User Behavioral Analytics

Published by Rahul on

For any digital product, behavioral analytics is crucial. It is a set of data that helps managers understand user journey through the product, feature adoption, and find users of interest.

Why behavioral analytics?

The business environment is digital and hyper-competitive. Identifying potentially churning customers in advance will have a definitive upside on the bottom line.

For Customer Success

If a product is offering a trial or a free version, it is very important for outbound teams to understand what is the interest level of the user? Which users are showing an inclination toward premium features? All this data is easily available from the behavioral analytics tool.

B2B products that have multi-user licenses need to track the behavior of an entire account across all the users. An account-based cohort will help account management process with all the data they need during the reach out.

Product Improvement

Product managers can easily find the friction points in each feature. In long run, feature heat maps help product managers understand which features are driving product growth.

Journey analysis for successful trial users vs churn users can help understand the fine gaps at the user experience level. This data will help product managers to create a roadmap to reduce user churn.

Anatomy of a Behavioral analytics tool?

For an effective product and behavior analytics tool, there are some must-haves.

Data Collection and quality of Data

The quality of data you have on the platform will determine how deep you can dive at user behavioral analysis.

  • Collect all user events like click actions, time spent on pages, and the API responses. Choose platforms that collect all this information without too much engineering effort like Fibotalk.
  • Data should be easily configurable by labeling systems to mark valuable data.

Usage Analysistrend analysis for specific user actions

Custom dashboards should be supported to help build trend analysis of different user actions based on multiple dimensions. Different managers should be able to focus on their KPIs using.

In Fibotalk, we have added custom dashboards and reporting tools. Now different teams can build their own dashboards with their KPIs and many reports.

Cohort Analytics

It is super important to get the list of users based on the common segmentation criteria like

  • users losing interest
  • super users
  • Used certain features or combination of used and not used features
  • Login frequency and time
  • # of times certain action is done and many more
deep dive at per user level in Fibotalk application

Advanced filters and saving options should be there for quick access. For B2B multi-user license products, account based cohorts should be offered.

Check how we do it in Fibotalk

Feature analytics – Friction and adoption

This is a very very hard problem for analytics. A feature is essentially a user journey across multiple actions like page opens, clicks, form and database operations. Users may be facing challenges at any of these stages.

It is super important to understand which user is at which stage, what are the friction points, and the whole funnel of the feature. If the quality of data is not good, this can be an ineffective analysis. That’s why we track all user events so we can ensure retrospective analytics as well.

In Fibotalk, you can just define this feature flow as blueprint and all analytics is directly presented.

Just configure the flow and get adoption preview
Heatmap to compare different feature adoptions
Adoption distribution, funnel analysis and usage frequency, All automatically generated

User Journey Analysis

It’s all about user journey. You should be able to deep-dive into specific types of journeys like successful payment, feature X used etc. Fibotalk supports many representations for user journey analysis.

Filters to track specific journey

page distribution per stage from all users to an individual


User behavioral analytics is crucial for digital products to understand how different features are getting adopted, which users are of high value, and compare different types of user journeys based on multiple dimensions. It is essential to choose analytics platforms that provide rich data of user activities and tools to deep-dive.

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