Decoding Customer Behavior: Who Buys, Who Stays, Who Leaves?
Overview
This project aims to understand customer behavior by grouping customers into different segments based on their purchasing habits. These insights empower businesses to create personalized marketing campaigns, improve customer retention, and drive overall growth.
Key Findings
1. Customer Groups (Clusters) Identified
We have successfully categorized customers into four main groups based on their shopping behavior:
- Cluster 0: Occasional Buyers
- Characteristics: Low spending and infrequent purchases; haven’t purchased recently.
- Suggested Action: Offer small discounts or time-limited deals to encourage repeat purchases.
- Cluster 1: At-Risk Customers
- Characteristics: Previously active but have not bought anything in a long time; low engagement and lower spending.
- Suggested Action: Re-engage with personalized emails, special discounts, or loyalty incentives.
- Cluster 2: Frequent & Loyal Customers
- Characteristics: Shop regularly with moderate spending.
- Suggested Action: Provide loyalty points, referral bonuses, or exclusive perks to strengthen retention.
- Cluster 3: High-Value Customers
- Characteristics: Frequently purchase and spend the most.
- Suggested Action: Give them VIP treatment with early access to products, premium offers, and exclusive support.
2. Customer Distribution
- At-Risk Customers (Cluster 1) make up the largest group.
- High-Value Customers (Cluster 3), while fewer in number, contribute the most revenue.
- Frequent & Loyal Customers (Cluster 2) represent a strong segment that should be nurtured.
Takeaway: The business should focus on re-engaging at-risk customers while rewarding high-value and loyal customers.
3. Customer Spending Behavior
- High-Value Customers (Cluster 3) spend significantly more than the other groups.
- At-Risk Customers (Cluster 1) have low spending and require re-engagement.
- Loyal Customers (Cluster 2) display a balanced spending pattern.
Takeaway: Use exclusive discounts and loyalty programs to maximize value from Clusters 2 and 3.
Visual Insights: Understanding Customer Behavior Through Data
Distribution by Cluster
- A bar chart of customer distribution shows that most customers are in Cluster 1 (At-Risk).
- Despite their small numbers, Cluster 3 (High-Value Customers) drives a significant portion of revenue.
Spending Trends
- Cluster 3 boasts the highest average purchase value, indicating premium buyers who are less price-sensitive.
- Cluster 1 has the lowest average transaction value, signaling the need for re-engagement strategies.
Visualization Insights:
Box plots and trend charts clearly contrast low-value customers needing intervention with high-value customers who contribute significantly to revenue.
Business Impact & Next Steps
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Retention of High-Value Customers:
These are the backbone of revenue generation. Focus on VIP programs and premium support.
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Re-Engagement of At-Risk Customers:
Prevent revenue loss by targeting these customers with personalized offers and promotions.
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Tailored Marketing Strategies:
Adapt marketing efforts based on each segment’s behavior to maximize customer lifetime value (CLV).
Action Plan: Maximizing Customer Engagement & Retention
| Customer Group |
Key Characteristics |
Engagement Strategy |
| Occasional Buyers (Cluster 0) |
Make purchases sporadically. |
Offer small discounts & time-limited deals to encourage repeat purchases. |
| At-Risk Customers (Cluster 1) |
Previously engaged but now inactive. |
Re-engage with personalized emails, special promotions, and loyalty incentives. |
| Frequent & Loyal Customers (Cluster 2) |
Regular purchasers with steady engagement. |
Provide loyalty perks, referral bonuses, and exclusive membership benefits. |
| High-Value Customers (Cluster 3) |
Top spenders with consistent high-value transactions. |
Offer VIP treatment, early product access, and premium customer service. |
Final Takeaway
Understanding these customer segments allows the business to:
- Personalize marketing efforts based on customer behavior.
- Enhance retention rates by focusing on at-risk and occasional buyers.
- Maximize revenue by nurturing loyal and high-value customers.
By implementing these strategies, businesses can make smarter marketing decisions, drive engagement, and build long-term customer relationships.
Next Steps
- Implement targeted promotions based on the cluster insights.
- Monitor customer movement between segments over time.
- Automate the real-time classification of new customers.
Understanding customers = Smarter decisions = Business growth!