User research is non-negotiable when it comes to designing better products. We all know that.

It gives us a wealth of qualitative and quantitative data to better understand our users and their problems.

The question is how do we best make use of this data. How can we define the precise problem or sets of problems we need to solve?

We do this by analyzing our data, and there are a number of methods to help us do just that.

Before we find out how to take our raw data and transform it into actionable insights, let’s first consider an important concept to the UX design and analysis process. The concept of triangulation.


You’re probably already aware of the concept of triangulation through movies and TV shows. When there’s a baddie who is on the run and needs to be found, measurements from three different sources are taken to accurately pinpoint the location of their mobile phone and thus them.

The concept of triangulation can also apply to the UX design process, though it works slightly differently.

In this context, we also use different sources to obtain more accurate results. But instead of cell phone towers, we use and analyze multiple data sources and methods (our research data) to obtain a better, more accurate understanding of the problems that need to be solved.

The key to this is to look for patterns.

If we identify patterns we can better articulate the problems we need to solve for our users while also being more confident that we are solving the right ones.

This isn’t always a straightforward process. It is often more of an art than a science. Like our user research data it can also appear messy.

But through the use of different UX analysis methods we can identify patterns, establish the direction to focus our design in, and ultimately design a solution that meets our users’ needs and solves their problems.

5 of the Best Methods for UX Analysis

There are five methods we can use to analyze our research data and identify patterns.

1. Affinity Diagram

One of the very best analysis methods is the Affinity Diagram. It is a great tool for organizing unstructured data into actionable insights.

The combination of Post-it notes and collaboration may not sound like much but it is a powerful way to quickly define high-level recommendations to base a design strategy on while giving everyone a voice and coming to a shared understanding.

2. User Journey Map

A User Journey Map enables you to visualize what a user experiences as they interact with your  company, service or software.

It is a brilliant highly structured tool that lets you see things through the eyes of your users and highlights aspects of the journey that need to be fixed as a priority.

As the output is visual, it is also easy to understand and share with others.

3. User Personas

There is some debate whether User Personas should be used or not because they usually involve at least some element of fiction.

However, they can be useful for providing a clear design target for the design team while avoiding self-referential design. They can also build empathy between the team and its end users.

4. Empathy maps

Empathy maps do exactly what they say on the tin. They are just as effective and achieve the same goal as user personas but without the pitfalls.

A typical empathy map has 4 quadrants: Says, Thinks, Feels and Does. But to make an empathy map less generic and a bit more more focused on the UX process and project itself, it’s usually a good idea to change these quadrants.

New quadrants may include mismatched mental modes, pain points, points of confusion and goals. You can also use our own logical categories that may be an even better match to your research and project.

Either way, you place insights written onto a Post-it note into the appropriate quadrant.

5. Customer Value Curve

The final method you can use is a Customer Value Curve.

This is a competitive analysis tool that shows how your current product currently stacks up against the competition or how it could stack up against the competition in the future.

It’s a great way of presenting research insights to non-design stakeholders, helps identify competitive gaps to close or exploit and can provide strategic direction.