lead-ai-customer-predictor

Lead.AI Customer Predictor

Model repo target: arun-gharami/lead-ai-customer-predictor

Lead.AI Customer Predictor classifies customer quality and churn likelihood for salons, stores, agencies, and small businesses.

Service message: "Find which customers are likely to buy again."

Business Output

• Hot Lead
• Normal Lead
• Churn Risk

Use this output to prioritize outreach, automate nurture campaigns, and export scored leads to CRM.

Features

• customer_tenure
• total_spent
• last_purchase_days
• visit_count
• email_open_rate
• discount_usage
• support_tickets
• satisfaction_score

Project Files

• data/data.csv - synthetic Kaggle-ready dataset
• dataset/README.md - dataset card
• train_model.py - training pipeline and metrics export
• model/model.joblib - serialized model artifact (generated after training)
• model/metrics.json - evaluation report (generated after training)
• app.py - Gradio demo for live scoring + CSV upload
• sample_api_usage.py - API integration example
• push_to_huggingface.py - publish project to Hugging Face model repo

Local Training

pip install -r requirements.txt
python train_model.py
python app.py

Sample API Payload

{
  "customer_tenure": 24,
  "total_spent": 3400,
  "last_purchase_days": 8,
  "visit_count": 42,
  "email_open_rate": 0.76,
  "discount_usage": 0.12,
  "support_tickets": 0,
  "satisfaction_score": 9.1
}

Evaluation Snapshot

• Accuracy: 0.8267
• Train/Test split: 80/20 stratified
• Metrics artifact: model/metrics.json

Pricing

• Starter: $49/month
• Business: $149/month with CRM export + team workflows
• Custom AI Setup: $499-$1,500 one-time

Publish to Hugging Face

export HF_TOKEN=hf_xxx
python push_to_huggingface.py