Author – Ken Hobson.
Smart lead scoring sounds complex, yet the idea is simple: pay attention to what people do online, give each action a number, add the numbers up, and ping your team when someone looks ready to buy or sell.

Below is a plain-English guide.

What Is Predictive Lead Scoring?

Predictive lead scoring is an AI system that watches every click, email open, and form fill, then works out how close each person is to taking the next step—like booking an inspection or signing an agency agreement.

• It looks at past deals to learn which behaviours led to success.

• New leads are compared to that pattern and given a score—usually 0–100.

• When a score crosses your “hot lead” line (often 70+), you receive an alert in real time.

Why It Matters to Your Business

• Faster follow-up: Hot prospects get personal calls within minutes, not days.

• Less guesswork: Stop chasing every browser window-shopper; focus on those most likely to list or buy.

• Higher conversion: Targeted attention means more signed authorities and fewer missed buyers.

• Happier clients: Helpful messages arrive when buyers are engaged, not when they have moved on.

The ABCs of Turning Behaviour into Scores

1. A – Assemble Data

   • CRM notes, portal enquiries, website analytics, email stats, call logs.

2. B – Build a Model

   • Feed last 12–24 months of “won” and “lost” deals into your scoring tool.

   • The AI spots patterns (e.g. viewed floor plan + downloaded contract = high intent).

3. C – Categorise Leads

   • Set score bands:

     • 0–39 = Cold

     • 40–69 = Nurture

     • 70–100 = Hot

4. D – Deliver Alerts

   • Choose channels: push notification, SMS, or Slack/Teams ping.

   • Include next-step suggestion: “Call now to book inspection.”

Behaviour Signals That Really Move the Meter

(Add or replace signals to match your own data sources.)

Step-by-Step: Build Your First Scoring Workflow

1. Export Past Deals

   • Mark each as Won or Lost so the AI sees winners and non-starters.

2. Clean the Data

   • Fix duplicate contacts, merge spelling variants of suburbs, tag missing phone numbers.

3. Pick a Tool (see list below).

4. Train and Test

   • Most tools auto-split data: 80 % for training, 20 % for testing.

   • Aim for an accuracy above 70 %.

5. Set Score Thresholds

   • Decide where “hot” begins. You can adjust monthly.

6. Automate Alerts

   • Use built-in workflows or connect via Zapier/Make.

7. Review Monthly

   • Compare scores to real deals to keep the model honest.

Quick Example: A One-Hour Setup

1. Connect your website, email platform, and CRM to a predictive scoring app.

2. Import last year’s contact list with deal outcomes.

3. Let the AI crunch numbers (10–15 minutes).

4. Create an automation: “If score ≥ 75 then SMS salesperson with contact and property link.”

5. Test by visiting a listing page repeatedly—watch your phone buzz.

Getting Started Checklist

• Choose which behaviour signals to track today.

• Export 12 months of leads with status Won/Lost.

• Trial one scoring tool on a freemium or demo plan.

• Set a “hot” threshold and connect instant alerts.

• Block out 30 minutes each week to fine-tune scores and actions.

Key Takeaway

Predictive lead scoring turns raw clicks into clear priorities. With the right signals, a simple model, and fast alerts, you’ll spend less time guessing and more time closing the deals that matter.