E-Commerce & DTC

RFM Customer Segmentation Dashboard

D
D2C Fashion Brand
3 weeks
4 Technologies

Key Results

693

Customers segmented into actionable groups

11

Distinct segments for targeted marketing

3x

Improvement in email campaign ROI

1The Challenge

The marketing team was sending the same email campaigns to all 693 customers with no personalization. They had no visibility into who their best customers were, who was at risk of churning, or how to prioritize retention efforts.

2Our Solution

Built an interactive RFM (Recency, Frequency, Monetary) segmentation dashboard that automatically categorizes customers into actionable segments like Champions, Loyal, At Risk, and Lost Customers, enabling targeted marketing strategies.

Our Approach

1

Extracted order data from e-commerce platform and calculated RFM scores for each customer

2

Designed scoring algorithm: Recency (days since last purchase), Frequency (order count), Monetary (total spend)

3

Created 11 distinct customer segments based on RFM score combinations

4

Built interactive dashboard with filters for segment deep-dives and customer lists

5

Added trend analysis showing segment migration over time

RFM Customer Segmentation Dashboard — data analytics case study by Alfa Analytics

The Impact

693

Customers segmented into actionable groups

11

Distinct segments for targeted marketing

3x

Improvement in email campaign ROI

Technology Stack

Power BISQLPythonRFM Analysis

Project Details

Client

D2C Fashion Brand

Industry

E-Commerce & DTC

Duration

3 weeks

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