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How can Behavioral Targeting Help Online Advertising? Yan et. al. 2009 October 23, 2014 Sam Hewitt
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What is behavioral targeting? Behavioral targeting (BT) is used by advertisers to target ads to different segments of users based on the users’ web history. Web history consists of search queries and page visits.
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The authors answer three questions related to BT Can BT help online marketers? Are users who clicked on the same ad different than those who did not? How much can BT help? They use the metric, click-through-rate (CTR) Which BT strategy is the best? Short window vs. long window Browsing history vs. query history
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Modeling user history
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Query history uses bag of words to populate the TFIDF matrix Authors used Porter Stemming Stop words were removed as well as terms that only appeared once If a term only appeared once it could not be used to determine similarity between users Number of terms reduced from 765k to 294k Term frequency is discounted based on clicks that a query led to If a user searched a term three time and clicked on an ad once that was served because of that term, the term frequency will be two
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Modeling user history Four BT strategies were assessed Long Term behavior based on Page Views (LP) Long Term behavior based on Query Terms (LQ) Short Term behavior based on Page Views (SP) Short Term behavior based on Query Terms (SQ) Long term = seven days Short term = one day
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Calculating similarity
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Results from similarity calculation SwSbR LP0.14170.025228.9217 LQ0.22390.019644.2908 ST0.15320.028124.5086 SQ0.25940.016191.1890 * Scores are average across all ads or query terms Users who clicked the same ad are up to 90 times more similar The authors chose to segment groups by k-means and CLUTO (a clustering software package) For all ad pairs, 99.37% had higher within ad user similarity than between ad similarity
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How is this helpful
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Improvement to CTR by segmentation CTR was improved by up to 670% off of the non segmented CTR
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Overall performance by different methods
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Issues with paper Authors are from Microsoft, which makes money from ads They do not reveal their source for this data (likely Yahoo!/Bing) Do not discuss the topic of over segmentation Are using outdated methodologies which work, but there is likely a better way (mentioned in future work)
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Summary Behavioral targeting is useful to advertisers It is better to use a short window to segment It is better to use query terms to segment Increasing the number of segments provides better targeting
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Ad Entropy As mentioned marketers want high CTR and impressions If specific user segments contribute highly to impressions then one could just send the ad to them If an ad is clicked more uniformly across all segments, then you need to send the ad to some users who might not be interested in the ad, hurting CPC
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Ad Entropy
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Results
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