This post is the first in a two-part series on making sense of the qualitative data we get from talking with customers. Part 1 focuses on what you can do before and during a customer interview to make life easier for yourself after the conversation is done. In Part 2, I will focus on finding patterns in the data you have collected.

As an innovation coach, I get the opportunity to hear questions about the challenges of implementing Lean methodologies. One question I hear a lot is: “How do I use the data I get from customer discovery interviews?”

crowd with one person standing out

Before your customer interviews

Let’s say you’ve figured out that you should be talking to your users to learn something about their problems, or perhaps your product or service. What are you doing to prepare for those conversations? How are you spending your time during those conversations? The good news is that even if you don’t do anything to prepare for your customer interviews, you are still doing more than the entrepreneur who is sitting at their desk all day trying to figure out what is wrong with their idea. Here’s how you can do more:

Focus your conversation

Before beginning a customer conversation, you should have a learning goal. A learning goal will help you keep your conversation on track, and as long as you stay focused on achieving that learning goal, the feedback and data you receive from the user will be focused as well. A sample learning goal might be:

“I want to learn how university professors distribute their presentations and other classroom material to their students.”


“I want to learn how much time and money first-time employees in San Francisco spend commuting to work.”

If you walk into a conversation with a focused learning goal, you are more likely to walk out with focused learnings. I like to keep the learning goal front and center in my conversations by incorporating it into my notes. I write it out in big letters at the top of each page so that each time I glance down at my notes, I’m reminded of what I’m there to accomplish.

During the interview

Limit your notes

I have to credit David Bland for helping me think differently about my note-taking habits in customer interviews. I used to write down everything I heard so I wouldn’t miss anything (sound familiar?). That all changed when I started focusing on taking only four different types of notes:

Direct Quotes

This type of note is pretty self-explanatory. Direct quotes are so important because writing them down prevents you from trying to turn your notes into insights while you are conducting the interview. The direct quote is a piece of objective data that you can analyze after you’re done with the interview. It helps you treat note-taking as its own activity.

Often I’ll record my customer interviews in a template so I can make sure I get the direct quotes down accurately. I don’t use the recording to replace or supplement the interview itself, I just use it to double check my notes and make sure my direct quotes are accurate.

two people talking chat bubbles


Much like the direct quotes, the purpose of writing down observations is to remain objective while taking notes. Observations are different from insights, and when you try to draw insights during note-taking, you run the risk of missing something else that a user/customer says.

Let’s say you are interviewing Jimmy about his lunchtime eating habits. He tells you about going to McDonald’s five times last week, and also what he ordered when he was there. It’s the difference between writing down that note as:

“Jimmy went to McDonald’s for lunch five times last week.” [Observation]


“Jimmy loves McDonald’s, and he goes there as much as he can.” [Insight]

It’s a subtle difference, but an important one. In the “Insight” example, you might very well be right about Jimmy, but you also may be wrong. What if Jimmy’s friends dragged him to McDonald’s against his will? Jumping to the conclusion that he loves McDonald’s just because he went there five times might seem safe, but is risky if it’s wrong. After you have completed the interview, you will have a more complete data set and can reference other parts of your notes for context and clues to help you limit the risk of making errors.

customer discovery interviews - face - Smiley to Frowny (1)

Body Language

Non-verbal communication can be quite telling, but it’s a tricky note type to record. Often the signals you are looking for happen in a split second: a little smile, eyes widening, someone shying away, etc. But when you recognize it, body language provides a powerful signal. Watching someone react to what you are telling them is like taking the filter out of the equation. So whether it’s positive or negative body language, make note of it. You might just find more truth in that than in the words of your customers.

customer discovery interview - emotion - face - Various

Miscellaneous notes

With every interview I run, I always have a section for taking down miscellaneous notes. Sometimes they’re notes that have to do with who the participant is. Other times they are just ideas that pop into my head. You’ll figure out what to put in this section when you actually do the interviews, but it always helps to have a little empty overflow space.

After your customer interviews

In my next post, I’ll be writing about what to do with your data after you have conducted a customer interview. For now, let’s recap the “before” and “during” parts before worrying about the “after” part.

We need to set ourselves up for success by:

  • Focusing our conversation with a learning goal.
  • Limiting our note-taking, focusing on:
    • Direct Quotes
    • Observations
    • Body Language

Once we have done that, then we can be confident with the data we are collecting, and know that we are using our time wisely when we gather insight from that data.

Lessons Learned:

  • Focus your conversation around your learning goal.
  • Limit your note-taking to quotes, observations, and body language.
  • Know the different between observations and insight.

Download Customer Insights Template

Read Part 2 here.

* This post has been recently updated to reflect developing thoughts on this topic.

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