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Smart Customer Segmentation

F&B Brand · Food & Beverage

Developed ML models for automated customer segmentation, enabling precision marketing campaigns.

-28%
CAC Reduction
+42%
Conversion Rate
-55%
Unsubscribe ↓
31%
Email Open Rate

! 挑战

The F&B brand was spending significant marketing budget sending the same campaigns to all customers, resulting in low ROI and high unsubscribe rates.

我们的解决方案

Built an ML pipeline segmenting customers into 12 micro-groups based on behavior, preferences, and purchase frequency, coupled with automated A/B testing.

成果

  • 28% reduction in Customer Acquisition Cost
  • 42% increase in campaign conversion rate
  • 55% decrease in unsubscribe rate
  • Email open rate improved from 12% to 31%

技术栈

Python scikit-learn XGBoost Airflow BigQuery Looker

项目周期

3 months

关键成果

28% lower CAC, 42% higher conversion

Tags

Machine LearningMarketingSegmentationPython
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