video1.0<iframe src="https://www.loom.com/embed/5635304400044cbababb6d2a4355f754" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/5635304400044cbababb6d2a4355f754-63756d735c3868c7.gif347.328This Loom explains how to use AI-generated customer personas to tailor marketing and revenue strategy. Personas are created after you have at least 1,000 enriched customers and AutoSignal groups customers into six personalized profiles based on shared traits. The Persona Analytics page shows match rate, typically around 80% with examples like an 89.4% match rate, plus how much of the customer base each persona represents versus the revenue it drives (for example, a persona that is 10% of customers but 31% of revenue). It also details how to interpret repeat rate and average days between orders for win back flows, along with demographics, geography, product affinity, and core customer samples, noting each customer is assigned to the closest persona.