Social Network For Analytic Professionals
Predictive Keyword Scores to Optimize Online Advertising Campaigns (audio seminar)
I will be presenting (August 19).
During this webinar, you will learn how to predict the chance of converting or converting odds for keywords with little or no historical data, in Pay-Per-Click programs such as Google, Yahoo and Bing (Microsoft). We will discuss text mining techniques, a rule engine, KPI selection and predictive modeling (logistic regression, decision trees, naïve Bayes or hybrid models) to score bid keywords with no or little historical data, such as new keywords added to existing ad groups. Also, a simple parametric keyword bidding algorithm will be discussed. The parametric bidding algorithm relies on keyword scores and – when available and statistically significant – conversion rates.
The scores are built using text mining rules, keyword grouping, and a training set with multiple clients with various conversion rates, and several million bid keywords. Cross-validation will be discussed. The keyword score (more precisely, a function of the score) is used as a proxy for the conversion rate. The predicted ROI, used in the bidding algorithm, is a simple function of the current bid, the score (which in turn is a predictor of the conversion rate, by design) and the revenue per conversion.
Illustration with lift measurements will be provided on a real example, using data from a very large advertiser, focusing on keywords with low click frequency (the long tail).
URL: http://www.bettermanagement.com/seminars/seminar.aspx?l=15103
During this webinar, you will learn how to predict the chance of converting or converting odds for keywords with little or no historical data, in Pay-Per-Click programs such as Google, Yahoo and Bing (Microsoft). We will discuss text mining techniques, a rule engine, KPI selection and predictive modeling (logistic regression, decision trees, naïve Bayes or hybrid models) to score bid keywords with no or little historical data, such as new keywords added to existing ad groups. Also, a simple parametric keyword bidding algorithm will be discussed. The parametric bidding algorithm relies on keyword scores and – when available and statistically significant – conversion rates.
The scores are built using text mining rules, keyword grouping, and a training set with multiple clients with various conversion rates, and several million bid keywords. Cross-validation will be discussed. The keyword score (more precisely, a function of the score) is used as a proxy for the conversion rate. The predicted ROI, used in the bidding algorithm, is a simple function of the current bid, the score (which in turn is a predictor of the conversion rate, by design) and the revenue per conversion.
Illustration with lift measurements will be provided on a real example, using data from a very large advertiser, focusing on keywords with low click frequency (the long tail).
URL: http://www.bettermanagement.com/seminars/seminar.aspx?l=15103
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