Chat with us!We built an AI lead-scoring engine for a real estate brokerage that predicts which inquiries are most likely to transact, so agents spend their time on the...
We stopped guessing. The model tells us who to call first, and the numbers prove it works.
Brokerage Sales Director
We built an AI lead-scoring engine for a real estate brokerage that predicts which inquiries are most likely to transact, so agents spend their time on the leads that actually convert.
| Project Detail | Information |
|---|---|
| Project Type | Web |
| Industry | Real Estate |
| Technologies | Gradient-boosted models, Python / scikit-learn, Feature store, PostgreSQL, FastAPI, React |
| Delivery Partner | mTouch Labs |
| Primary Outcome | Agents focused on high-probability leads, lifting conversion while reducing wasted outreach. |
Agents chased every lead equally, wasting effort on low-intent inquiries while hot prospects cooled. There was no data-driven way to prioritize a flood of portal and web leads.
We trained a predictive model on historical lead and transaction data, blending behavioral signals, property interest, and engagement to produce a calibrated conversion-likelihood score.
The platform scores and ranks every incoming lead in real time, explains the key drivers, and routes hot leads instantly to the right agent.
Conversion-likelihood prediction
Model training and evaluation
Real-time signal serving
Lead and outcome data
Real-time scoring API
Agent lead dashboard
Unified lead, behavioral, and transaction history.
Built predictive signals from engagement and intent.
Trained and calibrated scoring models against outcomes.
Deployed real-time scoring with instant lead routing.
Added drift detection and periodic retraining.
Agents focused on high-probability leads, lifting conversion while reducing wasted outreach.
Predictive lead scoring turned an undifferentiated lead pile into a prioritized pipeline, directing agent effort where it pays off.
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View case studyWhat businesses ask us most often about this project and how we built it.
It is a predictive model that estimates how likely each lead is to convert, so teams can prioritize outreach to the highest-intent prospects.
It blends behavioral signals, property interest, engagement history, and past transaction outcomes to produce a calibrated score.
Yes. Each lead shows the key drivers behind its score, so agents understand why it ranked where it did.
We monitor for drift and retrain periodically so the model keeps pace with changing market behavior.
High-scoring leads are routed instantly to the right agent so they are contacted within minutes.
mTouch Labs combines AI-powered development with deep industry expertise to deliver solutions faster.
