The GTM teams pulling ahead aren’t just sending more emails or making more dials. They’re using modern machine learning and first-party data to predict the value of their pipeline before they generate it, and using that to drive where they spend time, how they prioritize outreach, and which channels they use to engage. Join Harrison Rose (CEO, Goodfit) for a tactical session on how to move beyond gut feel to build a data-driven picture of pipeline value across your entire market - before you start to build it. What you can expect - How to classify your entire market by expected value: Understand how to use classification models and first-party data to assign expected dollar values to accounts, without relying on generic intent signals. - Matching expected value to execution: Learn how expected value gives clarity into which GTM channels work for each account, with real examples of how this changes day-to-day execution. - How to balance automation with human judgment: Explore how top teams are using AI to support better decisions without losing the critical thinking and experience that drive results. - A practical framework for getting started: Walk away with a clear understanding of what data you need (first-party and third-party), how to build feedback loops from wins, replies, and touchpoints, and how to operationalize this without a data science team.