Duration
Complexity
Contributors
User researcher, Data scientist, Design analyst, UX designer, Developers
When a product is used by the users, the way they use the product has definite data patterns of what users are actually doing with it. It also can clearly show patterns of what users are not doing.
Design analytics is a way to make products better by using data to understand a customer's needs. It is all about understanding how users interact with a product. By measuring and analyzing user activity, designers can get insights into what's working well and what needs to be improved.
To get started on design analytics, here are a few steps:
Define the design goals and metrics: The first step in design analytics is to define the goals and metrics that will be used to measure the impact of design. This may involve defining metrics such as user engagement, conversion rates, or user satisfaction.
Gather data: Gather data from various sources like analytics tools, surveys, interviews, and usability tests. It’s important to ensure that the data collected is relevant to the design goals and metrics.
Analyze data: Analyze the collected data to identify patterns, trends, and insights. This may involve using statistical analysis, data visualization, or other analytical techniques.
Communicate the findings: The insights gained from the analysis should be communicated to stakeholders in a clear, concise, and actionable manner. This may involve creating reports, dashboards, or presentations.
Iterate and refine: The insights gained from design analytics should be used to inform the design process and make iterative improvements to the product or service. This may involve testing design variations, implementing new features, or refining existing ones.
Measure the impact: The impact of the design changes should be measured using the same metrics defined in step 1. This will help to validate the effectiveness of the design changes and identify areas for further improvement.
Analytics could be used with Qualitative and Quantitative research methods.
Quantitative research is studying something using numeric and objective data gathered from genuine sources.
In case of product design, this data is collected from actual product usage and UX research methods like surveys, satisfaction ratings etc.
Usage data is collected from what people are actually doing with the product, not what they are saying or being told to do. Hence, it is the most unbiased form of data.
Some examples of data that is popularly tracked using analytics is:
User flows
Click through
Conversion
Completion rates
Drop off
Business goals
Acquisition
Bounce rates
Audience
User counts
Unique users
Returning Users
Funnels
The data clearly shows patterns of ‘What’ users are doing or not with the product. For finding ‘Why’ or reason behind these patterns, Qualitative research methods need to be used.
This is performed by methods like interviews, usability tests, etc.
This research helps in understanding reasons behind patterns.
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GoogleAnalytics
SmartLook
CrazyEgg
Using Design Analytics to Identify and Solve Actual Problems from Oracle Blog.
Data-informed design: Getting started with UX analytics from MixPanel.
What is UX Analytics? from UXCam.
How to Leverage UX Analytics for Data-Driven Product Design from STXNext.
The ultimate guide to Google Analytics for UX designers from UX Collective.
Basics of User Research
Secondary Research