Editorial
In today’s data-driven world, marketers amass immense amounts of customer information through numerous sources such as analytics, CRMs and loyalty programs — all of which provide plenty of quantitative data about customers.
This type of data offers the when, where, what and how of your customers’ interactions with your experiences. But critically, it does not provide the why. As head of research at WiderFunnel, I find that numbers alone (the quantitative data) are not enough for understanding what makes your customers tick. To understand the whys behind your customer’s actions, you need to have thick data.
Thick data allows you to understand your customer's emotional needs, which is what drives your quantitative data. Research techniques — such as contextual inquiry, diary studies, ethnographic research and others — can generate thick data that allows you to understand your customer’s emotional needs.
Here's how to leverage customer research to generate thick data, and how to apply this same data throughout your experiences.
Related Article: Mastering the Art of Emotional Customer Experience
Get as Close as Possible to the Right Participants
Let’s acknowledge a hard truth: real people don’t live in a lab. Further, research conducted in a lab is often subject to the Hawthorne effect — the tendency for research participants to alter their behavior under the researcher’s study. This can significantly affect the quality of your data.
To mitigate these risks, it is important to get as close to your participants as possible. My preferred method is to conduct deep, contextual interviews. As such, I am a big fan of remote research techniques that leverage technology. These tools allow me access to participants, in their natural environment, through their personal devices that they use every day.
I evaluate participant fit based on both the research context and timing. I always ask: Does this person fit the studies’ context? And: Are they actively engaged in or have recently experienced the situation we are looking to investigate?
Yes, participant recruitment can be difficult and time consuming, but getting as close as possible to the right participants is the foundation for leveraging your research in your customer experience.
Related Article: Customer Journey Mapping: Navigating a Way to Better Customer Relations
Balance Unstructured/Structured Approaches
Customer research should be both structured and unstructured. Following a completely structured research approach, with preset participant questions and a predetermined methodology for data analysis, often restricts the depth of insights that can be generated. This depth is critical for developing thick data and requires flexibility in the research design.
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When I conduct deep, contextual interviews, I use an unstructured format. I use my intuition to further inquire about unexpected topics of interest throughout the interview process, in order to deeply understand a subject’s unique context.
This unstructured format is then balanced with a structured approach for analysis. This involves coding observations using a structured system so that the codes can be analyzed and grouped into themes. This structured process allows me to synthesize my themes and trace my patterns of thinking into rich insights.
Consider the Different Systems of the Brain
When leveraging thick data it is important to keep in mind the different thinking systems of the brain. In his book, “Thinking Fast and Slow,” Daniel Kahneman explains that the human brain has two ways of thinking, the predominant fast, instinctual decision-making (System 1) and the slow, rational decision-making (System 2).
System 1 thinking is based on pattern recognition, mental models based on past experience, and the emotional associations of these past experiences. As such, emotions play a critical role in the human decision-making process.
To understand the emotional associations and needs of customers, I use the Limbic model to guide my analysis of thick data, as a way of understanding the customer’s emotional decision-making process. This framework has been developed over the past 20 years by Gruppe Nymphenburg and is based on the latest findings across various disciplines including neuroanatomy, evolutionary biology, neurochemistry and psychology.
The Limbic model analysis provides more than a contextual understanding of the customer; it also provides a psychological understanding of what incentivizes and delights your customers at every point in their journey.
Related Article: Everything You Thought You Knew About User Experience Is Wrong
Validate Your Insights Through Experimentation
Thick data is only as powerful as your ability to leverage it. And leveraging your thick data requires validation. I validate my insights through experimentation. Experiments not only help researchers validate existing insights; they also reveal more knowledge of how your customer behaves across every touchpoint.
When you gain an insight from your customer research, you should turn that insight into a powerful experiment hypothesis and design an experiment — whether that’s an A/B test, a multivariate test, or even a factorial design experiment — to test your hypothesis within your experience. Your customers then prove your ability to connect emotionally to them by moving further within your funnel, and this is validated with quantitative data: your sales.
But, your ability to connect emotionally to your customers is more than conversion metrics. An emotionally connected customer has an increased attention to your communications, a higher likelihood to recommend your product or services, less sensitivity to price, and a larger share of wallet — all indicators of a customer’s higher lifetime value for your brand.
Your skills in analyzing and acting on your thick data takes practice, creativity and curiosity — getting more impactful with each new iteration. Gathering and leveraging thick data takes work. But combining it with experimentation can lead to incredible results that compound over time to build a deep emotional connection with your customers.
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