Πωλήσεις

Lead scoring

Σύντομη απάντηση

Scoring leads by fit with the ideal customer profile and by behaviour, so the team works the highest-probability opportunities first.

Βασικά συμπεράσματα

Start from customers won in the last 12 months and identify shared attributes
Score fit and behaviour separately; a good-fit but inactive lead needs a different action than an active but poor-fit one
Recalibrate quarterly against real outcomes

What it is

Lead scoring assigns each lead a score on two axes: how well it fits the ideal customer profile (industry, size, region) and how active it is (requests, opens, visits, replies).

Building a model that works

Start from customers won in the last 12 months and identify shared attributes

Score fit and behaviour separately; a good-fit but inactive lead needs a different action than an active but poor-fit one

Recalibrate quarterly against real outcomes

The common mistake

Copying models from other industries. A score that works in B2B software does not transfer to distribution, where order frequency and geography weigh far more than digital engagement.

Πραγματικό παράδειγμα

A 12-rep team cut time spent on poor-fit leads by 40% after the score was recalibrated on actual won customers rather than marketing assumptions.

Ενημέρωση: 2026-07-17

Συχνές ερωτήσεις

How much data does a useful model need?+

Roughly 50-100 closed opportunities, won and lost. Below that, the score reflects noise rather than pattern.

Does lead scoring replace human qualification?+

No. It orders the work queue; the qualification decision stays with the rep, based on the conversation.

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