10 Steps to Creating a Data-Driven Design Culture

Photo by Mel Poole on Unsplash

What is data-driven design?

Data-driven design is an approach in which decisions are made based on both quantitative and qualitative data, leaving personal (gut) feelings or opinions aside.

Why do we want to be data-driven?

In short: products designed with users in mind are more likely to succeed.

  • Who are our users?
  • Why are they using our product?
  • What is the value of our product?

Data-driven design 101: where to start

1. Do a design audit

Start by doing research. Good news: you’re on the right track since you’re already reading this article! But with all seriousness, audits help you understand where your company stands in terms of design maturity. We started by asking questions about the data:

  1. Do we know how many people visited this page during the past month?
  2. Do we know how many people are using our product via desktop or mobile phone?
  3. Do we know how many people signed up last week?
  • Data: Start asking questions about your product’s usage. Collect everything you want to know (including existing and missing data) into one document, and use it as a backlog.
  • People and resources: Talk with people to learn as much as you can about the product, users, and how work is being done.
  • Procedures and tooling: Find out which design methods and tools are being used and how information is being shared.
Stages of UX maturity, image courtesy of nngroup.com

2. Data-driven culture starts at the top

One of the mistakes I have seen in the past when trying to build a data-driven design culture is goals not being aligned between teams and upper management.

  • CEO shares data insights during a company-wide all-hands meeting.
  • Team leads share monthly reports (based on data) during the all-hands meeting as well as in written form in chat.
  • We challenge each other (both leaders as well as individuals) during weekly product sync meetings by asking, “do we know how many users…”, “do we know why…”, and more.

3. Set specific goals

After joining Qminder, I asked myself immediately: “Where do we want to be at the end of 2021?”

  1. We measure the impact of what we create (for example, when we release a new feature, we have methods to measure whether the feature is performing well or not).
  2. We make decisions based on the data we have collected (this means we won’t start working on a new project just because we like the idea; instead, the idea is backed with data).
  3. We collect quantitative data where the results can be presented in numbers, i.e., “how many, how often or how much”, and qualitative data where the results take the form of observations, interviews, feedback, and feelings and answer to “why”.
Photo by Karla Hernandez on Unsplash

4. Start collecting quantitative data

Product analytics

We need data to get a bird’s-eye view of what people are doing and understand how the product works. We had already created a backlog of questions that need answers. With the help of product and development teams, missing tracking events were added to the code. The next step was to find a data analytics tool that would allow everyone from the company to explore patterns in data, find answers, and share their findings.

Surveys and questionnaires

Surveys and questionnaires are easy to use and low-cost ways to produce a combination of quantitative and qualitative data.

Measuring visual design and aesthetics

Visual design and aesthetics are often quite hard to measure and therefore categorized as subjective matters. One of the interesting ways to measure a design is by looking at how it makes users feel and what words they associate with it.

5. Start collecting qualitative data

Once you have gathered insights on what people are doing, it’s time to deep dive into your users’ behavior, problems and needs.

  • Writing down the most important things I need to find answers for (that answered to why).
  • Getting the most out of Hotjar. I started watching screen recordings that captured thorough user behavior, like mouse hovers, clicks, and scrolls. This helped me understand what users actually do. For instance, I discovered a new user flow; I found out that users couldn’t find a search option and spend over half a minute doing a manual search instead; and how often a specific user group used a feature that we didn’t know they even needed.
  • I started experimenting with on-page surveys. For example, I began asking users, “What’s the one thing we should change on this page?”, “What other information would you like to see on this page?”. In addition to getting feedback about the product, we discovered a few bugs while doing those surveys.
  • Quantitative data sets a great foundation for understanding user behavior and helps identify UX trouble spots.
  • Qualitative data reveals users’ needs by creating a new narrative to the story.

6. Analyze the data

So you have the data? Great. But we’re far from over.

7. Hire a product researcher

You cannot, and should not, do everything alone. I’m lucky to have a really supportive team that trusts me 🤗 Right after joining the company, I recommended hiring a product researcher. The team heard my reasoning on the value of user research, and we posted the job ad soon after.

8. Show your work

Showing how design and research impacts business goals is important for learning and improvement, as well as sharing knowledge and increasing transparency in the company.

  1. Weekly syncs between product, development, design, and research.
  2. Separate Slack channel called #design-showcase where design and research team share their work such as feature updates, visuals of UI, new design system components, research reports, upcoming plans, work in progress, etc. This channel is also an opportunity for people from other teams to ask questions and share their perspective.
  3. Presentations at company-wide meetings. I think that’s one of the most important ones — you can include everyone and provide context by covering why, how, and what you’re working on.
  4. Sharing know-how and articles about UX, research, and data-driven design. Once again, we have a specific channel for that — #read.

9. Review your goals

Goal-setting is an ongoing process, and you need to constantly review your goals if you want to succeed.

Photo by Daniel Öberg on Unsplash

10. Form a habit of data-driven mindset

It’s a big commitment to adopt data-driven design practices. You might complete all the steps at once, but the key to success is to keep the momentum going. Being systematic and forming a habit of a data-driven mindset is what prevents the organization from falling back.

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Heidi Taperson-Lelumees

Heidi Taperson-Lelumees

I’m passionate about building digital products — providing delightful user experience while solving complex business problems.