What is Design Analytics?


Generally, design analytics is an ongoing process that begins at the planning and discovery phase and continues throughout the design process.




User researcher, Data scientist, Design analyst, UX designer, Developers

Getting Started

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:

  1. 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.

  2. 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.

  3. Analyze data: Analyze the collected data to identify patterns, trends, and insights. This may involve using statistical analysis, data visualization, or other analytical techniques.

  4.  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.

  5. 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.

  6. 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

  • 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:

  1. User flows

    1. Click through 

    2. Conversion

    3. Completion rates

    4. Drop off

  2. Business goals 

    1. Acquisition

    2. Bounce rates

  3. Audience

    1. User counts

    2. Unique users

    3. Returning Users

  4. 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.

Qualitative Research

  • This  is performed by methods like interviews, usability tests, etc.

  • This research helps in understanding reasons behind patterns.

Do’s & Don'ts



  1. Be clear on what to track and measure

  2. Prioritize user stories to track

  3. Use metrics to evaluate

  4. Note any issues

  5. Test and iterate

  6. Collaborate with stakeholders

  1. Don’t gather everything of everything

  2. Don’t overlook the context in which analytics data was collected

  3. Don’t ignore privacy concerns

  4. Don’t focus solely on vanity metrics

  5. Don’t neglect to communicate your analytics insights to stakeholders

Suggested Tools 

  • GoogleAnalytics 

  • SmartLook

  • CrazyEgg


Other Related Best Practices

  • Basics of User Research 

  • Secondary Research