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CASE STUDY

Optimizing E-Commerce with Customer Segmentation and Targeted Marketing

AT A GLANCE

A customer segmentation and targeted marketing solution was developed using RFM modeling and K-means clustering, optimizing marketing strategies, improving customer retention by 15%, and reducing marketing costs by 10%

Client information

Company Name
A Leading Consumer Electronics Manufacturer
location
Mississuaga, Ontario
SIZE
Medium-Sized Business
INDUSTRY
Consumer Electronics
Services Provided
Customer Segmentation Analysis
10%
Savings from the the overall marketing budget, reducing unnecessary expenditures.
15%
Increased retention rates, strengthening loyalty and driving repeat purchases.
20%
Reduction in repeat purchase cycles, increasing purchase frequency to 1.8 times per quarter from 1.5 times.

CHALLENGE

The client needed to analyze customer spending patterns to improve online promotions, segment customers based on purchasing behavior and frequency, and identify loyal customers to enhance retention strategies. Their goal was to better understand customer preferences and optimize marketing efforts to drive loyalty and increase revenue.

SOLUTION

Beam Data implemented a comprehensive e-commerce customer segmentation solution using an RFM (Recency, Frequency, Monetary) model to evaluate purchasing behavior and identify high, medium, and low-value customers. By consolidating transactional data, product details, customer journey information, and third-party demographic data, the team applied K-means clustering to segment customers effectively. Data visualization tools like Tableau were leveraged to communicate findings and drive informed decision-making.

 

IMPACT

  • Reduced Marketing Costs: Targeted marketing for identified customer clusters saved 10% of the overall marketing budget, reducing unnecessary expenditures.
  • Improved Customer Retention: Tailored campaigns for high-value customer segments increased retention rates by an estimated 15%, strengthening loyalty and driving repeat purchases.
  • Optimized Customer Experience: By offering the right products at the right time, repeat purchase cycles were shortened by 20%, increasing purchase frequency to 1.8 times per quarter from 1.5 times.
  • Strategic Geographic Insights: Identified key regions with high-value customer clusters, refining marketing and service strategies for increased sales opportunities.

TOOLS

SQL Server
Tableau
Excel

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