Element / Retail - Intelligent Lead Scoring for Campaign Optimization
Intelligent Lead Scoring for Campaign Optimization
Problem :
Coco Republic was investing heavily in ad campaigns without a reliable method to prioritize high-quality leads. Sales teams spent time chasing cold prospects, and marketing lacked precision in targeting, reducing ROI across digital efforts.
Solution :
A lead scoring and propensity model was built using 15,652 training records and validated/tested with over 6,700 additional records. Key variables included user engagement (visit time, frequency), geographic and technographic data, category preferences, and campaign interactions. The model applied optimized thresholds to balance lead quality with sales opportunity volume.
Outcome :
The business successfully identified and converted 5,082 high-value leads from a pool of 320,912. Conversion rates improved to 1.5%, with 6,393 total orders and an average session duration of 10 minutes. The model enabled smarter campaign targeting and reduced ad waste.