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Data / ML

Using Causal Inference to Improve the Uber User Experience

June 19, 2019 / Global
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Figure 1. Causal inference methods apply to very specific experimental data.
Figure 2. Causal inference methods apply to very specific observational data.
Figure 3. A possible data-generating causal graph shows how the number of Uber Eats orders could confound the relationship between experiencing a delayed delivery and customer engagement.
Figure 4. The regression discontinuity approach estimates if changing surge multiplier has an effect of purchase rates.21
Figure 5. A possible data-generating causal graph shows how an instrument is related with the candidate cause variable whose relationship with the outcome is confounded.
Totte Harinen

Totte Harinen

Totte Harinen is a senior data scientist with Uber Labs, Uber's Applied Behavioral Science team.

Bonnie Li

Bonnie Li

Bonnie Li is a senior data scientist with Uber Labs, Uber's Applied Behavioral Science team.

Posted by Totte Harinen, Bonnie Li

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