Getting the most out of your Voice of Customer data

Michelle Shotts
Jan 6, 2017 · 5 min read

It was Albert Einstein who said, “The formulation of the problem is often more essential than its solution.” This statement is true for any type of research, and user research is no exception. Only by truly understanding the question can you begin to formulate what techniques and tools you might use to answer that question.

Different user research methods lend themselves to different types of questions. You need multiple ways to listen to customers and the ability to connect those metrics. We’ve all seen visual maps that show where different methodologies fall on the continuum of the type of questions they answer best. One of my favorite, and in my opinion easiest to understand, is by Christian Rohrer from his post “Landscape of User Research Methods.” To best explain when to use which method, Rohrer maps various methods along a “3-dimensional framework with the following axes: Attitudinal vs. Behavioral, Qualitative vs. Quantitative, and Context of Use”.

But, in addition to thinking about the 3-dimensional framework, when considering Voice of Customer (VOC) data sources, you also need to think about a 4th dimension — what level of granularity is needed. The more granular the listening the more tactical the insights tend to be. This is likely true across all research methods but especially so when it comes to VOC data.

In general, there are 4 key levels to consider when thinking through levels of granularity for Voice of Customer data:

Each of these levels gives you a different perspective into your customers and provides insights that build on and feed into the other.

Brand or journey level

At the brand or journey level, you can understand the relationship or emotional connection customers have with your brand. Do they think of you like family, a good friend, just an acquaintance, or do they not know you at all? Are you the go-to friend, the fun friend, the flaky friend? Does their perception of your brand match the way you want to be seen? For example, in a 2015 iModerate study, both Trader Joe’s and Whole Foods were known as being alternative options to traditional grocery chains with a focus on organic, health-conscious offerings. However, Trader Joe’s was generally seen as quirky and down-to-earth while Whole Foods was seen as liberal and elitist. How you’re perceived at this level will set the tone of what customers expect from you at the levels outlined below. Insights at this level are generally more global and therefore more strategic.

End-to-end experience level

The end-to-end experience level is a subset of the overall journey. It tells you how well your experiences deliver across functional silos — this can mean across devices and/or from online to offline. This is also where you can see how customers are treated if you’re passing them on to a partner relationship, such as a ticketing site passing customers on to a movie theater partner. The end-to-end can give you insight into where you’re most successful in delighting customers or where there may be breakdowns that are degrading overall brand perception. Insights at this level start moving toward being tactical but are still somewhat higher level requiring more granular follow on research to be truly actionable.

Visit level

The visit level is a subset of the end-to-end experience and tends to be transaction oriented. You can think of the visit as a single shopping trip to Target where you bought 5 items or a single visit to the Amazon app where you put 3 items on a Wishlist. This is the level where you can deep dive into individual channels that make up the overall end-to-end experience such as your desktop, mobile, customer care or in-store offerings, in order to understand customer expectations for each channel and how it fits in with the overall end-to-end experience.

Page, component or subtask level

The page, component or subtask level is the most granular and tactical level of listening and measurement. At this level, you might specifically focus on an individual page of your website such as the product page on Amazon where you see all the information about an item. Or, you might focus on a core subtask such as looking through product photos on the product page or using a price check kiosk in-store. This level also tends to get a lot of attention because it feels like it has the most actionable outcomes, but it doesn’t tell you how well things work together.

It’s important to remember that customers don’t experience your brand as pages, widgets or individual offerings which is why you need to understand all levels of the experience.

Once you’ve thought through the problem and considered granularity in addition to the 3-dimensional framework, you can determine which methods are best suited to your particular time and budget constraints. Your next step will be to think about how to integrate data across methods, whether they be quantitative, qualitative or Big Data, so you can derive 360 degree insights. You don’t want fragmented data living in silos. For an outstanding article on avoiding a research monoculture, I highly recommend Louis Rosenfeld’s article “Seeing the Elephant: Defragmenting User Research.”

And, keep in mind, it’s not just about data collection and analysis. Once you’ve collected the data, you need to leverage storytelling and feedback loops to make sense of and capitalize on the insights you gain through your tools. Stats and charts are hard to remember. Stories are memorable and create empathy that motivates people to act. Use stats and charts to punctuate the key points in the story you’re telling with the data but don’t make them the center of attention. Keeping your audience top-of-mind, communicate how the insights you’ve gleaned from the data are relevant to the original business problem.

Michelle Shotts
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