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Online Ad Auctions By : Hal R. Varian Reviewed By : Sahil Gupta Instructor : Professor Mattmann TA: Kaijan Xu 14/11/2013.

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Presentation on theme: "Online Ad Auctions By : Hal R. Varian Reviewed By : Sahil Gupta Instructor : Professor Mattmann TA: Kaijan Xu 14/11/2013."— Presentation transcript:

1 Online Ad Auctions By : Hal R. Varian Reviewed By : Sahil Gupta Email : Instructor : Professor Mattmann TA: Kaijan Xu 14/11/2013 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. 2 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. 34/11/2013 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. 44/11/2013 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. b a = bid of advertiser a for a particular keyword. P a = price per click for advertiser a for the particular keyword e a = predicted clickthrough rate of advertiser a for the particular key word. 54/11/2013 Online Ad Auctions

6 Auction Rules(Contd) Each advertiser a chooses a bid b a. The advertisers are ordered by bid times predicted clickthrough rate (b a e a ). b 1 e 1 >b 2 e 2 >…………. b m e m 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. p s e s = b s+1 e s+1 --- p s= ( b s+1 e s+1 )/ e s If there are fewer bidders than slots, the last bidder pays the reserve price r. 64/11/2013 Online Ad Auctions

7 Equilibrium Revenue (Assume ad quality is same, that is e a = 1) v c= value of a click for an advertiser in slot position s. x s= 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+1s value plus value of incremental clicks due to higher slot position. 7 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. 84/11/2013 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 v 2 x 2 + v 3 x 3 If advertiser 1 is absent : the other advertisers will have a reported value of v 2 x 1 + v 3 x 2 + v 4 x 3 94/11/2013 Online Ad Auctions

10 VCG Auctions (Contd) Thus, the advertiser 1 has to pay v 2 (x 1 - x 2 )+ v 3 (x 2 - x 3 )+ v 4 x 3 (Exp 2 – Exp 1) This algorithm is however susceptible to click fraud. 104/11/2013 Online Ad Auctions

11 Bidding Behavior X a : 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. 11 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 x a at a cost c a. 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. 124/11/2013 Online Ad Auctions

13 Advertiser Surplus (Contd) Rearranging the inequality Multiply by x a and sum to find This expression gives us a bound on the Surplus ratio. Normalizing, both sides by total cost. 134/11/2013 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 advertisers 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. 144/11/2013 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. 154/11/2013 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 advertisers 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. 164/11/2013 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. 17 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. 184/11/2013 Online Ad Auctions

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