Platform module
Scoring Model Health
14 automated checks to evaluate lead scoring models, threshold calibration, score distribution, and scoring-to-lifecycle alignment.
Audit results
14 checks · live
Threshold calibration
Your MQL threshold is 60 but the median converted lead scored 42.
Score-to-conversion correlation
Lead score has weak correlation (0.18) with deal conversion.
Score decay configuration
No score decay rules — engagement from 6+ months ago carries full weight.
+11 more findings
Why does lead scoring accuracy matter?
Lead scoring is the bridge between marketing and sales. When scores don't reflect buyer intent, sales wastes time on unqualified leads while hot prospects go cold. Miscalibrated thresholds mean your MQL definition is meaningless — and pipeline quality suffers.
Sample findings
Examples from a real scoring audit
Every check produces a finding with severity, an impact estimate, and a step-by-step fix.
Threshold calibration
Your MQL threshold is 60 but the median converted lead scored 42.
Estimated Impact
Sales missing 38% of historically high-converting leads.
Solution
Recalibrate MQL threshold based on actual conversion data.
Score-to-conversion correlation
Lead score has weak correlation (0.18) with deal conversion.
Estimated Impact
Scoring model not predicting buyer intent.
Solution
Review scoring properties and rebalance behavioral vs demographic signals.
Score decay configuration
No score decay rules — engagement from 6+ months ago carries full weight.
Estimated Impact
Stale leads still surfacing as MQLs.
Solution
Add a score decay rule for engagement properties older than 90 days.
All 14 checks in this module
Featured findings above are 3 of the most impactful. Here's the complete list.
Questions
Scoring audit questions
How do I know if my HubSpot lead scoring model is working?
Test it against outcomes, not intuition: if high-scoring leads do not convert at a higher rate than low-scoring leads, the model is not predictive. RevTrace checks score-to-conversion correlation, score distribution across your database, threshold calibration, and whether scores actually drive the lifecycle transitions they are supposed to.
What is a good MQL score threshold?
The right threshold is the point where conversion rate rises sharply, which is specific to your data — a copied threshold from another company is arbitrary. A useful warning sign is distribution: if most of your database clusters just above or just below the line, the threshold is set where it cannot discriminate between leads.
What is score decay in lead scoring?
Score decay reduces a lead's score as their activity ages, so someone who downloaded an ebook a year ago does not look as engaged as someone who did it yesterday. Without decay, scores only ever climb and your MQL pool fills with stale leads. RevTrace checks whether decay is configured and whether the window is realistic for your cycle.
Scoring module
14
automated checks
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