Most mortgage lenders focus all their effort on new leads—while aged leads sit untouched in their CRM.
But one national lender saw things differently. Instead of pouring more budget into acquisition, they asked:
“What if we could re-engage the leads we already have?”
The result?
An 83% increase in lead re-engagement—driven entirely by predictive lead scoring.
Here’s how they did it using ProPair, and how your team can unlock the same kind of hidden revenue.
The Challenge: Thousands of Cold Leads, Zero Visibility
This lender had a high-performing sales team, consistent lead flow, and strong initial response times.
But after 10–15 days, their follow-up stalled. Reps lost interest in “cold” leads. Pipeline velocity slowed. And their CRM filled up with:
- 🧊 Aged leads marked “not ready”
- 🗑️ Leads deprioritized based on surface behavior
- ⏱️ Missed re-engagement windows
They didn’t need more leads. They needed smarter prioritization.
The Strategy: Predictive Scoring for Re-Engagement
They turned to ProPair, a predictive AI platform built to score leads based on actual conversion probability—not assumptions or fixed CRM rules.
What ProPair did:
- Ingested 12 months of historical lead + outcome data
- Built a machine learning model to identify re-engagement patterns
- Scored every aged lead based on similarity to past closed-won deals
- Re-ranked lead queues and routed high-potential aged leads to the right loan officers
Within weeks, reps were re-engaging leads they had previously ignored—with confidence backed by data.
The Results
- 🔁 83% increase in aged lead re-engagement
- 📈 32% increase in second-attempt conversions
- 🧠 Higher rep confidence in following up on “cold” leads
- 💰 More pipeline value recovered without new lead spend
What changed? The reps didn’t work harder. They worked smarter—focusing only on aged leads with a high likelihood of converting.
Why This Worked
Predictive scoring outperforms manual guesswork because it:
- Learns from your closed-won/closed-lost history
- Prioritizes leads based on real-world patterns—not gut feel
- Continuously improves as outcomes feed the model
- Surfaces hidden opportunities buried in your CRM
Most CRMs treat aged leads as liabilities. ProPair treats them as a second-chance pipeline.
Re-Engagement Before vs After ProPair
| Metric | Before Predictive Scoring | After ProPair Implementation |
| Aged Lead Re-Engagement | Low, ad hoc follow-up | +83% increase |
| Lead Queue Visibility | Flat, time-based | Prioritized by conversion fit |
| Rep Response Confidence | Low | High |
| Second-Touch Conversions | Under 10% | Over 30% |
| Revenue Recovered | Inconsistent | Predictable and growing |
The Big Lesson
Every CRM has value hiding in plain sight.
With predictive AI, Sales Ops and lending teams can unlock that value without more spend, more reps, or more tools.
It’s not about chasing harder. It’s about scoring smarter.
Want to Recover More from the Leads You Already Own?
If you’re sitting on hundreds—or thousands—of aged leads, your next 10% revenue lift may already be in your pipeline.
👉 Schedule a demo with ProPair and see how predictive lead scoring can turn ignored leads into engaged borrowers—automatically.
