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Sponsored Search Presenter: Lory Al Moakar. Outline Motivation Problem Definition VCG solution GSP(Generalized Second Price) GSP vs. VCG Is GSP incentive.

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Presentation on theme: "Sponsored Search Presenter: Lory Al Moakar. Outline Motivation Problem Definition VCG solution GSP(Generalized Second Price) GSP vs. VCG Is GSP incentive."— Presentation transcript:

1 Sponsored Search Presenter: Lory Al Moakar

2 Outline Motivation Problem Definition VCG solution GSP(Generalized Second Price) GSP vs. VCG Is GSP incentive compatible? GSP has a Nash Equilibrium formed of market clearing prices. Some GSP Nash Equilibria may not be socially optimal. Conclusion A note on further issues

3 Motivation Search is by far the most lucrative area, accounting for 40 percent of the total online ad spending in the U.S., according to JupiterResearch. Search advertising is expected to grow from $4.2 billion in 2005 to $7.5 billion in 2010, … JupiterResearch has forecast.

4 Snap Shots of Adwords

5 Problem Definition N advertisers M slots such that M ≤ N r j the clickthrough rate for slot j i.e. the number of clicks the ad will receive if it is listed in slot j. V i the declared value an advertiser is willing to pay per click V i * is the true value an advertiser is willing to pay per click The value an advertiser i places on his/her ad in the jth slot V ij = V i × r j X ij = 1 if advertiser i is assigned slot j Social Objective: find a perfect matching that maximizes the total valuation of the advertisers over all perfect matchings

6 Example 3 advertisers: 3 slots V ij *a1a1 a2a2 a3a3 s1s1 641 s2s2 321 s3s3 000 a1a1 a2a2 a3a3 Vi*Vi*321 s1s1 s2s2 s3s3 rjrj 210 a 1 a 2 a 3 s 1 s 2 s 3 6 2 0

7 Review on VCG mechanism with Clark-Pivot Rule Player i pays the mechanism : P i = the best the other players can do if player i was not there – the best the other players can do when player i is there

8 Another objective: Incentive Compatible using VCG Assume advertiser i is assigned slot j if i tells the truth. V N-i M is the maximum valuation over all perfect matchings of all slots and all advertisers except i V N-i M-j is the maximum valuation over all perfect matchings of all slots except j and all advertisers except i The harm that i does by showing up is: P j = V N-i M – V N-i M-j P j is the VCG price for advertiser i assigned to slot j.

9 Is this incentive compatible? Assume i lies and is assigned slot k ≠ j which is the slot i gets if it does not lie. Gain from lying = V ik * – P k Gain from telling the truth = V ij * – P j To be incentive compatible, we need to prove that the gain from lying ≤ gain from telling the truth prove that [V ij * – P j ] – [V ik * – P k ] ≥ 0 Proof: V ik * – P k = V ik * – [ V N-i M – V N-i M-k ] V ij * – P j = V ij * – [ V N-i M – V N-i M-j ] [V ij * – P j ] – [V ik * – P k ] = V ij * + V N-i M-j – [V ik * + V N-i M-k ] = optimal valuation – (total valuation when i gets k) ≥ 0  This mechanism is incentive compatible.

10 GSP ( Generalized Second Price) GSP assigns slots to highest M bids GSP charges advertiser who gets slot j the bid of the advertiser in slot j-1. used by Google and a variation of it used by yahoo Excerpt from Google’s AdWords Ad:

11 Is GSP incentive compatible? Counterexample: 2 slots with r 1 = 10 and r 2 = 4 3 advertisers with V 1 * = 7, V 2 * = 6 and V 3 * = 1 if a 1 bids truthfully, he/she will be assigned to s 1  pays 60 and gains 70 with net profit of 10 if a 1 lies and bids 5, he/she will be assigned to s 2  pays 4 and gains 28 with net profit of 24. a 1 is better off with lying!

12 GSP vs. VCG Consider this example. 2 slots (r 1 = 10 and r 2 = 4) add r 3 = 0 3 advertisers (V 1 * = 7, V 2 * = 6 and V 3 * = 1) VCG prices are P 1 = 40 P 2 = 4 Total 44 GSP prices are P 1 = 60 P 2 = 4 Total 64

13 Why do search engines choose not to use VCG? P VCG i = V N-i M – V N-i M-i V N-i M = V N-i M-i = P VCGi =

14 Why do search engines choose not to use VCG?-cont’d P VCGi+1 = ΔVCG = P VCGi – P VCGi+1 = V i+1 (r i – r i+1 ) ΔGSP = P GSPi – P GSPi+1 = V i+1 ×r i – V i+2 ×r i+1 ΔGSP – ΔVCG = r i (V i+1 – V i+2 ) ≥ 0  an advertiser pays less using VCG  a search engine gains less using VCG

15 Is there a social optimal equilibrium in GSP? Consider the previous example: 2 slots with r 1 = 10 and r 2 = 4 r 3 = 0 3 advertisers with V 1 * = 7, V 2 * = 6 and V 3 * = 1 The market clearing prices per click for s 1, s 2 and s 3 respectively are (4, 1, 0) Are there bids that would result in these prices for the slots? Yes, a 1 bids higher than 4, a 2 bids 4, and a 3 bids 1  a 1 gets s 1 and pays 4 per click  payoff = 70 – 40 = 30  a 2 gets s 2 and pays 1 per click  payoff = 24 – 4 = 20  a 3 gets s 3 and pays 0 per click  payoff = 0

16 Is there a social optimal equilibrium in GSP?-cont’d a 1 lowers its bid to 4 - ε  gets s 2  payoff = 28 – 4 = 24 < 30  a 1 does not have the incentive to lower its bid a 2 raises its bid to 5  gets s 1  payoff = 60 – 40 = 20  a 2 does not have the incentive to lower its bid This is a Nash equilibrium Vi*Vi*ViVi riri Slotpayoff 174+ε 10130 264 4 2 20 311 0 30

17 General Argument: Is there a social optimal equilibrium in GSP? N advertisers sorted in decreasing order of valuation per click M slots + (N-M) slots with 0 click-through rate sort slots in decreasing order of click-though rates Consider any set of market clearing prices: Since for any set of market-clearing prices, a perfect matching in the resulting preferred seller graph maximizes the total valuation of each valuation for the slot it gets  the advertiser with the highest valuation per click gets the top slot  advertiser i gets slot i

18 Proof that there is an optimal equilibrium in GSP Plan of the proof: 1.Construct a set of bids that produces a set of market clearing prices 2.These bids form a Nash equilibrium 1. Construct a set of bids that produces a set of market clearing prices Consider a set of market clearing prices p j  price per click for slot j : p j * = p j / r j show that p 1 *  p 2 *  p 3 * ……  p M *

19 Proof that there is an optimal equilibrium in GSP Proof: Consider any arbitrary slots j and k such that j < k  show that p j *  p k * advertiser k prefers slot k to j (by property of market clearing prices) advertiser k ‘s payoff in slot k is (V k * – p k *) r k advertiser k ’s payoff in slot j is (V k * – p j *) r j k’s payoff per click in slot k = V k * – p k * k’s payoff per click in slot j = V k * – p j * since r j  r k but advertiser k prefers slot k to slot j  V k * – p k *  V k * – p j *  p j *  p k * Therefore, if advertiser i bids Vi such that V i = p i-1 * then the prices for the slots are market clearing prices.

20 Proof that there is an optimal equilibrium in GSP 2. These bids form a Nash equilibrium Show that with the above bids, no advertiser wants to lower his/her bid and no advertiser wants to raise his/her price. Proof: advertiser j in slot j lowers its bid and gets slot k where j < k but since prices are market clearing  advertiser j prefers slot j over any other slot for its current price. advertiser j in slot j raises its bid to get slot i but p i > p j in order to get slot i, j has to bid higher than what advertiser i is paying  new p i > current p i

21 Proof that there is an optimal equilibrium in GSP since the current prices are market clearing prices  advertiser j doesn’t want slot i at the current price so j does not want this slot at a higher price  this set of bids forms a Nash Equilibrium Therefore: GSP has one good Nash Equilibrium in which advertisers get matched to slots in a way that maximizes social welfare i.e. the total valuation of all advertisers for their slots.

22 Are all GSP Nash Equilibria socially optimal? Counterexample: 3 slots with r 1 = 10, r 2 = 4, r 3 = 0 if a3 moves, he/she pays 3 which results in a negative payoff if a2 moves, he/she pays 3 and gets a payoff 24-3 = 21  less than 30. if a1 moves, he/she pays 5 and gets a payoff 70-50= 20  less than 24  a Nash equilibrium Vi*Vi*ViVi Slotpayoff 173s2s2 24-3=21 265s1s1 60-30=30 311s3s3 0

23 Are all GSP Nash Equilibria socially optimal? Is this Nash market clearing? No, since a1 would prefer s1 for its current price 30 and get a payoff of 70 – 30 = 40 instead of s2 but if a1 increases its bid then it has to pay 50 and get a payoff of 20 < 24 (its current payment). Vi*Vi*ViVi Slotpayoff 173s2s2 24-3=21 265s1s1 60-30=30 311s3s3 0

24 Conclusions VCG the worst equilibrium for the search engines the best equilibrium for the advertisers Incentive compatible GSP Not clear if it maximizes revenue Has one optimal equilibrium truth-telling is generally not an equilibrium strategy

25 Further Issues A more general model : vij = vi ×αij αij is the probability that a user will click on this ad if advertiser i is in the jth slot What happens when a user specifies a budget and a set of keywords to bid on? Which ads to show given a set of keywords and a search query asking for similar keywords but not the exact ones? If a click occurs, then how much to charge the chosen advertisers who did not bid on these keywords? How many ads to show? Does more ads mean more revenue? Is pay-per-click the best model? How about pay-per-sale or pay- per-action to stop robot clicks? Does the identity of the other advertisers in the other slots affect an advertiser’s click-through-ratio?

26 References David Easley and Jon Kleinberg, Lecture Notes on Keyword Based Advertising Matching Buyers and Sellers Chapter 28: Sponsored Search Auctions from Algorithmic Game Theory by Nisan, Roughgarden, Tardos and Vazirani. www.google.com/adsense/afs.pdf


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