What is UX analytics?
UX analytics refers to analyzing user behaviors and actions on the digital product or website to see how the users engage with the UI elements and their overall experience. The ultimate goals of UX analytics are to find hidden friction in the user flow and get the insight to improve user experience.
The most common ways to do UX analytics are quantitative and qualitative data measurements. Qualitative UX data measures subjective data from user interviews, such as surveys, VOC(Voice of customers), or recording actual user sessions and finding users' pain points. Quantitative UX data measures numeric data such as NPS(Net Promoter Score), CSAT(Customer Satisfaction), or success rate and measures the specific metric to analyze user experience.
Types of UX analytics
Both qualitative and quantitative data methods are essential to get better insights from UX analytics, but both ways require different tools to measure the data.
Qualitative UX data analytics
The most common way for qualitative data analytics is through session recordings.
Session recording provides the user’s activity on the website or product, such as clicking, tapping, and scrolling each page. This provides the UX issues that real users are struggling with and functionality problems.
Also, surveys on the website or product with simple opened-ended questions or surveys about detailed user experiences are another common way to gather qualitative data.
Lab usability testing is a common option for collecting qualitative data. Moderated usability testing by watching user interaction with the product or website can help to gather qualitative data.
Learn more about usability testing.
Quantitative UX data analytics
Quantitative data for UX analytics is measurable. It uses numeric data to understand if users have good or bad experiences and if they are satisfied or not with the product or website experience.
The standard data for this method include the following:
- NPS score (Net Promoter Score): to see how likely a user would like to recommend the product to others.
- CES(Customer Effort Score): to see how much effort users need to put into finishing a task on the product or website.
- Success Rate: See the percentage of users who completed the task, like signing up for a paid subscription or engagement rate of a new product feature.
Fortunately, many tools can help track this data for UX researchers. Heatmaps, product analytics, and survey tools can help gather these quantitative data.
However, quantitative data doesn’t explain why and there are no absolute criteria for it, so conducting qualitative research will help better understand and interpret quantitative data.
Benefits of UX Analytics
Improving user experience on the product or website is the key to revenue growth. There are core benefits of UX Analytics:
- Opportunity to identify the issues
- Understand user behavior and implement insights into the design process.
- Answer questions like ‘Why is the customer retention rate so low?’
- Optimize user journey and remove the friction
UX analytics provides the overview of user experience on the product or website and helps find the best UX strategy to provide a seamless user experience. It also helps to understand low customer retention and find the best way to maximize conversions. UX data analytics should include quantitative and qualitative data analytics. Choosing the right metric and tools is also essential.