Customer Retention Analysis for a Musical E-Commerce Firm (Quantum Analytica - Experential Learning)
Description
As part of academic program (Experiential Learning), worked on providing a end to end solution to address the business objective of Improving the Customer Retention for a Musical Ecommerce Firm.
Solution
- Developed an interactive dashboard to analyse repurchasing patterns of customers by analysing in house orders data collected over past 10 years.
- Identified the duration between the repeat purchases for each product.
- Analysed trends in repurchases, change in repeat purchase rate over years & business from new customers vs returning customers.
- Furthermore Implement Apriori analysis to find the associations in the frequently purchased products.
- Based on the analysis the dashboard also provided a comprehensive list of target customers that will be used by the marketing team to initiate targeted email campaigns.
- Dashboard Implementation
Environment
- Python (Numpy,Pandas,Plotly,Streamlit)
- Heroku
Data Visualizations
Analysis 1 : Top 10 Trending Product Categories
Analysis 2 : Change in the Repeat Purchase Rate Over 10 Years
Analysis 3 : Total Number of Orders from New Customers Vs Repeat Customers
Analysis 4 : Total Revenue from New Customers Vs Repeat Customers
Analysis 5 : Apriori Analysis
Analysis 5 : Identifying the Duration between Repeat Purchases for a Product
Results:
On studying the associations between the categories in the dataset we see that,
- There is a strong relation between BB trumpet, Mouthpieces, and Cases & Gig Bags with a confidence of 52% and a lift value of 1.49.
- Correlations between mutes and mouthpieces, repair services and mouthpieces, cornets and mouthpieces, valve oil and mouthpieces with a confidence greater than 30%.
- Valve Oils are purchased after a median of 269 days, Mouthpieces after 141 days, and cases and gig bags after 279 days.
Based on the observations made, client can make recommendations to their customers with target email campaigns.