algo-ad-ctr
CTR Prediction Model
Overview
CTR prediction estimates the probability that a user clicks on an ad given context (user, query, ad, position). Forms the core of ad ranking: AdRank = Bid × pCTR. Typically uses logistic regression or gradient-boosted trees. Training on billions of impressions.
When to Use
Trigger conditions:
- Building or improving an ad ranking system
- Predicting click probability for bid optimization
- Evaluating ad creative effectiveness from feature analysis
When NOT to use:
- When predicting post-click conversions (use conversion rate model)
- When setting bid amounts (use bidding strategy skill)
Algorithm
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