AI Real Estate Sales Machine View packages

Guide

Real estate lead scoring: how to rate leads HOT, WARM or COLD

A sales team has limited hours. If every lead gets the same effort, the serious buyers wait while the casual browsers get long calls. Lead scoring fixes that with a simple rule: give points for signs of real intent, then work the highest scores first.

What to score

SignalExample points
Budget matches your inventory+25
Plans to buy within 3 months+25
Loan pre-approved or no loan needed+15
Replied to your message+10
Agreed to a site visit+20
Decision maker is on the call+5
Budget far below your lowest price-20
No reply after 3 attempts-10

These numbers are a starting point. Adjust them to match what has actually converted for your project.

Turn points into categories

Review monthly

Look at your last 20 bookings. What did they have in common at the time of the enquiry? If most were "buy within 3 months", give that signal more points. Scoring is a habit, not a one-time setup.

Do it in Excel without macros

You do not need expensive software. A spreadsheet with a few formulas can total the points and label each lead automatically. The CRM in the AI Real Estate Sales Machine does this with editable points, a follow-up queue and a dashboard, using formulas only, so there is nothing to enable.

Next: the follow-up message sequence to use for each category.