A Power BI dashboard built to analyze churn behavior across 6,687 customers for a business strugg...A Power BI dashboard built to analyze churn behavior across 6,687 customers for a business strugg...
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A Power BI dashboard built to analyze churn behavior across 6,687 customers for a business struggling with unclear retention insights. The dashboard combines geographic churn mapping, category-wise breakdown (Competitor, Attitude, Price), root-cause analysis by churn reason, and demographic segmentation by age group — all powered by Power Query for data modeling and DAX for calculated measures like churn percentage and churn weight. Key finding: price sensitivity drove 62% of churn, and customers under 30 represented the highest-risk segment at 56.6% of total churn weight. The result is a single-page, self-service view that lets stakeholders prioritize retention strategy by actual cause instead of guesswork.
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Mo's avatar
Strong cause-first framing, Muhammad. One guardrail I’d add is separating share of churn from churn rate within each segment: 56.6% of churn weight among under-30 customers could reflect risk, segment size, or both. Pair that with customer value and intervention cost, then...
Muhammad Sohail's avatar
thanks for feedback
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