On Revenue in the Generalized Second Price Auction Brendan Renato - - PowerPoint PPT Presentation

on revenue in the generalized second price auction
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On Revenue in the Generalized Second Price Auction Brendan Renato - - PowerPoint PPT Presentation

On Revenue in the Generalized Second Price Auction Brendan Renato va Lucier Paes Leme Tardos (MSR-NE) (Cornell) (Cornell) Sponsored Search Auctions Sponsored Search Auctions Two AdAuctions Mechanisms Generalized Second


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On Revenue in the Generalized Second Price Auction

Brendan Lucier (MSR-NE) Renato Paes Leme (Cornell) Éva Tardos (Cornell)

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Sponsored Search Auctions

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Sponsored Search Auctions

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Generalized Second Price Auction Vickrey-Clarke-Groves Mechanism

Two AdAuctions Mechanisms

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GSP VCG Two AdAuctions Mechanisms

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GSP VCG

Main Question: How do those mechanisms compare from a game-theoretic viewpoint ?

Two AdAuctions Mechanisms

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GSP VCG Two AdAuctions Mechanisms

  • sort by bid
  • sort by bid
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GSP VCG Two AdAuctions Mechanisms

  • sort by bid
  • pricing = next

highest bid

  • sort by bid
  • complicated

pricing rule

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GSP VCG Two AdAuctions Mechanisms

  • Simple
  • Industrial

standard

  • Complicated
  • Optimal in

theory

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With respect to which metric ?

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With respect to which metric ?

Users Advertisers Search Engine

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With respect to which metric ?

Users

Clicks * (value/click – pay/click) Clicks * pay/click Usefulness of ads

Advertisers Search Engine

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With respect to which metric ?

Users

Clicks * (value/click – pay/click) Clicks * pay/click Usefulness of ads

Revenue

Advertisers Search Engine

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With respect to which metric ?

Users

Clicks * (value/click – pay/click) Clicks * pay/click Usefulness of ads

Revenue (our focus)

Advertisers Search Engine

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With respect to which metric ?

Advertisers Users Search Engine

Clicks * (value/click – pay/click) Clicks * pay/click Usefulness of ads

Social Welfare = ∑ Clicks . (value/click)

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With respect to which metric ?

Users

Clicks * (value/click – pay/click) Clicks * pay/click Usefulness of ads

?

Advertisers Search Engine

Social Welfare = ∑ Clicks . (value/click)

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With respect to which metric ?

Users

Clicks * (value/click – pay/click) Clicks * pay/click Usefulness of ads [Varian], [Eldeman, Ostrovsky, Schwarz], [Paes Leme, Tardos], [Lucier, Paes Leme], [Caragiannis, Kaklamanis, Kanellopoulos, Kyropoulou], [CKKKLPLT], [Athey, Nekipelov], [Ellison, Athey], …

Advertisers Search Engine

Social Welfare = ∑ Clicks . (value/click)

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Warm-up: When we have one ad slot…

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Which ad to place and how much to charge?

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Which ad to place and how much to charge?

$0.03 / click $0.02 / click $0.01 / click

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Which ad to place and how much to charge?

$0.03 / click $0.02 / click $0.01 / click

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Which ad to place and how much to charge?

$0.03 / click $0.02 / click $0.01 / click

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Which ad to place and how much to charge?

Pays $0.02 / click (second highest bid)

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Selling Display Ads

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Selling Display Ads

Single ad slot Second-price auction

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Selling Display Ads

Single ad slot Second-price auction

  • simple
  • easy to bid (truthful)
  • maximizes welfare
  • maximizes revenue with
  • ptimal reserve r
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Selling Display Ads

Single ad slot Second-price auction

Theorem (Myerson’81) The revenue-optimal auction* for a single item is the second price auctions with a reserve price. * under suitable assumptions

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Usually we have many ad slots …

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… and not all of them are equal

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… and not all of them are equal

Position Auctions auctioning positions on webpages How to place ads and how to charge for them with multiple positions.

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1) Without uncertainty: GSP revenue is at least ½ of a natural VCG-like benchmark 2) With uncertainty (Bayesian setting): GSP with appropriate reserve price extracts constant fraction of the optimal revenue 3) Revenue and Welfare: What are the trade-offs?

Our Results

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Our Results

1) Without uncertainty: GSP revenue is at least ½ of a natural VCG-like benchmark 2) With uncertainty (Bayesian setting): GSP with appropriate reserve price extracts constant fraction of the optimal revenue 3) Revenue and Welfare: What are the trade-offs?

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Related Work

Position Auctions model due to [Edelman, Ostrovsky, Schwarz] and [Varian], who study revenue of GSP for a particular class

  • f equilibria.
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Related Work

Position Auctions model due to [Edelman, Ostrovsky, Schwarz] and [Varian], who study revenue of GSP for a particular class

  • f equilibria.

In contrast, we study revenue of GSP over all equilibria in settings with uncertainty.

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  • n advertisers and n slots
  • slot i has click through rate
  • values per click i.i.d.
  • distributions are nice*
  • reserve price r

Position Auctions Model

* nice = regular, i.e., revenue curve is concave, e.g., uniform, exponential, normal, …

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  • Strategy for i : a bidding function
  • Assume non-overbidding
  • Bidding functions form a Bayes-Nash

equilibrium, i.e., no player benefits from changing bids even after learning their valuation

Position Auctions Model

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α1 α2 α3

Position Auctions Model

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α1 α2 α3

b1(v1) b2(v2) b3(v3)

Position Auctions Model

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α1 α2 α3

b1(v1) b2(v2) b3(v3)

Position Auctions Model

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α1 α2 α3

b1(v1) b2(v2) b3(v3)

  • Remove bids below r
  • Sort by bid
  • Charge next highest bid or r [GSP]
  • Charge a complicated function [VCG]

Position Auctions Model

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Thm: If are iid according to a regular distribution, then GSP with the appropriate reserve price r extracts at least a 1/6 fraction of the revenue of the

  • ptimal mechanism.

Our Main Result

is a Bayes-Nash equilibrium of GSPr then its revenue is at least 1/6 of the revenue of any mechanism and any equilibrium of this mechanism.

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Thm: If are iid according to a regular distribution, then GSP with the appropriate reserve price r extracts at least a 1/6 fraction of the revenue of the

  • ptimal mechanism.

Our Main Result

Why is this good ? 1/6 is an absolute worst-case theoretical guarantee. It assumes very little about distributions. The guarantee doesn’t depend on # of players, alphas,

  • r characteristics of the distribution (besides regularity).
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Our Main Result

Application: We give guidelines for setting reserve prices in GSP. Myerson’s Thm prescribes how to set reserves on VCG. [see Ostrovsky and Schwarz, EC’11] Ingredients of the proof: 1) study two cases: (i) revenue is distributed among many slots (ii) most of the revenue comes from one slot 2) passing to virtual values 3) prophet inequalities

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Revenue Welfare

Opt Welfare Opt Revenue

How does the plot of all equilibria look like? Is there an equilibrium achieving maximum revenue and social welfare ? ?

Revenue-Efficiency Trade offs

Now in the non-Bayesian world, where are fixed:

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Observation: The revenue optimal equilibrium might be inefficient.

1.2 1.0

Cost of efficiency: ratio between revenue-optimal equilibrium and revenue-

  • ptimal efficient
  • equilibrium. For vector:

Revenue-Efficiency Trade offs

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Thm 3: If CTR α are convex, then the revenue-

  • ptimal equilibrium is efficient.

Observation: The revenue optimal equilibrium might be inefficient.

i α1 α2 α3 α4 α5

Revenue Welfare

Revenue-Efficiency Trade offs

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Thm 3: If CTR α are convex, then the revenue-

  • ptimal equilibrium is efficient.

Proof Idea:

  • Structure of revenue in inefficient equilibria
  • Local improvement proof

Revenue-Efficiency Trade offs

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  • Bounds on revenue extracted by GSP

– Full Information – Bayesian setting – Revenue x Welfare tradeoffs

Conclusion

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  • Bounds on revenue extracted by GSP

– Full Information – Bayesian setting – Revenue x Welfare tradeoffs

Conclusion Thanks !