7 Cs method for analysis and synthesis of qualitative research data

95% of 30,000 consumer products launched each year fail.

https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing

Let’s imagine you have an idea for a new product or service innovation. If you want to give yourself the best show at succeeding, you MUST “front load” on the opportunity and problem analysis effort as much as possible.

Creating products (solutions) first and then trying to fit that to customer needs is a much riskier and more expensive undertaking.

Here are some steps you must do upfront:

Once you’ve done all this and interviewed a reasonable number of users (10-15 in each of the segments you may be targeting), you are most likely in the following situation:

You’ve come out of these meetings/interviews with voluminous amount of information. WHAT NEXT?

How do you mine this qualitative research data? How do you turn it into intelligence that can be used to answer the questions in your original research strategy?

If your interview questions were open ended (as they should be because they are meant to be exploratory), you’ll have a ton of somewhat free flowing information that you’ll to parse and understand. You’ll have answers to direct questions about pain points, but also motivations, psychology of the users, the WHYs and the WHATs.

Good, experienced researchers develop these skills over time. As product innovators, if you’re conducting this on your own (or with your team) you want to wear the hat of a researcher as well as a businessperson who will be utilizing that research for decision making.  NOW the real fun begins.

For the actual synthesis, there is an element of art and science however a framework to process and synthesize the data can be very helpful.

The goal is to produce ACTIONABLE insight as it relates to your original research intent and target.

7 steps (7 Cs) to synthesize user interviews from qualitative research

  1. Capture: It goes without saying that everything discussed in the user interview should be captured, recorded and transcribed without filtering out anything. Best practice is to have a team member who understands the research intent and goals join you as a participant to observe and capture all notes.
  2. Classify: To a large degree a “refined and structured” version of the actual interview notes. The interviews will almost always introduce free flowing information. The goal of this step is to help clear up the obvious frivolous information. If the overall interview questions were constructed correctly, they should more or less guide this step and some classifications/categories/themes should start to emerge at this point.
  3. Consider: Because it is crucial to stay within the problem domain (and not start to think of solutions yet), it is a very powerful technique to consider and surface deeper motivations and latent needs of the users. For each of the key answers from the step above, ask yourself… was there more to the answer? Why did they say that? This step forces the researcher and product innovator to really set the stage for recognition of motivations and needs (especially the latent ones) and eventually creation of target personas for the product.
  4. Conclude: This is where the research starts to draw conclusions and insights from the data in the steps above. For each of the user/respondent, provide conclusions that are focused on the original research goals and measures.
  5. Create: As a skilled researcher and especially as a product innovator we need to be able to create actionable intelligence and recommendations. The step differs from the step above because there is a final action proposal or decision geared towards the consumer of the research and the businessperson.  If your role is to produce the final research report , you should focus on producing answers to the original questions for the audience who sponsored the research. If you are a product innovator and entrepreneur conducting the research, it is very possible that you’ve learned things that were outside the direct realm of the research targets, however they are important enough to explore for the product vision. In my personal experience, that can be valuable in case you need to pivot or evolve in the future.
  6. Combine: If you speak to 10-15 users and perform this synthesis for all of them, it is important to combine that into a cohesive research output.
  7. Communicate: No research is complete unless the combined output is summarized and an executive summary communicated at the end of the study.

The research study on its own shouldn’t be the only criteria for deciding the future of your product offering and your eventual solution. It is only ONE of the many inputs for that decision making. It is quite possible that a follow up quantitative study needs to be performed to validate some of the aspects highlighted in the research report, or perhaps a round 2 of qualitative study

What is your experience with the practices you’ve used for analysis of qualitative research data?

14 thoughts on “7 Cs method for analysis and synthesis of qualitative research data

  • Kim

    Interesting stuff. Yes, the if you build it, will they come — waste.

    Let’s bring on surveys. It’s also good to get another round of qualitative, check research for any current happenings if necessary to continue to narrow the scope if needed. So curious to see where this will go.

    Oh oh the places you’ll go – Dr. Seuss ;p.

    • Vipin Makhija

      @k4dwin RIght on Kim. It’s never either only one type research. Qualitative, quantitative, industry research all go hand in hand in fulfilling the overall research objective.

  • Rahul

    This is a challenging phase of product discovery. One thing I learnt from our discussion Vipin, was that you always need to keep the research goals at the forefront when mining the data for insights. We can’t be solving each and every user problem/pain-point. The empathy map was a useful tool to structure this analysis.

    It’ll be interesting to see how the quant survey goes – should either reinforce what we’ve learnt from qual interviews OR force us to critically think about pivoting; and if it’s the latter – where do we pivot?

    • Vipin Makhija

      @rsridhar It’s easy to get carried away sometimes isn’t it, especially in qualitative interviews and user discussions. Having a vision set up upfront around the key objectives of the research, are immensely helpful in being effective.

  • Aouie G.

    This 7 steps is such a helpful guide! Synthesizing user interviews is really challenging, especially when you get insights that are contrary to your initial hypothesis or assumptions. The empathy map was also useful in guiding me in making my synthesis.

    Looking forward to how we’ll process key findings from interviews and our next steps.

    • Vipin Makhija

      @aougarcia It is a lot of science and a little bit of art. There’s no such thing as perfect research, but user interviews almost always throw a few (useful) surprises.

  • Rosanna

    Very useful and helpful guide. Analyzing the interviews let you reflect on other potential direction to explore for the product innovation and that is however related to opportunity hypothesis.
    What I am finding more challenging is linking and relating the industry research data and information, more at higher level, to the narrowed down specific experience of the users interview.
    What I was wondering is if the qualitative phase should have a large group of users interviewed to have more experience to compare but also including the insight emerged from the round 1.

    • Vipin Makhija

      @rosanna To your point about having a large group of users for comparison, yes absolutely, however, there comes a point, when it doesn’t add further value, and synthesis of user interviews (especially 1-1) is a very time-consuming exercise. In my experience, a general rule of thumb is to try to go for 6-8 interviews in a particular segment.

  • Ronit Mhatre

    The 7 C’s approach is very well drafted considering the failures and success of product launches . Considering our Real Estate project, once done with the industry and user research we need to focus on what job of realtors for getting quality lead are we trying to do? Are we focusing on the pain points like lack of trust, less knowledge of real estate buying as a buyer, financial barriers or are we focusing on emotional needs like choice of location, friendly neighborhood, infrastructure.

    Also, I agree with @rosanna that number of users are less for synthesis so, following the 7 C’s approach recursively will give more concrete results after increasing user interviews in a phased way.

    • Vipin Makhija

      @ronitmhatre Good points Ronit. The goal and objectives of the research will determine the expected outcome.
      The actual creation of solution is a subsequent step and requires its own sequence of stages and analysis.

  • Runa

    The 7cs seem like a methodical way of doing qualitative analysis. During my individual analysis, I realized I heard some of the pain-points during parts of the conversation when the agent was not really answering a specific interview question but was sharing a recent experience. It would be interesting to see if the quantitative survey would align or misalign with the qualitative analysis.

    • Vipin Makhija

      @Runa Very true. Some of the most insightful findings can come when the user shares their own experience freely. And that’s exactly where followup rounds or a quantitative survey can help validate findings with a larger set of respondents.

  • Pras Palani

    I loved the HBS article Vipin. So true.

    We need to think of RE Agents’ Jobs to Do & how are we making that easier & efficient.

    On the blog post itself I am thinking should ‘Consider’ be the 2nd step. After ‘Consder’ you can ‘classify’ answers & insights. That will complete classification process. Also ‘consider’ itself is a lighter word & not truly reflective of the tasks in that step. We are trying to come up with motivations & insights. Just my 2 cents.

    Though you are trying to differentiate between step 4 & 5, I think there is lot of repetition between them.
    For ex – ‘create actionable intelligence and recommendations’ should be part of ‘conclude’. How can we conclude with any of the above ?

    Steps 6 & 7 should be sub steps of ‘Conclude’ ( which should be the last step in my opinion).

    Hope this helps ! Appreciate your effort in blogs & that stir up thoughts !

    • Vipin Makhija

      @pras Interesting points Pras. In the end remember we are parsing, analyzing, and eventually synthesizing free-flowing , natural language (including understanding some unsaid things). So any method that creates an approach to truly empathize with the users and enables the researchers to avoid assumptions and biases can be embraced. As long as there is a conscious formal exercise to try and convert the answers from the users into intelligence that can be actionable.

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