Case Study: Sales Intelligence and Customer Segmentation Dashboard
Client: Mr. Robert, CEO of ‘Global Retail Mart’ Role: Data Analyst and BI Expert Objective: To transform fragmented sales data into an interactive dashboard and provide data-driven insights for business growth.
1. Problem Statement
‘Global Retail Mart’ faced a common but critical challenge: data overload without insights.
Unstructured Data: Last year’s sales records were messy and unoptimized.
Lack of Visibility: The CEO could not identify high-performing areas vs. areas of financial waste.
Undefined Customer Base: There was no clear idea of who the “high-value customers” were.
2. My Strategic Workflow (Solution)
I followed a 3-step scientific method (method) to solve this project:
Phase A: Data Cleansing and Transformation (Foundation)
Data cleaning is the most important thing before starting any major analysis.
Data Scoping: All the messy data is consolidated and duplicates and incorrect entries are removed.
Integration: Data from different sources is brought into a central format.
Phase B: Interactive Dashboard Creation (Visual)
A dynamic dashboard is created as per the buyer’s needs that shows real-time data:
KPI Tracking: A system to see total sales, number of orders and profit margin at a glance.
Regional Performance Map: Identify which regions are doing well and where the costs are high through a map.
Interactive Filter: The facility to filter data by date, region and category.
Stage C: Advanced Customer Segmentation (Insights)
Here I used the RFM (Recency, Frequency, Monetary) model:
Best Customers: Those who make regular and large purchases.
At-Risk Customers: Those who were regular in the past but have now reduced their purchases.
Potential Loyal: New customers who may become large customers in the future.
3. Final Results and Business Recommendations
Here is a sample of your report:
Result: After looking at regional performance, it was found that 'Region X' has high marketing spend but low sales. On the other hand, 'Region Y' has satisfactory sales despite low spend.
Recommendation 1: Reduce the marketing budget of 'Region X' and invest in 'Region Y' to increase ROI (return on investment).
Recommendation 2: Launch a loyalty program to make it easier to retain the "best customers".
4. Tools used in this project
Dashboarding: Power BI / Tableau
Data Analysis: Microsoft Excel (Advanced) / Google Sheets
Documentation: Professional report PDF.
