Project: Advanced Cohort Analysis for Retention Rates and CLV Calculation
Leveraging advanced analytics to understand customer retention and lifetime value.
Client: E-commerce in Fashion and Beauty
Challenge
The e-commerce client needed to understand their customer retention rates over different time segments and calculate Customer Lifetime Value (CLV) to inform their marketing and customer retention strategies.
Solution
I conducted an advanced cohort analysis to calculate retention rates for different time segments, including a 90-day retention rate, and eventually calculated CLV.
This analysis provided valuable insights into customer behavior and helped the client develop strategies to improve retention and maximize customer value.
Key Actions:
Cohort Analysis: Developed complex SQL queries in BigQuery to calculate cohort tables with cumulative calculations.
Retention Rate Calculation: Analyzed retention rates over various time segments, providing a detailed view of customer retention.
CLV Calculation: Calculated Customer Lifetime Value (CLV) to understand the long-term value of retaining customers.
Data Visualization: Utilized Looker Studio to create dynamic and insightful dashboards for easy interpretation of retention rates and CLV.
Technical Details:
Tools Used: SQL in BigQuery, Looker Studio
Query Complexity: The SQL query involved multiple Common Table Expressions (CTEs) and exceeded 3000 characters, showcasing advanced SQL skills.
Responsibilities: Cohort analysis, retention rate calculation, CLV calculation, data visualization
Impact:
Strategic Insights: Provided the client with a clear understanding of customer retention patterns and the financial impact of retaining customers over time.
Improved Retention Strategies: Enabled the client to develop targeted retention strategies based on detailed cohort analysis.
Maximized Customer Value: Informed marketing and customer service efforts to maximize Customer Lifetime Value, driving long-term profitability.
View the Query:
Check out the detailed SQL query for cohort analysis on my GitHub.
