Customer Cohort Analysis Dashboard

Power BI Case Study

Interactive Power BI dashboard analyzing customer retention, repeat purchases, cohort performance, customer lifetime value, and revenue trends.

Project Overview Watch Demo Try Live Dashboard
Power BI DAX Power Query Cohort Analysis Customer Analytics

Project Overview

This dashboard helps businesses understand how customer groups behave over time after their first purchase or first engagement period.

Business Focus

Customer retention, repeat purchases, cohort behavior, and revenue contribution across acquisition periods.

Dashboard Goal

Help decision makers identify strong and weak customer cohorts and improve retention strategy.

Tools Used

Power BI, DAX, Power Query, data modeling, customer analytics, and interactive reporting design.

Video Walkthrough

Watch a quick walkthrough of the dashboard layout, filters, and customer cohort insights.

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Business Problem

The business needed a clear way to understand customer retention, repeat purchase behavior, and revenue contribution across different customer acquisition periods.

Without cohort analysis, it can be difficult to know whether new customers continue buying, which acquisition periods perform best, and where customer drop off starts happening.

Solution

I created an interactive Power BI dashboard that groups customers into cohorts and tracks their behavior over time. The report helps identify which customer groups are retained, which periods perform best, and where the business may need to improve customer engagement.

Key Features

Tools Used

Power BI DAX Power Query Data Modeling Customer Analytics Business Intelligence

Business Value

This dashboard helps businesses understand customer retention patterns, identify valuable customer groups, monitor customer lifetime trends, and improve customer engagement strategies.

Dashboard Highlights

Key areas this dashboard helps business users analyze.

Retention Visibility

Shows how customers continue engaging after their first period and where drop off may occur.

Revenue Tracking

Helps compare revenue contribution across different customer cohorts and time periods.

Customer Behavior

Provides insight into repeat purchase behavior and customer activity trends.

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