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