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In this episode, we explore how PayPal estimates incremental lift in customer value using synthetic control methods. This causal inference–based approach provides a principled way to construct a counterfactual and isolate causal effects when traditional experiments aren’t sufficient, helping teams measure true impact in a complex, noisy, real-world environment and make more informed decisions.
For more details, you can refer to their published tech blog, linked here for your reference: https://medium.com/paypal-tech/estimating-incremental-lift-in-customer-value-delta-cv-using-synthetic-control-522be5e3da3a
By Pan Wu5
99 ratings
In this episode, we explore how PayPal estimates incremental lift in customer value using synthetic control methods. This causal inference–based approach provides a principled way to construct a counterfactual and isolate causal effects when traditional experiments aren’t sufficient, helping teams measure true impact in a complex, noisy, real-world environment and make more informed decisions.
For more details, you can refer to their published tech blog, linked here for your reference: https://medium.com/paypal-tech/estimating-incremental-lift-in-customer-value-delta-cv-using-synthetic-control-522be5e3da3a

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