Also known as Lead score
A simple rule-based score adds points for signals: budget matches available inventory (+20), wants to buy within three months (+20), answered the first call (+10), visited a site (+30), home loan pre-approved (+10); and subtracts for signals such as three RNR attempts in a row or a wrong number. Teams then work leads above a threshold first.
Scores only help if they are checked against outcomes. Every quarter, compare the scores of leads that booked with those that did not; if they look the same, the weights are wrong. Keep the reasons visible next to the score, because a telecaller who sees “budget fit, visited, loan approved” can use that on the call, while a bare “72” tells them little.
Example
Two leads, one morning (illustrative)
A Bengaluru telecaller has 40 callbacks. Lead A: 2 BHK in Whitefield, budget ₹95 L, wants to move by March, answered yesterday — score 70. Lead B: “any property”, no budget, three RNRs — score 10 (illustrative weights). She calls A first and schedules B for an evening attempt, rather than working the list in arrival order.
Figures are illustrative, not market rates.
Questions about Lead scoring
What is a good lead score?
There is no universal number; a score only means something within your own model. Set a threshold by looking back at past bookings — for example, the score most booked leads had reached before their site visit — and adjust it each quarter as your inventory and sources change.
Is a lead score the same as hot, warm and cold?
They express the same idea at different precision. Hot, warm and cold are three buckets an agent picks by judgement; a score is calculated from recorded signals. Many teams calculate a score and then show it as a temperature so it is easy to read on a call list.
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