Iron: Keyword Grouping Model for Text Ads Bidding in Paid Search: We present a keyword grouping model named Iron that helps determine keyword bidding prices for text ads auctions in Google paid search. In the grouping process, we first train a Gradient Boosting Machine to predict the conversion rate of every keyword based on eBay search log data, paid search performance and Google feedback for the keywords, then calculate the expected value of each keyword based on the predicted conversion rate and the price, and finally group keywords according to the expected value. After that, we set the bids of keywords based on group-level data. We demonstrate that the Iron model improves our incremental revenue greatly compared with the previous keyword grouping model, which groups keywords solely based on keyword category.

1. Iron: Keyword Grouping Model for
Text Ads Bidding in Paid Search
May 20, 2016
Suxin Guo

2. Google Paid Search – Text Ads and Product Listing Ads
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Text Ads PLA

3. Keyword Bidding – Data Scarcity
KW portfolio
KW with
impressions
KW with
clicks
KW with
conversions
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4. Text Ads Bidding Process
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5. Algorithm Structure
• Conversion rate prediction
• Revenue Prediction/Grouping
• Market-based feedback loop
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6. Data Pipeline
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Keyword Features
eBay Search
Data
Paid Search
Performance
Google
Feedback
Gradient
Boosting
Model
Predicted
Conversion
Rate
Keyword
Price
Parameter
Set Φ
Estimated
Revenue

7. Overall performance: ROI significantly increases by 27.7%
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8. Thank you!
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