Portfolio Case Study: E-commerce Sales Performance & Customer Segmentation
1. Project Overview
The main objective of this project was to analyze the sales data of an e-commerce company for the last one year and segment them based on customer behavior. This analysis made it easier to determine the business growth and customer retention strategy.
2. Key Business Questions
What was the monthly sales trend or trend in the last one year?
Who are our top 10 customers who spent the most?
How can we differentiate customers based on their purchasing power and activity (e.g. VIP vs. At Risk)?
3. Technical Solution and Logic
a) Monthly Sales Trend
A line chart has been created using 'Order Date' and 'Sales Amount', which shows the seasonality and monthly ups and downs of the business.
b) Customer Segmentation Logic
I used the following calculated field logic in Tableau to understand the importance of customers:
VIP Customer: Those who have made at least 3 purchases and have a total spend of more than $1000.
Logic: IF {FIXED [CustomerID] : COUNTD([OrderID])} >= 3 AND {FIXED [CustomerID] : SUM([SalesAmount])} > 1000 THEN "VIP Customer"
At Risk (those we are losing): Those who have spent more than $500 but have not placed any more orders after August 1, 2025.
Logic: IF {FIXED [CustomerID] : MAX([OrderDate])} < DATE('2025-08-01') AND {FIXED [CustomerID] : SUM([SalesAmount])} > 500 THEN "At Risk"
Regular Customer: All other regular customers.
c) Top 10 Spenders
Using filters and sorting mechanisms, the top 10 customers who are generating the most revenue for the business have been identified.
4. Interactive Dashboard Features
I have created a 'One-Click' interactive dashboard where 'Action Filters' have been used. Through this:
Selecting a specific Region changes the entire report according to the information of that region.
It is possible to directly view the list of VIP or At-Risk customers and their sales information by clicking on the Customer Segment chart.
5. Results (Impact & Insights)
Informed Decisions: Quickly identify regions or categories where sales are declining.
Customer Retention: Create opportunities to bring back 'At Risk' customers by launching special offers or email campaigns.
VIP Treatment: Paves the way for loyalty programs for top spenders.
Tools Used: Tableau Desktop, Advanced Calculations (LOD Expressions), Data Visualization.
