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Internet Economics כלכלת האינטרנט

Internet Economics כלכלת האינטרנט. Class 7 – Online Advertising. Outline. Part 1: Bla bla bla Part 2: Equilibrium analysis of Google’s auction Reminder: please come to my office hours. Please let me know in advance. Outline. Introduction: online advertising Sponsored search

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Internet Economics כלכלת האינטרנט

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  1. Internet Economicsכלכלת האינטרנט Class 7 – Online Advertising

  2. Outline Part 1: Blablabla Part 2: Equilibrium analysis of Google’s auction Reminder: • please come to my office hours. • Please let me know in advance.

  3. Outline • Introduction: online advertising • Sponsored search • Bidding and properties • Formal model • The Generalized second-price auction • Reminder: multi-unit auctions and VCG • Equilibrium analysis

  4. Classic advertising

  5. Classic advertising: newspapers

  6. Classic advertising: TV

  7. Classic advertising: Billboards

  8. Online advertising

  9. Banner ads • General: • Examples: banner, sponserd search, video, videa games, adsense, in social networks • Some numbers • advantages over classic ads • Ppi,ppc,ppconversion • Sponsored search: • Some history • Definitions: ctr, conversion-rate • GSP- definition, non truthfulness. • Diagram of first-price yahoo data. • Analysis of equilibrium.

  10. Sponsored search

  11. Semantic advertising

  12. Email advertising

  13. Online Advertising:Some rough numbers • 2008: • Worldwide advertising spending: about 500 Billion • Online advertising: about 10% of that (!!!!) • Google : over 98% of revenue from advertising (Total $21 Billion in 2008) • Double digit growth in online advertising in the past and in the near future (expected)

  14. Online advertising - advantages • Targeting • By search keywords, context, • Personalized ads. • Additional information • Time, history, personal data • Advanced billing/effectiveness options • By eyeballs, clicks, actual purchases • “pay only when you sell” • Advanced bidding options • No printing/”menu” costs. • Variety of multimedia tools • Enables cheap campaigns, low entry levels.

  15. Advertising types • Brand advertisers • Direct advertisers

  16. Revenue model • Pay per impression • CPM-cost per mille. Cost per thousand impressions. • Good for brand advertisers • Pay per click • CPC - cost per click. • Most prevalent • Brand advertisers get value for free. • Pay per action • CPA – cost per action/acquisition/conversion. • Risk-free for advertisers • Harder to implement

  17. Outline • Introduction: online advertising  Sponsored search • Bidding and properties • Formal model • The Generalized second-price auction • Reminder: multi-unit auctions and VCG • Equilibrium analysis

  18. Sponsored search auctions Real (“organic”) search result Ads: “sponsored search”

  19. Sponsored search auctions Search keywords keywords keywords Ad slots

  20. Bidding • A basic campaign for an advertiser includes: • Some keywords have bids greater than $50 • E.g., Mesothelioma • Search engine provides assistance • traffic estimator, keyword suggestions, automatic bidding • Google started pay-per-action sales.

  21. Bidding: more details When does a keyword match a user search-query? • When bidding $5 per “hotel California”.Will “hotel California song” appear? • Broad match • California hotel, hotel California Hilton, cheap hotel California. • Exact match: • “hotel California” with no changes or additions. • Negative words: • “hotel California–song -eagles “ • Many more options: • Geography, time, languages, mobile/desktops/laptops, etc.

  22. Economics of sponsored search Search engines Internet users advertisers

  23. Click Through Rates • Are all ads equal? • Position matters. • User mainly click on top ads. • Need to understand user behavior.

  24. Click Through rate 0.5% 9% 4% 0.2% 2% 0.08%

  25. Click Through rate c4 c1 c2 … c3 … ck

  26. Formal model • n advertisers • For advertiser i: value per click vi • k ad slots (positions): 1,…,k • Click-through-rates: c1 > c2 > …> ck • Simplifying assumption: CTR identical for all users. • Advertiser i, wins slot t, pays p.utility: ct (vi –p) • Social welfare (assume advertisers 1,..,k win slots 1,…,k) :

  27. Example The efficient outcome: v1=10 Slot 1 c1=0.08 Slot 2 v2=8 c2=0.03 Slot 3 c3=0.01 v3=2 Total efficiency:10*0.8 + 8*0.03 + 2*0.01

  28. How would you sell the slots? Yahoo! (that acquired Overture) sold ads in a pay-your-bid auction (that is, first-price auction). Results: Sawtooth

  29. Pay-your-bid data (14 hours)

  30. Pay-your-bid data (week)

  31. Unstable bidding Think about two neighboring gas stations. What’s bad with instability? • Inefficiency – advertisers with high values spend part of the time on the top. • Investment in strategy – advertisers invest a lot of efforts (time, software, consultants, etc.) handling their strategy. • Relevance – assuming advertisers’ values are correlated with their relevance, bidders see less relevant ads. Is there an efficient auction then?

  32. Why efficiency? Isn’t Google (and other internet companies) required by their shareholders to maximize profit? Reasons: • Long term thinking in a competitive environment. • Making the whole pie larger. • Easier to model and analyze…

  33. GSP • The Generalized Second price (GSP) auction • I like the name “next-price auction” better. • Used by major search engines • Google, Bing (Microsoft), Yahoo Auction rules • Bidders bid their value per click bi • The ith highest bidder wins the ith slot and pays the (i+1)th highest bid. • With one slot: reduces to 2nd-price auction.

  34. Example b1=10 Slot 1 c1=0.08 Pays $8 Slot 2 b2=8 c2=0.03 Pays $2 Slot 3 c3=0.01 b3=2 Pays $1 b4=1

  35. GSP and VCG • Google advertising its new auction:“… unique auction model uses Nobel Prize winning economic theory to eliminate … that feeling that you’ve paid too much” • GSP is a “new” auction, invented by Google. • Probably by mistake…. • But GSP is not VCG! • Not truthful! • Is it still efficient? (remember 1st-price auctions)

  36. Example: GSP not truthful v1=10 Slot 1 c1=0.08 Slot 2 v2=8 c2=0.03 Slot 3 c3=0.01 v3=2 wins slot 1. utility: 0.08 * (10-8) = 0.16 b1=10 wins slot 2.utility: 0.3 * (8-2) = 0.18 b1=5

  37. VCG prices b1=10 Slot 1 c1=0.08 Pays $5.625 Slot 2 b2=8 c2=0.03 Pays $1.67 Slot 3 c3=0.01 b3=2 Pays $1 b4=1

  38. Outline • Introduction: online advertising • Sponsored search • Bidding and properties • Formal model • The Generalized second-price auction  Reminder: multi-unit auctions and VCG • Equilibrium analysis

  39. Reminder • In the previous class we discussed multi-unit auctions and VCG prices.

  40. Auctions for non-Identical items • Non identical items: a, b, c, d, e, • Each bidder has a value for each itemvi(a),vi(b),bi(c),.. • Each bidder wants one item only.

  41. Simultaneous Ascending Auction • Start with zero prices. • Each bidder reports his favorite item • Price of over-demanded items is raised by $1. • Stop when there are no over-demanded items. • Bidders win their demands at the final prices. Claim: this auction terminates with: (1) Efficient allocation. (2) VCG prices ( ± $1 )

  42. Market clearing prices • Conclusion: In a multi-unit auction with unit-demand bidders:This auction finds “market-clearing prices”: • every bidder receives his favorite item (given the prices) • all items are allocated (unless their price is 0). • And we saw that: • these market clearing prices are exactly the VCG prices • the allocation is efficient

  43. Sponsored search as multi-unit auction • Sponsored search can be viewed as multi-unit auction: • Each slot is an item • Advertiser i has value of ctvi for slot t. • We can conclude: In sponsored search auctions, the VCG prices are market-clearing prices. • No advertiser “envies” another advertiser and wants to have their slot+price. Slot 1 p1=5 I prefer “slot 1 + pay 5”to “slot 2 +pay 3” Slot 2 p2=3

  44. Market Clearing Prices b1=10 Slot 1 c1=0.08 Pays $5.625 Slot 2 b2=8 c2=0.03 Pays $1.67 Slot 3 c3=0.01 b3=2 p1= $5.625 p2=$1.67 p3= $1 Pays $1 Let’s verify that Advertiser 1 do not want to switch to another slot under these prices: b4=1 u1(slot 1)= 0.08*(10-5.625) =0.35 u1(slot 2)= 0.03*(10-1.67) =0.25 u1(slot 3)= 0.01(10-1) =0.09

  45. Equilibrium concept We will analyze the auction as a full-information game. Payoff are determined by the auction rules. Nash equilibrium: a set of bids in the GSP auction where no bidder benefits from changing his bid (given the other bids). Reason: equilibrium model “stable” bids in repeated-auction scenarios. (advertisers experiment…)

  46. Equilibrium Let p1,..,pkbe market clearing prices. Let v1,…,vkbe the per-click values of the advertisers Claim: a Nash equilibrium is when each player i bids price pi-1 (bidder 1 can bid any number > p1). Proof: Step 1: show that market-clearing prices are decreasing with slots. Step 2: show that this is an equilibrium.

  47. Equilibrium bidding b1=10 Slot 1 c1=0.08 Slot 2 b2=8 c2=0.03 Slot 3 c3=0.01 b3=2 p1= $5.625 p2=$1.67 p3= $1 The following bids are an equilibrium: b1=6, b2=5.625, b3=1.67, b4=1 b4=1 First observation: the bids are decreasing. Is it always the case?

  48. Step 1 • We will show:if p1,…,pkare market clearing prices then p1>p2>…>pk Slot j Utility: cj( vi – pj) ≥ Advertiser twins slot t: Slot t Utility: ct ( vt– pt ) Market clearing prices: t will not want to get slot j and pay pj. Since cj>ct, it must be that pt<pj.

  49. Step 2: equilibrium • Let p1,…,pkbe market-clearing prices.bi-1=pi-2 , bi=pi-1 , bi+1=pi • Under GSP, i wins slot iand pays pi. • Should i lower his bid? If he bids below bi+1, he will win slot i+1 and pay pi+1. • Cannot happen under market –clearing prices. Slot i-1 bi Slot i bi+1 bi+2 Slot i+1

  50. Equilibrium bidding b1=10 Slot 1 c1=0.08 Slot 2 b2=8 c2=0.03 Slot 3 c3=0.01 b3=2 p1= $5.625 p2=$1.67 p3= $1 The following bids are an equilibrium: b1=6, b2=5.625, b3=1.67, b4=1 b4=1

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