Evaluation
Beyond A/B Testing: Using Surrogacy and Region-Splits to Measure Long-Term Effects in Marketplaces
Our short summary of Lyft’s engineering write-up. The full story, with all the detail, is on their blog.
Read the full write-up on eng.lyft.com (opens in a new tab)Problem
Deciding how much to spend on driver incentives or rider prices without knowing long‑term effects was risky.
Solution
They built a framework that splits regions and uses surrogate metrics to predict long‑term outcomes of pricing and incentive changes in the marketplace.
Want the architecture, code and numbers? They’re in the original post.
Read the full write-up on eng.lyft.com (opens in a new tab)
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