6Sense
Chief Revenue Officer
Building systematic revenue infrastructure to address steep learning curves, black-box AI trust issues, and SMB churn while scaling from current $250M ARR target through improved ICP alignment and automated workflows.
6Sense has leading AI prediction technology but suffers from implementation friction, trust barriers, and ICP misalignment driving churn. The revenue organization lacks systematic workflows to convert platform capabilities into predictable growth, with manual processes creating bottlenecks in the 6-12 week setup cycle and poor SMB market fit undermining unit economics.
$180M ARR (72% of target)
$250M ARR (roadmap target)
$320M ARR (28% above target with accelerated enterprise expansion)
Core Opportunity
6Sense leads in AI prediction technology but faces implementation friction, trust barriers, and ICP misalignment driving churn. The company has strong market position but needs systematic revenue infrastructure to convert platform capabilities into predictable growth.
Execution Thesis
Deploy AI-powered ICP optimization, global workflow automation, and predictive revenue intelligence to eliminate implementation friction, reduce churn, and achieve 2x ACV/4x win rate improvements — building the systematic revenue machine that converts leading AI technology into $250M+ ARR performance.
Production systems, not theory. Revenue captured, not demos given.