Early Experience Variance Reduction
by Dan Hockenmaier • Head of Strategy and Analytics at Faire
A renowned marketplace expert who previously worked at Thumbtack during its scaling phase and founded the strategy consulting firm Basis One. He is considered one of the world's leading authorities on marketplace dynamics, growth models, and unit economics.
🎙️ Episode Context
Dan Hockenmaier deconstructs the complex mechanics of building and scaling marketplace businesses, contrasting them with traditional SaaS models. He provides a masterclass on constructing growth models, defining true liquidity, and making high-stakes strategic decisions regarding verticalization and expansion.
Problem It Solves
Fixes retention issues by addressing the root cause (bad first impressions) rather than trying to resurrect churned users.
Framework Overview
A method to improve retention by identifying and eliminating the 'bad luck' scenarios in a user's first week, thereby homogenizing the onboarding experience toward the mean or better.
🧠 Framework Structure
Segment new users by their first-week...
Identify the bottom quartile of exper...
Implement product interventions (guar...
Measure the downstream retention of t...
When to Use
When retention curves are flattening at a lower-than-desired rate, or when early churn is high despite a seemingly good product.
Common Mistakes
Focusing on 'resurrection' campaigns (emailing people who left 6 months ago) instead of fixing the onboarding variability.
Real World Example
Uber and Lyft using 'earnings guarantees' for new drivers. A driver might have a bad first week due to luck, but the guarantee simulates a 'good' week, proving the platform's value and keeping them retained.
If you can target streamlining that experience... you pull up all those below average first experiences to average and drive much better retention curves going forward.
— Dan Hockenmaier