Doing any kind of user research is a good thing but if you don't mix things up regularly, you'll become blinkered.

We often repeat the same things in our lives and work wether out of laziness, habit, or simply because we lack the confidence to try something new. Although this behaviour may not be massively detrimental in our personal lives, doing the same kind of user research day in, day out will seriously limit your view of the landscape and the quality of insights you collect.

I’ve witnessed many product teams doing the same old usability testing sprint after sprint, constantly refining interface elements and copy on a micro-level, only to see them loose focus on the rest of the user journey and context of use (e.g. ‘What route did users take to get to this page and what issues did they encounter along the way?’).

To avoid falling into this trap, follow these 3 steps to reduce bias in your user research and make your findings more robust.

1. Make a list of all data sources which are available to you.

Combining data from different sources will help you see things from different angles and give you a fuller picture of the problem.

First, locate all information sources that will provide you with a range of different data types (this user research cheat sheet is a great place to start). If you’re already doing some research - such as user testing/usability testing - then consider other areas to focus on, such as speaking to frontline staff or contact centre advisers, as these will allow you to view the problem space from their perspective.

*‘Triangulation’ or mixed-methods research allows you to evaluate different perspectives and data types, which will lead to more robust insights in your user research.*

2. Do research in each area individually and compare your findings.

When planning your user research you should have came up with a set of questions or hypotheses centred around what you want to learn, or any assumptions you have. It’s a good idea to use these same hypotheses to inform each piece of research, wether it’s in the form of a discussion guide (for user interviews) or a checklist that will guide your data analysis in web analytics or social media. You will also generate more questions (and answers) as you go.

Always aim to include contrasting types of data in your research. For example, by comparing quantitative data from call/email logs with data from interviews with call handlers, you can begin to understand the context and motivations around why customers are calling up about Problem X.

3. Reflect, rinse and repeat

When you’ve done research in all areas, keep revisiting them until you’re fully confident that you’ve got enough evidence on all of your hypotheses and assumptions. A good way to do this is to use a technique known as assumptions mapping, which will allow you to visualise and document your understanding.

This stage is more about pausing and reflecting, which is so important. I’ve identified potential issues in usability tests which I then attempted to evidence or ‘validate’ using Google Analytics, only to find that the analytics data appeared to contradict what we’d learned during our testing. After iterating our approach and doing further testing, we eventually had a fuller understanding of user journeys and ironed out the issues. So, it’s always good to keep going to each area until you’re getting validation from all sides

By following this 3 step process, I hope you’ll be able to fill in any knowledge gaps and make your research findings more robust.