There are two major benefits of using data driven design. It allows you to:
- Make informed design decisions based off real user needs
- Prioritize what issue to solve based on its relative impact for users
However, as with any tool, it can be a double-edged sword. As bias exists through the process of data collection and analysis, there is a risk that data can be used for the sake of arguing for a point of a view rather than a way to improve the design process.
Types of Data
Before going further, let’s define the two types of data that can be collected:
- Quantitative data: numerical data (such as analytics or statistics) which tells you things like how many visitors your site received, click rates, success rates, etc.
- Qualitative data: non-numerical data which helps to tell you about the how or why of your users’ behavior.
Madness in Your Method
A classic risk of data-driven design is that the collected data may look exact and precise, whilst the research method may actually be biased. One can also go to the extreme and end up collecting a mass of low quality data, rather than focusing on quality and relevant topics.
Data is also not the be all end all solution. By itself, data does not and cannot capture the whole story as some factors, which may not be measurable, could be very important: emotional responses, context, changing set of users, and so on.
Worth the Effort
But on the other hand, data-driven design does allow you to get buy off from a diverse group of stakeholders and increase empathy for the end user. Therefore, it is important to use data from a variety of sources to combat bias (for example: A/B testing, analytics, site visits, etc.) and use research in a meaningful way to track trends and explore new features, rather than proving a specific point.
Now go forth and test! Here are some resources to help you collect data:
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