August 13, 2020

How do you organize/structure your market research?

Tobin Schwaiger-Hastanan @tobins

I'm curious how some of you structure your market research for sharing within teams. As a developer, I find I can get lost in trying to organize the information I have perfectly.

I'm less interested in what tools you are using and more interested in how you organize your market research so that it's not just a bunch of data points.

At the top level, I organize the research into the following silos:

  • Customer Profiles
  • Market Segments

Customer profiles identify the customer's problems, the costs associated with the problems, which market segments the customer is associated with, customer interviews, and how to reach those customers.

Market segments identify the size of the market, which customer profiles are included in the market segment, marketing/acquisition channels, companies operating in that segment.

  1. 1

    As a fellow developer who tends to gather as much data as possible...
    I think one needs to separate things, the core data, like you get a full data warehouse with everything humanly possible..
    Than you need to process it to be useful, so you might explore the infinite things in there, but that won't interest many.. What data do you find makes the best points? things that are clear to explain, and "meaningful" (either can drive a decision, show impact-full differences, can track things over time clearly..)
    At the end of the day people might only need 1-3 data points, 5 are already a boat load usually, don't dump the full truck load on them unless they are specifically data engineers than you need to document all the craziness in one way or another for them.

    If you need you need more, understand this is a data digestion position... like not marketing lets say, they might want to ask their own question, but probably won't be able to self server easily.

    I guess I'm saying there is:

    • Data gathering which might include processing
    • Data research (finding what's interesting in the data and/or ask questions that the data should answer)
    • Presenting data
    • Acting on data

    Most of the team would probably be close to the end on that?

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