Working with data as a designer

Data and Design. While the alliteration is undeniable, the two words often seem to be opposed to each other. That doesn’t need to be the case, though. Your design can vastly improve with the right application of data. But how do we do that? Let’s take a look.

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What do we mean by “data”?

It’s important to start with this question because it can often mean different things to different people.

While some take it to refer to hard numbers, statistics and quantitative data only, others choose a broader definition and include results from qualitative research and customer feedback.

The latter works better for two reasons:

1. Qualitative data struggles to receive the same kind of attention and importance as hard numbers.
2. It does a much better job of explaining user behaviours and motivation, which is needed to really address issues spotted through analytics.

Quantitative and qualitative data complement each other. While analytics can show you what’s happening, it doesn’t answer why it’s happening. Qualitative data from research and customer feedback fills in those blanks.

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Quantitative data

Quantitative or analytic data involves tracking how users interact with a product. This can include metrics such as the number of clicks on a button, the amount of time spent on a page or step in a journey, and the number of users who complete a specific task. By analysing this data, product teams identify patterns and trends in user behaviour and use this information to improve the design of their products.

The most common way you can employ quantitative testing is by the use of “A/B testing” which involves deploying slightly different variants of a solution to different audiences for a certain amount of time. Usage metrics from both audiences are tracked and analysed to understand which variant performed better. The one that did better is then usually deployed to all audiences. Companies like Google are famous for A/B testing even tiny parts of their interface like different shades of UI colours to get maximum impact out of their designs.

Note of caution – This is not to be confused with testing different solutions in usability testing. That’s a qualitative research method aimed at figuring out typical issues faced by target users. A/B testing comes in much later, towards the end of the workflow and usually needs the support of engineers and data analysts.

The results of A/B testing tell you what’s happening. Qualitative research and data answer the “why”.

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Qualitative data

Qualitative data can be broadly split into two categories: customer research data and customer feedback.

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Customer research

This involves gathering insights directly from users through methods such as interviews, focus groups, and surveys. Customer research can provide valuable insights into how people think, feel, and behave when using a product. It provides answers about their goals and motivations, and why they behave a certain way. By incorporating this data into the design process, UX designers can create designs that are more in line with the needs and preferences of their target audience.

This research is usually done before or at the start of a project so that it can provide visibility and direction to a team’s efforts. It can be done either by an external research agency, or if you’re a scrappy startup, by something as simple as a few online surveys. Design research is a huge field, and if you’re looking to get started with it for your project, you can check out this article for some tips.

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Customer feedback

This type of data collection involves gathering insights from users after they have used a product. This can happen through customer support channels, feedback forms, and online reviews. Some common ways to collect customer feedback is through metrics like NPS (Net Promoter Score) which is traditionally sent as an email survey asking customers how likely they are to recommend the service or product to a friend.

Within apps, customer feedback is usually gathered by inserting feedback prompts at strategic points after a user has undergone a key journey that the app aims to serve. For example, a dating app might ask a user to provide feedback after they’ve received a match to understand their experience. By analysing this data, UX designers can identify common pain points, user behaviour patterns and areas for improvement in their designs.

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Wrapping up

Good design solves real problems and lets people complete their tasks easily. As a designer in the digital realm, it can be tough to know if you’re doing that unless you use data to inform and refine your designs.

Use data as you would any other tool in your arsenal, and you’ll find yourself growing as a designer much more quickly than you anticipated. All the best!

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