Using Data-Driven Insights for Better Design with Adobe Express.

Summary/Overview

Data-driven design means using different data points to inform decisions often relating to aspects of user experience (UX) and user interface (UI) design. Simply, it’s about making designs better and more user-friendly. This is a core component of intelligent design and makes a great idea usable.

Luckily, your business will most likely have a range of data to inform your creative decisions. Whether it’s using customer feedback and purchase data to improve your product designs or optimising your website based on the way users navigate each page, there are endless ways to use data to enhance your business.

In this article, we’ll focus on the key elements of data-driven design and how you can use data-driven insights for better design with Adobe Express.

What do we mean by data-driven design?

Designers aren’t users (or at least can’t replicate the experience of every user) and so without insider knowledge, products and websites can sometimes be difficult to use.

Imagine this – you design a door. It’s a door that says PUSH. In clear letters embossed on the door it says push – of course you’d push it! But for the sake of design consistency there’s a handle on both sides.

Oh no, someone has now pulled on the handle, and everyone is looking. That’s not a problem you picked up in testing because you designed it to push. But your data shows that 20% of people pulled it. That data demonstrates an issue you could correct with data-driven design.

Look at it another way, data-driven design can help you fix problems you may not have known existed. You can identify behaviours from users and implement data-driven design solutions to make things even better (before you’re told.) You could even use data-driven insights to better tailor your product to your target audience.

What different types of data can you use to inform your designs?

There are two distinct categories of data you can use to inform your design decisions. They often focus on the what and whys of user behaviour.

Quantitative data.

Quantitative data focuses on measurable and numerical datasets for insights into user behaviours and trends.

An example of this could be counting clicks onto specific links or portions of the page. This could guide future layout decisions. Quantitative data is good for getting a sense of the what, when and how of a behaviour such as, what number of people pulled on the push door? from the data.

Quantitative testing methods could include:

• Analytics tools
• Data samples
• Tracking software
• Closed-questionnaires or surveys.

Qualitative data.

Where quantitative data works in the realm of the measurable and numerical, qualitative data focuses on the experiential. This observation of subjective user opinions, feelings or motivations gives a solid answer to the why’s of user behaviour. For example, why did you pull the push door?

Examples of qualitative testing methods include:

• Interviews, survey and questionnaires.
• A/B testing.
• Results.
• Usability tests.

Free data-driven design examples.

Why is data-driven design so important for user experience (UX)?

Data-driven design thinking lets you create your product, service, webpage or advertisement from the ground up with your users in mind – even if they’re not fully aware it’s an issue. With behavioural data points and rigorous testing, you can inform designs both current and future.

• Get insights into what’s working. Data-driven design thinking doesn’t just tell you what needs to be changed – it lets you know what’s working. Then you can figure out why it’s working to learn from those principles.
• Spot quick wins that could help improve your design. Is your data pointing out some obvious flaws? Is the click rate on a certain section too low? Maybe people aren’t interacting with your product or service in ways you thought. Spot issues quickly with data insights to make swift changes to your design.
• Remove guesswork. Take the mystery out of issues with readable results that tell you where and what the problems are. This can help you build a business case for changes.
• Improve decision-making. Make decisions with confidence and by the numbers. With data-driven insights you can improve your designs to get the results you want.
• Boost efficiency. With data-driven insights, you can boost your team’s efficiency. Ideation can focus on solutions rather than guesswork on the problems.

How to use Adobe Express to create data-driven designs.

Use data-driven design practices with Adobe Express to boost you designs. With a suite of tools (and some handy templates) you can bolster your workflows and create designs fit for purpose.

1. Use data insights to inform your brand assets.

Use Adobe Express to build out a brand kit, complete with your key assets. Create logos, colour palettes and other on-brand designs informed by data-driven insights and add them into your very own Brand. You can then instantly apply these design elements to future creations in one click.

2. Customise your existing designs based on user data.

With data-driven insights, you can easily customise your existing designs based on data – not guesswork. For instance, say you’ve just tested out a new webpage template. You can save this template to your favourites and then easily edit and amend the design based on the user data you collect over a set period of time.

Alternatively, you can use the Bulk, Create and Generate tool to create multiple versions of a single design. These different variations can then be tested to see which one performs best for your business. This could be particularly useful when A/B testing a social media campaign, experimenting with different product page layouts or trialling a new menu design.

3. Use Adobe Express to visualize data.

With free infographic, charts and reporting templates, you can easily turn your data insights into visual insights. That way, you can share important metrics with your team and start your next project with all your data points in an easy to digest format.

It could also help when pitching a large design change to the wider business.

4. Create advertisements that land.

Use data-driven insights to inform your advertisement designs and discover what resonates with your target audience. Try a range of designs in minutes with free advertisement templates from Adobe and see what works best.

Apply your own data to these editable designs.

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Useful things to know.

What are some useful data sources for designers?

Both qualitative and quantitative data sources are useful for designers for different reasons. Analytics tools are a great way to source data passively to get a sense of user behaviours. Other common methods of data acquisition include A/B testing, usability testing, surveys and questionnaires, heatmaps and click tracking.

What is an example of data-driven design?

An example of data-driven design could be used in making a bespoke experience for users. For example, Amazon uses data-driven insights to create individually relevant recommendations for consumers to boost their shopping experience. Similarly, the introduction of profiles on Netflix was based on user data, testing and feedback.

What are the challenges with data-driven design?

Data-driven design isn’t as easy as looking at the data and jumping to a conclusion. It requires a balance of quantitative and qualitative data acquisition. It’s also important to be able to determine if the data is outdated, incomplete or flawed. Analysis paralysis can be an issue if you have too many data points – especially if they’re conflicting.

While data-driven design is powerful it has to be used intelligently and with the human experience at the forefront of decision-making.

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