Lead scoring
Lead scoring is a model that ranks records by expected conversion, and it is only valid when it is calibrated against realized outcomes.
A defensible model separates fit scoring from intent scoring, because they decay differently: fit is stable, intent is perishable. Combining them into one number hides the fact that a high score can mean a perfect-fit account that did nothing, or a poor-fit account that read everything.
The scoring model is a hypothesis about conversion. Calibration, comparing predicted rank to realized SAL and opportunity rates by decile, is what turns it into a measurement. Uncalibrated point systems accumulate rules for years and end up ranking on whatever behavior is easiest to trigger.
Where it breaks
Point values were assigned in a workshop three years ago and have never been tested against outcomes.
Related terms
- Marketing qualified lead (MQL)
- An MQL is a record that has met a documented, enforced threshold of fit and intent, and that marketing is formally handing to sales.
- Ideal customer profile (ICP)
- An ICP is a testable specification of the accounts a company can serve profitably and repeatably, expressed in attributes the revenue system can actually evaluate.
- Intent data
- Intent data is third-party or first-party behavioral signal used to infer that an account is actively researching a purchase.
- Data enrichment
- Enrichment appends third-party attributes to records so that fit can be evaluated from data the buyer did not have to supply.
Field notes on this
- The MQL debate needs an acceptance record
A recorded acceptance decision makes lead-quality disputes inspectable. It is a signal, not a complete diagnosis of demand performance.