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Business

Best analysis technique for user study interview data?

I have completed 6 user study interviews. Each interview contained around 40 questions in addition to a walkthrough of an MVP to get suggestions. I have assumed i have four different scenarios in which my service could operate in and so there are four sections to the interview (10 questions per section). Now i am stuck wondering which is the best or most commonly used analysis technique to record and review the data?

Can you include your questions, please?

There are different approaches depending on they type of data your received.

1 Answer

Ben, thanks for sending the link. Your questions require narrative answers - much harder to analyze than Likert scale (strongly agree, agree, neither agree nor disagree, disagree, strongly disagree) or multiple choice.

You'll have to do a content analysis. Start by finding themes in the answers given, then try to code the answers (code as in qualitative analysis not computers).

For example with the question: What do you typically do when preparing to transact funds to a business in person? If their answer was "I check my bank account to see what funds are available". You might code that as "payment ability".

You would then search for other answers from other people for that same theme.

You'll end up with a code book with the different types of responses, you can distill each answer to its most basic elements. Then you can perform some basic stats work - like finding the percent of people who identify with a certain theme.

Your answers will be easier for you to look at and find similarities, and decide if your product will work as you intended.

Hope that helps.