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Estimating Incremental Lift in Customer Value (Delta CV) using Synthetic Control
- At PayPal, Data Science teams use causal inference to evaluate the impact of key customer actions on revenue and engagement.
- They introduced Delta CV (delta in Customer Value) to measure the incremental profit margin after adopting a new product.
- Delta CV measures the cumulative lift in customer value considering all PayPal transactions of a user.
- Measurement of Delta CV is done using causal inference and synthetic control, matching treatment users with non-adopters.
- Delta CV helps in strategic decision making, ROI calculations, and optimizing in-app product placements.
- Delta CV considers both the direct profit from a new adoption and the halo effects that lead to increased engagement with other products.
- Median delta CV and mean delta CV are used to understand the incremental customer value at scale.
- The methodology involves KNN algorithm to create a synthetic control group for estimating treatment effects.
- Delta CV estimation has caveats like variance, bias, and impact interpretation due to product adoptions' non-additive nature.
- Delta CV is vital for PayPal's strategic decisions, continuously evolving with new products and improved matching methodologies.
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