Estimate revenue of organic shopping tab

Your team is evaluating a new Shopping tab in a social photo app. The scope includes only organic posts and in-app search; ads and paid placements are excluded. Using the available data—product page views, add-to-carts, purchases, average order value, and organic impression counts—estimate the potential monthly revenue if the tab were launched to 100% of users. Address the following: (a) the conversion funnel and the algebra behind it (for example, $\text{revenue} = \text{impressions} \times \text{CTR} \times \text{PDP\_view\_rate} \times \text{add\_to\_cart\_rate} \times \text{purchase\_rate} \times \text{AOV}$), (b) how you would obtain unbiased CTR and PDP rates from current organic entry points, (c) how to adjust for cannibalization of existing organic purchases, (d) how to scale from experiment traffic to the full population while accounting for heterogeneity, and (e) a sensitivity analysis of the key assumptions.

Overview: The question tests a data scientist's ability in revenue modeling, funnel construction, causal inference for bias correction, experimentation scaling, and sensitivity analysis based on organic engagement and purchase metrics.

This question is drawn from a Meta Data Scientist interview experience.