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Online Ad Auctions

Online Ad Auctions. By : Hal R. Varian Reviewed By : Sahil Gupta Email : sahilg@usc.edu Instructor : Professor Mattmann TA: Kaijan Xu. Introduction to Online Ad Auctions. How Search Engines Sell Ad Space using an online(automated) auction.

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Online Ad Auctions

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  1. Online Ad Auctions By : Hal R. Varian Reviewed By : Sahil Gupta Email : sahilg@usc.edu Instructor : Professor Mattmann TA: KaijanXu 4/11/2013 Online Ad Auctions

  2. Introduction to Online Ad Auctions • How Search Engines Sell Ad Space using an online(automated) auction. • When user sends a query to the search engine, the system finds a set of Ads with keywords that match the query and determines which ad to show and where to show them. Structure of an Online Ad Auction • Advertisers bid for keywords and Ad text. • When a user clicks on the ad, the advertiser pays the search engine an amount determined by the bids of other competing advertisers. 4/11/2013 Online Ad Auctions

  3. Introduction (Continued) • Search Engines are expected to sell the most prominent positions(likely to get clicks) to ads that have the highest Expected Revenue. • Expected Revenue = Price per click X Expected CTR • Click Through Rate = (Clicks/Impressions) X100 • Therefore, Ads are ranked by Expected Revenue. • However, Expected Revenue is not the only measure and Various measures for Ad Quality are taken into account while deciding upon the ranking of the ads. 4/11/2013 Online Ad Auctions

  4. Topics Covered in Class • Search Engine Advertising • Discussed About Pay Per Click Advertising • Search Engine Marketing (Google Adwords) • Return on Investment • The paper provides insight into how these concepts are used by search engines in Online Ad Auctions. 4/11/2013 Online Ad Auctions

  5. AuctionRules • How search engines determine which ads are shown, when they are shown and how much they pay per click? • Terminology • a = 1,…..,A index advertisers. • s = 1,……,S index slots. • ba = bid of advertiser a for a particular keyword. • Pa = price per click for advertiser a for the particular keyword • ea = predicted clickthrough rate of advertiser a for the particular key word. 4/11/2013 Online Ad Auctions

  6. Auction Rules(Contd) • Each advertiser a chooses a bid ba . • The advertisers are ordered by bid times predicted clickthrough rate (ba ea). b1 e1 >b2 e2>…………. bmem where m<=S • The price that the advertiser a pays for a click is the minimum necessary to retain its position in the particular slot. pses= bs+1 es+1 --- ps= ( bs+1es+1 )/ es • If there are fewer bidders than slots, the last bidder pays the reserve price r. 4/11/2013 Online Ad Auctions

  7. Equilibrium Revenue (Assume ad quality is same, that is ea = 1) • vc= value of a click for an advertiser in slot position s. • xs= position specific effect for an advertiser in slot position s. • When the advertiser in slot s+1 does not want to move up to slot s(equilibrium), advertiser in slot s must beat slot s+1 advertiser ‘s value for the clicks to retain its slot S.That is • Rearranging • Cost of slot s should be atleast as large as cost of slot s+1’s value plus value of incremental clicks due to higher slot position. 4/11/2013 Online Ad Auctions

  8. Equilibrium Revenue (Continued) Recursively, using this inequality: This yields a lower bound on auction revenue in the equilibrium position where every advertiser prefers its own slot than the slot above it. 4/11/2013 Online Ad Auctions

  9. Vickrey-Clarke-Groves Auctions • This method of auction is based on the Equilibrium Revenue approach. • Each advertiser pays the cost it imposes on other advertisers. • For example , if there are 3 slots and 4 advertisers. • If advertiser 1 is present: the other advertisers will have a reported value of v2x2 + v3x3 If advertiser 1 is absent : the other advertisers will have a reported value of v2x1 + v3x2 + v4x3 4/11/2013 Online Ad Auctions

  10. VCG Auctions (Contd) • Thus, the advertiser 1 has to pay v2(x1- x2)+ v3(x2- x3)+ v4x3 (Exp 2 – Exp 1) • This algorithm is however susceptible to click fraud. 4/11/2013 Online Ad Auctions

  11. Bidding Behavior • Xa: Number of clicks received by advertiser a in a given time period. • Va: value generated for advertiser a by Xa clicks. • Ca: Cost the advertiser a incurs for getting Xa clicks. • Now, the idea is to maximize the advertiser surplus: VaXa – CaXa and this drives the bidding behavior for an advertiser. • The Cost per click and Bid Per click function can be used to analyze the bidding behavior for an advertiser. 4/11/2013 Online Ad Auctions

  12. Advertiser Surplus • Surplus Ratio : Aggregate Value/Aggregate Cost • Suppose Advertiser a is currently having a campaign where it chooses some number of clicks xaat a cost ca. • Suppose it decides to change its campaign such that it receives smaller number of clicks at a reduced cost Surplus for the new campaign will be less than the surplus for the old campaign. 4/11/2013 Online Ad Auctions

  13. Advertiser Surplus (Contd) • Rearranging the inequality • Multiply by xaand sum to find • This expression gives us a bound on the Surplus ratio. Normalizing, both sides by total cost. 4/11/2013 Online Ad Auctions

  14. Estimation Methods and Results • A challenging aspect is to determine how many clicks an advertiser would receive if its position is changed. • Simple Algorithm illustrated • Cut advertiser’s bid to ½. • Determine its position in the slot table and how much it would pay in the ad auction with the lower bid.This is accomplished using Auction Rules. • Estimating the clicks it would receive at this lower position. This is done using a predictive model on how clicks vary with ad position. 4/11/2013 Online Ad Auctions

  15. Two Important Observations • Total value enjoyed by advertisers is between 2 and 2.3 times their total expenditure. • Bid of an advertiser also provides a lower bound on the value of the click. However,Bids are only about 25-30 percent larger than the prices, so using bids understates the advertiser value. 4/11/2013 Online Ad Auctions

  16. Conclusion • The research paper provides a useful insight in the Online Ad auctions and basic infrastructure and rules that drive them. • It describes the various factors that are taken into account by search engines to determine which ads are shown when and where depending on the advertiser’s bid and campaign. • It gives a useful insight in the mechanism of Online Ad auctions describing the lower bounds on the Auction Revenue and how it can be used by the advertisers. 4/11/2013 Online Ad Auctions

  17. Pros and Cons • Pros: • Provide a clear picture of Online Ad Auctions and how advertisers bid in the system and are ranked by the search engines based on their campaigns. • Describes simple mechanisms for illustrating Online Ad Auction Rules, Auction Revenue, Advertiser Surplus. 4/11/2013 Online Ad Auctions

  18. Cons • Cons: • Does not take into account the effect of ad quality while determining various mechanisms. • Does not provide any information on the training data set used for the Experimental analysis. • Does not describe how Bidding behavior is decided upon. (Facts on Bidding behavior are quite Unclear) • Issues of Click Fraud and there impact on ranking are not discussed. 4/11/2013 Online Ad Auctions

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