Market Report
Account Scoring ROI
Four companies replaced guesswork with a ranked queue, and the results showed up within 30 to 60 days.
Better data won't fix flat MQL conversion. A ranked queue will.
The ROI from account scoring doesn’t come from better data. It comes from rep behavior change. When reps have a ranked, explainable queue, they stop working unsorted MQL lists and start calling the accounts most likely to close. This report shows what that looks like across four companies, in numbers.
Chartio saw a 40% increase in trial-to-paid conversion and MQTs that were 5x more likely to become paying customers after replacing single-signal scoring with a multi-signal model.
Read this if you’re generating MQL volume but struggling to translate it into pipeline:
- See why ROI comes from behavior, not data: Learn why a ranked queue, not more signal, is what changes rep output and drives conversion.
- Diagnose your scoring architecture: Find out if your model is producing a ranked queue or a binary gate, and why that distinction drives pipeline.
- Review four cases with hard numbers: Chartio, MarketMuse, OutSystems, and Cockroach Labs each saw measurable improvement within 30 to 90 days.
- Audit your model for single-signal bias: Get five prioritized recommendations for improving adoption and conversion without buying more tools.
- Test whether your signals reach your reps: See how CRM-native delivery, not more data sources, is what drives the improvement.