Estimating Ad Impact on Clicker Conversions for Causal Attribution: A Potential Outcomes Approach

@inproceedings{Barajas2015EstimatingAI,
  title={Estimating Ad Impact on Clicker Conversions for Causal Attribution: A Potential Outcomes Approach},
  author={Joel Barajas and Ram Akella and Aaron Flores and Marius Holtan},
  booktitle={SDM},
  year={2015}
}
We analyze the causal effect of online ads on the conversion probability of the users who click on the ad (clickers). We show that designing a randomized experiment to find this effect is infeasible, and propose a method to find the local effect on the clicker conversions. This method is developed in the Potential Outcomes causal model, via Principal Stratification to model non-ignorable post-treatment (or endogenous) variables such as user clicks, and is validated with simulated data. Based on… 

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