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Analyzing and synthesizing research results

Make Insights from observations

When you synthesize something, you combine ideas to draw conclusions.

What does that mean for us? Well, when UX designers synthesize research, we group data into themes.

We want to find insights that evolve our understanding of users and their needs.

That last part is really key. A synthesis evolves our understanding.

By grouping these shared frustrations, we can understand how crucial this problem is and figure out ways to solve it this is our insight.

After we discover insights, we're ready to iterate on our design.

Iterate means we revise the original design to create a new and improved version. UX design is all about coming up with an idea, getting feedback from participants or users, and iterating to make the idea better. We are constantly improving our work.

Traditional research, like asking riders to test a new app feature and collecting feedback and compiling data, is always a useful process in the UX world.

However, field research or firsthand observation of people in their natural environment is incredibly valuable too.

It allows researchers to collect audio, video, and in-person experiences.

These personal experiences helped the UX team truly empathize with its users and understand exactly what each person needs.

Developing Insights

Insight is an observation about people that helps you understand the user or their needs from a new perspective. Insights can help us figure out how different pieces of data relate to each other.

Insights also help explain what data means and what to do with it.

How can we come up with a list of insights?

First, we need to gather all of the data from our usability study in one place.

We might have collected data in various formats such as stacks of sticky notes, a spreadsheet, audio notes, or even a notebook with our scribbles.

You also need to gather together the notes from everyone who observed the usability study.

Step 2: Organize the data. This is where we take the data gathered in Step 1 and arrange it.

If you wrote your observations on sticky notes, you might use a method called affinity diagramming

to organize your data.

You'll learn more about this later. If you used spreadsheet notetaking to record your observations, you've already started organizing the data without even realizing it.

Step 3: Find themes in the data. One of the key goals of user research is to identify themes that are common across participants.

These themes help us to turn our data into insights about the users.

You'll find that UX designers and researchers often use the words, patterns, and themes interchangeably.

Technically, they're a little different, but for the sake of simplicity, we're just going to use the word theme.

Finally, come up with insights for each theme.

We want to write an insight that tells the design team how to improve the product based on a theme.

Depending on the amount of data you've collected, you should be able to come up with a handful of

themes and insights.

You're well on your way toward what we call synthesis, which is combining ideas to draw conclusions.

Gather and organize data

One method you can use to organize data is called affinity diagramming

Affinity diagramming is a feeling of like mindedness or compatibility towards something or someone.

Have you ever run into someone from your hometown while traveling?

You likely felt an affinity towards them.

You had something important in common that made you feel closer to each other.

An affinity diagram is a method of synthesizing that organizes data into groups with common themes or relationships.

Affinity diagramming is a quick and easy way to gather observations during a usability study and synthesized data.

To make an affinity diagram, you need all of the observations from participants to be on sticky notes.

To make 4 or 5 clusters. You can place these clusters on wall, window, or whiteboard.

Your job is to bundle together sticky notes that have related ideas or themes.

In order to do this, compare sticky notes one x one and ask yourself is the observation on the sticky notes similar to any of the other observations I've reviewed so far or is this observation different?

By putting sticky notes and clusters, you can easily spot themes across all of the observations from your usability study.

It's also easy to shift ideas around between themes because you can peel and stick the notes in different locations.

One more note about affinity diagramming. Although it's highly visual in nature, affinity diagramming can be adapted for participants who are visually impaired.

For instance, during an affinity diagramming session, a participant with a visual impairment could dictate what to write on each sticky note.

After stickies are grouped together, someone could read each sticky note out loud and ask participants to suggest groupings. This way you keep all participants involved.

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Put sticky notes in groups

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With all of your sticky notes ready to go, it’s time to cluster the observations and quotes into groups. You can either list a couple of groups to get started, or you can come up with group names as you go.

For example, there might be a group that you know there’s feedback about, like “Scheduling." If this is the case, you can create this group from the start. As you review the sticky notes, add them to this group. For example, sticky notes that say "Wants to book multiple dog walker sessions" and “Wants a calendar to schedule date and time for the dog walker” would belong in the "Scheduling" group.

Or, as you review the sticky notes, you might notice that two of notes are related, like: "Wants to filter dog-walkers by experience" and “Confused about how to select a dog walker from the list” In this case, you’d create a new group called “Dog walker selection.” It’s part of the process to come up with groups as you go.

Continue until there are no sticky notes remaining

Try to categorize as many of your sticky notes as possible, which will ensure that all feedback from participants is represented in distinct groups. Ideally, you should end up with three to ten groups.

If there are a few sticky notes that don’t belong in any of the groups you made, that’s normal; sometimes only one person in your study had a problem with a feature or experience. But you should strongly consider the observation or quote, and determine if it should stand alone in its own group or receive further consideration before disregarding it entirely.

Do a second review

The beauty of affinity diagramming is that there are no “right” answers. You can make as many or as few groups as your observations require. Take some time to review your groupings and determine if you want to move any sticky notes around, or even make a new group. Have fun with your data and the connections you can draw from it. You might end up with a really unique group that you didn’t notice at first!

Here’s a pro tip: If you have a lot of sticky notes within a group, you should consider creating sub-groups to further organize the data. It's almost like doing the affinity diagramming exercise all over again, but with a subset of the sticky notes.

Create your own affinity diagram

When you have a lot of research data to sort through, it can be overwhelming to hunt for patterns and make a plan for iterating on your product. Creating an affinity diagram helps you group together research insights so that you can further understand and define the problems in your product and design.

In addition, affinity diagramming helps you think outside of the box. The interactive and visual format of affinity mapping allows you to make connections within your data that you may not have noticed by simply reading through your notes. This helps you think of new, creative ways to solve user problems.

Now it's your turn to sort through research data, and have some fun while you’re at it. Remember, there’s no right or wrong way to group data in your affinity diagram. Play with your sticky notes and come up with unique groupings. It’ll be worth the effort!

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Affinity Diagramming: Collaboratively Sort UX Findings & Design Ideas (nngroup.com)⁠

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Patterns and themes in research data

You've now learned how to gather all of the data from your research in one place and organize it so that it's easy to understand.

Now it's time to find themes in that data. To do this we'll ask ourselves two key questions.

What common patterns have you identified in the data that you've collected and

what did they tell you about the product design?

To identify themes? The best place to start is with your affinity diagram.

As we discussed in an earlier video affinity diagrams, help you organize the data from the note taking spreadsheets into broad groupings or patterns.

We use colorful sticky notes to create visual representations of these patterns.

After creating your affinity diagram, take some time to observe which sticky notes have been grouped together into categories.

Areas of the affinity diagram with multiple sticky notes usually represent a pattern and later each pattern becomes a theme.

Start by taking the data from the pattern and then expanding on it.

Connecting the pattern to the user's experience is the best way to do this.

For example, the first pattern is being able to book a dog walker repeatedly.

So our theme might be: Most participants feel that being able to make a re occurring booking would offer them more options on the app.

The second pattern be observed for four out of five participants was being surprised there is no confirmation page before completing checkout.

So our main theme might be: Most participants want to confirm the details for the dog walking session before booking.

Thanks to our data being organized in the affinity diagram, we can quickly identify themes.

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Qualities of strong insights

First, strong insights are grounded in real data. Insights need to be based solely on what you observed during the research study, not what you felt at the time.

And each insight should be supported by multiple pieces of data.

Insights are strongest when they apply to multiple study participants instead of just one.

It's okay to have outliers of course. Not everyone will agree, but the more of your participants that feel the same way, the stronger your insight is.

We would write an insight based on the theme,

Most participants want to book a dog walker on a regular basis.

Our insight might be, users want to book a dog walker on a scheduled basis instead of making a one-time reservation.

Second, strong insights need to answer the research questions you listed in your research plan.

You want to tie your insight to the research questions to help people understand why the insight matters.

Third, strong insights should be easy to understand. Keep in mind that your stakeholders might not

have been involved in the planning of your study, but you still want them to understand your insights.

Use simple language that doesn't require detailed knowledge of the study.

Fourth, strong insights increase empathy for the user experience.

Empathy increases the team's engagement because they put themselves in the user's shoes.

That extra level of commitment can fuel their enthusiasm to improve the product.

Finally, strong insights inspire direct action.

For example, an insight that states: "The dog walker app is useful" does not suggest an action.

But an insight that states: "Users want to book a dog walker on a scheduled basis instead of making a one-time reservation," tells the team that this part of the user experience needs to be adjusted.

Remember, UX research is all about identifying problems, finding solutions, and testing those solutions.

The most valuable insights include suggestions for putting a solution into action.

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We got to find a solution which works for a wide variety of people and not necessarily for a subset of people.

In the process of solution design, which comes after a study is complete, it is very important to really understand not only what the problem was, but also why the problem occurred in the first place.

Once you fall in love with the understanding of the problem, then you are much more equipped to

come up with solutions and find solutions which might not have been thought of in the first place.

Now, you have defined a solution for the problem that existed in the small space, but how does that solution work, and how does that solution scale to the rest of your experience, is also an important part.

Keeping the entire holistic experience end-to-end in mind is very essential to coming up with any solution for problems which are being identified for the product.

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Course 4 Week 3 - Glossary⁠

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