Tomás Delgado-Wren

Behavioral data beats firmographics for predicting which users will adopt features.

Standard stickiness metrics hide collaborative feature failures in multi-seat accounts.

Whole-product and feature activation measure different things and need different thresholds.

How to measure feature discovery in ways that actually reveal what's broken.

Define adoption metrics precisely or your dashboard will lie to you.

PLG teams need product usage signals, not lagging CRM data, to forecast accurately.

Define exit criteria upfront to retire features that usage data shows truly don't matter.