The Challenge.
- Often, companies only segment customers based on spending (average spend per transaction or total spend).
- There is a lack of understanding of the purchase behavior of different customers.
- All customers are targeted the same way, with no customized interactions based on customer loyalty or value.
The Solution.
- Built a segmentation model to categorize customers by recency of purchase, purchase frequency, amount spent, and other factors.
- Identified different four different segments with different behavior patterns in terms of loyalty, purchase frequency, tendency to purchase on sale or at full price, etc.
- Output the results to a dashboard to track customer segments on a monthly basis and identify trends.
The Results.
- Customized customer interactions and promotional campaigns by segment.
- Reduced promotional costs by targeting promotions only to customers more likely to buy on sale.
- Increased sales by targeting different segments in different ways.