It’s not unusual for designers to omit data-driven design from their workflow, simply because of the unfair myths surrounding analytics and the way that data-driven design is conducted.
Psychology studies and UX studies are mistakenly thought to be sufficient enough as an informant, since the results are tested in a controlled environment and defined by large sets of data. But while the information is certainly useful (I mean, it’s fine to regard the results of user studies as best practices, for example), what’s missing from these experiments is the fact that the test subjects aren’t necessarily our users.
Without data collected from our audience, it’s easy to make assumptions or be without the other half of the story.
Let’s take a look at 5 myths about data-driven design that might change the way you look at using analytics for UX design.
Myth #1: “Analytics Aren’t My Responsibility”
Oh, hell no ?♂️. Data is definitely 100% your responsibility, regardless of what your primary role is in a team. If you’re a marketer, you need to know conversion rates to see if your marketing strategy is working. If you’re a developer, you need to know conversion rates to see if your code is bugging out somewhere. If you’re a designer, you need to know conversion rates to see if the user experience is optimal. What marketers, developers and designers all have in common is the same business goal of helping users convert.
Product managers have to care about all of those things, although each team member collectively has a responsibility to improve metrics using the skill and knowledge of their field.
TL;DR: analytics are everyone’s responsibility.
Myth #2: Data = Numbers
Data can be the heatmap from a user test, the answers from a customer survey, a scrap of feedback from a teammate. Anything that informs our decision-making is data. However, many of us make our first mistake when we assume that usability testing and surveying are alternatives to analytics, where in fact analytics lives and breathes at the center of all user research.
Analytics helps you ask the right questions for your customer survey, define the right user groups for usability testing, and identify where exactly the UX is falling short so that you can run A/B tests on those areas and find design solutions.
TL;DR: data isn’t just numbers, but analytics comes first.
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