This repository documents a lead scoring system designed to evaluate and prioritize inbound leads using data and behavioral signals.
The full implementation is private. This repository explains what the system does at a high level.
If you want to see the model, review the logic, or discuss real-world use cases, contact me directly.
For each lead, the system outputs:
- A lead score from 0 to 100
- A qualification level: High, Medium, or Low
- The key signals that influenced the score
This allows sales and marketing teams to focus on the leads most likely to convert.
The model can work with a wide range of data, including:
- User or company information
- Engagement and behavior signals
- Source and acquisition channel
- Custom business rules
Inputs are flexible and can be adapted to different businesses and pipelines.
The system is designed to stay simple, explainable, and easy to integrate into existing workflows.
- Clear and explainable scoring logic
- Handles messy, real-world data
- Easy to customize and extend
- Built for practical sales and marketing use
- Python
- Data processing logic
- Rule-based and weighted scoring
The full model and scoring logic are not public.
If you want:
- A demo
- A walkthrough
- Access to the implementation
Reach out to discuss.