have their CXI processes assisted by automation for efficiency but for learning and for quality assurance, people need to be involved in most parts of the transformation, from inputs to insights stages, so that human attributes are not lost. If the process is left completely to machines, much of the value of thick data will be filtered out.

Organizations with continuous, real-time experience intelligence inputs that can quickly transform the inputs into insights, recommendations and actions will create customer experience leadership for their businesses. 

Some organizations are there now. They represent the leading edge of CXI by combining big data, internal sales data and customer-specific information anchored by thick data. Those inputs are transformed in a timely way into customer experience improvements and innovation. What these companies have in common is a culture of customer experience. If we were to go into these firms, we would find many variations in the kinds of customer experience inputs they use, how they anchor the input portfolio with thick data and how they transform inputs to insights and insights to recommendations and actions. But the businesses share a commitment and urgency to improving and innovating customer experience with dynamic customer experience intelligence. These organizations also use customer experience intelligence for developing experimental interactions and new customer journeys.

Many customer experience intelligence leaders have their inputs and processes for insights and actions so well-tuned and so well-timed that they’ve gone beyond persona profiles to innovate customer experience at the individual level. This type of intelligence can be inspirational as a palette of knowledge for innovating messages, products and services that will please the individual with an experience in unexpected ways.

Whether digital or analog, each interaction of a customer journey can produce qualitative and quantitative information and insights. In several cases, they are accompanied by information about specific personas, including the probability that the persona would proceed to the next interaction in the customer journey as well as the likelihood the customer would advocate based on that interaction.

You are doing it

Whether you are just beginning to transition data and words into insights or are a company that represents the customer experience intelligence of the future, the important thing is that you are doing it and it is effective for your business and for your customers.

If you want to bring the advantages of competing with customer experience to your organization, think about where you are now with customer experience intelligence and then carefully and thoughtfully develop the definition of next-generation customer experience intelligence. Whether it’s a two-input method to test or you have the good problem of transitioning a well-running customer experience intelligence method from low-frequency contribution to the business to a more dynamic and consistent go-to contributor to decision-making, it’s important that the quality of your customer intelligence is in the hands of people who genuinely care about the experiences people have with your business. 

References

1 “Alan Alda would like your attention,” Washington Post, March 12, 2020.