When user research goes wrong

When user research goes wrong

Oh no my user research has gone wrong!

Insights from user research are invaluable to the development of high-quality digital products and services. However, more user research does not always mean a better end product. Poorly designed, run or analysed research can definitely do more harm than good. Here are my top five pitfalls that can turn user research into a waste of resources:

  1. Asking the wrong questions. As I talked about in a previous blog post writing bad questions for surveys or interviews can distort your findings and set the whole development process off in the wrong direction.
  2. Asking the wrong people. The people you carry out your user research with should genuinely represent your users – their knowledge, their abilities and their attitudes. Testing with experienced tech enthusiasts is pointless if most of your users will be people with low digital knowledge, for example.
  3. Researching for the wrong reasons.  As a user researcher sometimes you get asked to perform research on projects when there is no plan or capability to act on the findings we will produce. The research is being done purely to stroke egos or tick a box, but no matter what is found it will not alter the final product or service. Research isn’t there to provide validation and reassurance – its role is to challenge assumptions and inform changes. If it’s not going to do that, it’s a waste of time.
  4. Testing in the wrong context.  In some circumstances the context in which users interact with your product is so important that doing research out of context will only give you confusing and misleading results.  For example, if you’re testing a prototype app that users will engage with in a busy, noisy factory, then there is no point in testing it in a quiet lab – you won’t find out about the elements of the environment that could make your app useless.
  5. Making wrong assumptions about your users. The design and development of products is built on a combination of knowledge and assumptions – things you know about your users and things that you think you know. Acknowledging the assumptions you are making and testing them will ensure you start off on the right foot. For example, if you think improving the readability of your terms and conditions will increase the number of people signing up to your service, you’re assuming that people at least try to read the terms and conditions. There is no point researching the best way to improve the readability if you don’t first check your assumption that people are reading them at all.

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