How to be a UX Researcher: Analysis 2

How to be a UX Researcher: Analysis

Welcome to the second instalment of How to be a UX Researcher. 

In the first lesson, I went over the importance of talking to users to gather information. So what’s next? We now need to think about interpreting and analysing that information. In this post, I’m going to pass on my personal tips and advice on the analysis stage. So grab a cuppa, get comfy and let’s get started!

Let’s say you’ve carried out your interviews, shadowing and questionnaires, so you have a whole bunch of experience data and answers to find greater meaning from. But where do you even begin with a task like this? If you’re not sure where to start, let’s break things down and take a look through the different steps you’ll need to follow.

Be prepared

It’s all well and good having insightful conversations with users but it means nothing unless you can note that information down. That’s why it’s so important to put in a little groundwork before you get started.  So, prior to jumping in and talking to people or handing out questionnaires, do some prep and consider how you’re going to record your data. Will you record mirroring and interview sessions, then make notes afterwards? Will you try to take notes during? And where will you keep your notes?

I’ve always preferred to take notes during the interview. The main reason is that any key insight can be taken down in context of the conversation. That said, none of us are superhumans – so it won’t be possible to write absolutely everything down. That’s why I’d recommend recording the session too, so that you have a backup version to fall back on. You’ll probably find that you pick up new information when you listen back to the recording, so you can add more details to your notes then. 

Identify patterns

Going through all of the information can seem daunting at first. But don’t worry – you’ll soon find a flow to it, especially if you can identify patterns within your transcripts. 

If you’re not sure where to start, think about what stands out. Are there certain user issues that pop up time and time again? Are common thoughts and feelings being expressed during lots of different sessions? 

You’ll soon start to notice common themes. When you do, it’s vital to make notes about them, in whatever format works best for you. I’m a tactile worker, so I like to make literal tally marks in a notebook. Some of my colleagues prefer to colour code answers and responses in a spreadsheet, others like to copy and paste common answers into a separate document. 

Do what works best for you. Whatever method you choose, finding patterns in your data will form the backbone of your findings. Best of all, it will help you to organise the information in a way that is much easier to present and report on. 

Quantify the Unquantifiable

Want to know the most important lesson I’ve learned during my time as a researcher? Here it is:

The most powerful factors for change are a good quote and solid numbers. 

I find that some clients respond better to stories about people, whereas others prefer to see data in the form of numbers and percentages. That’s why it’s so important to be able to take a mass of different stories and experiences and condense them into an easy to understand figure. 

This is simpler than it might sound. For me, once I’ve identified a pattern, I quantify the number of people who fall within that pattern or occurrence. Let’s say I’ve spoken to or shadowed 25 people. In my notes, I’ve identified that 20 of those people struggle with a particular issue or action. I could represent this by telling the client each individual’s issue with the action, how they came at it and what they thought. But wouldn’t it be better to simply say 80% of users/customers/employees struggle with X action? Presenting the information in this way  means I’m able to get straight to the point, making it easier for the client to remember. 

Remember the stand outs

I’ve covered the importance of solid numbers, but what about the ‘good quote’ I mentioned earlier? Well, a good quote is like a pot of gold. You’ll have a participant that sums something up in a way that really stands out. You’ll see a throw away comment that expresses an issue or concern much better than you ever could. 

Quotes add a human element to your data. So while it’s important to have a quantifiable answer, it’s equally important to remember the people behind the numbers. Choosing a quote that makes an impact is a great way to achieve this. Any good researcher will talk a lot about quantifiable and qualifiable data – and all good research will strike the right balance between numbers and stories. 

Key takeaway: Present the data, and then explain the context

Here’s a quick summary:

  • Think ahead – that means being prepped and ready to go before you start your research. 
  • Look for patterns in the data and highlight them using a method that works for you. 
  • Find ways to turn those patterns into good solid figures…
  • …But don’t forget to tell the story that goes along with it!

That’s all for now – see you next time for Stage 3!

Andrew Machin
Andrew Machin

With over 25 years’ experience in UX and digital strategy, Andrew has helped many national and global brands such as John Lewis, Harley Davidson, Johnson & Johnson, and Interflora create exceptional digital product experiences.

Through the success of such projects Andrew has received high-profile accolades that span innovation, strategy, and design, such as the Dadi Grand Prix Award and the Digital Impact Award for Innovation.

This experience has led to Andrew judging digital design awards, been featured in .net magazine, lecturing at Leeds university, and speaking at seminars and conferences across the UK.

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