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Predict Next-Period Conversion Rate Using Historical Campaign Data

Walmart LabsData Scientist · Onsite
MediumData ScientistOnsiteMachine Learning

Last updated

This interview question evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer for Predict Next-Period Conversion Rate Using Historical Campaign Data states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Scenario

Predicting next-period ad conversion rate using historical campaign data (adid, date, impressions, clicks, conversions).

Question

How would you predict conversion_rate for the upcoming period?

Do we need to transform the target conversion_rate and why?

If more data were available, what additional features would you add?

How would you evaluate model performance?

Explain logistic regression’s loss function.

Describe PCA’s eigenvalues, eigenvectors, and its assumptions.

Hints

Consider logistic/beta regression with time-series lags; evaluate with log-loss, AUC, calibration; PCA assumes linearity & orthogonality of components.