The how of data-driven UX design
It is unmistakably evident that data-driven UX design will bring significant benefits to your digital product. But how do you go about implementing a data-driven UX design approach?
Step 1 – Collect the data
First up, it’s crucial to understand the different forms that data can come in, so that’s where we are starting with the collection process. Data comes in two main forms – qualitative and quantitative. However, this isn’t about a quantitative versus qualitative debate, rather it’s about combining the two approaches to fully understand customer behaviours and usage, and to drive decisions that are as informed as possible.
Quantitative data is, very simply, numerical data that shows who is taking an action, what they’re doing, when they’re doing it, and where they’re doing it. For example, survey and A/B testing.
Quantitative data is usually obtainable in larger volumes and at scale. On the flip side, however, sample sizes need to be adequate enough to achieve a confidence level and to be ‘statistically significant’ and collecting data in larger volumes can take time. Finally, quantitative data can tell you what, but it can’t tell you why – why customers are behaving in a certain way or what’s driving them to take specific actions.
With qualitative data, we’re dealing with information and feedback that demonstrates the why and how, so it’s typically expressed in non-statistical means and often called ‘unstructured data’. For example, interviews and focus groups.
Qualitative data provides rich insights, helping your team to develop a deeper understanding of the challenge or pain point at hand. Typically, sample sizes are smaller and so can be quicker to work through. That said, you still need to ensure the data is significant enough – for that, we advise using diminishing returns to find the correct sample size. What’s more, be sure to allow for sufficient time after data collection to analyse it, as qualitative data is much more hands-on!
With both quantitative and qualitative data, there are two main ways in which you can collect it: primary and secondary methods.
This is when you typically run the data collection process yourself, such that the results are yours exclusively. While this approach can be expensive and ‘in the moment’, it is the closest type of data you’ll get to the origin and source of the information. For example, Google Analytics.
Secondary data is existing research or information that you draw on from outside your organisation, sometimes called desk or secondary research. Often, this method is faster, lower cost, and provides more background and context. On the other hand, that context may be quite different to yours so this should be considered. For example, white papers and journals.
Top tips from the Adrenalin team on collecting your data
Get the rest of your product team involved in the user research – ask them to sit in on sessions you’re running so they can see how real customers are interacting with their product. Believe us, it makes all the difference!
Have two UX team members in as many research sessions as possible so one can focus on running the session and one can focus on taking notes. Then swap the roles to get the best spread of insights.
A quick note: Adrenalin will be releasing a FREE guide on data collection for brand, marketing and digital leaders and digital product owners. As part of the guide, we will include a comprehensive checklist of quantitative methods, qualitative methods, primary sources and secondary sources. Subscribe to our newsletter (at the bottom of this page) to avoid missing out.