Relevance
Serve quality ads that matches the user intent! Offer a seamless ad experience with a ML algorithm that awards relevant products and a platform that gives absolute control to configure relevance.
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Promoted CTR that’s Higher than Organic CTR
Relevance is one of the main factors in ad quality. Offering a great ad experience to your vendors and users is the key. Topsort relevance algorithm uses your platform’s relevance logic to offer a truly native ad experience and makes sure that the ads match the user intent. Your vendors create quality campaigns, your users see relevant ads, you generate more revenue!
Native or Hybrid
The customizability of Topsort kicks in when it comes to ad relevance, too! We can use your platform’s relevance logic, use ours, or build additional relevance on top of yours.
Quality Scores
Your ad relevance plays a role in the quality score which determines the auctions. An ad with higher relevance can win an auction without bidding the top price.
Organic Results
We know that you’ve perfected your search algorithm. That’s why our algorithm takes your organic search results into consideration when determining the relevance of an ad. Our ads boost your search, not harm it!
CustomizeExperience
Give keyword, brand, or subcategory level access to your brands and vendors to increase the ad experience. Feed user cohorts, zip codes, and other 1st party data for higher relevance.
How Relevance Works
Topsort Relevance
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With Topsort’s relevance, a product that’s not relevant according to your platform’s logic, can not win the auction and show up as sponsored listings. In other words, a “Bluetooth speaker” won’t appear among the sponsored listings when a user searches for “gaming laptops” no matter how high they bid.
Parallel Relevance
Nobody likes to see a “bluetooth speaker” when they search for “gaming laptops”, or see a promoted restaurant doesn’t serve in their area! It’s bad for user and seller ad experience. An ad paltform without high-quality built-in relevance will ruin your marketplace dynamics.
From Rigorous Research
“We propose a simple approach to determine a revenue-optimal ranking rule within our family, taking into account effects on advertiser satisfaction and user experience.” Revenue Analysis of a Family of Ranking Rules for Keyword Auctions - Sebastien Lahaie, David M. Pennock
