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Q2: How does Google sell ad spaces? . Mung Chiang Networks: Friends, Money, and Bytes . How to sell online ad spaces?. Different goals: Seller vs. Buyers 1994: Impression-based ($ per 1000 impressions) 1997: Click-based 2002: Auction-based Google AdWords
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Q2: How does Google sell ad spaces? Mung Chiang Networks: Friends, Money, and Bytes
How to sell online ad spaces? • Different goals: Seller vs. Buyers • 1994: Impression-based ($ per 1000 impressions) • 1997: Click-based • 2002: Auction-based • Google AdWords • Search advertisements / sponsored content
Question 1 • Where will your ad appear? • Different spots have different values • Each has an expected clickthrough rate C • Assume R is independent of the ad placed there
Question 2 • How do advertisers pay Google? • When you actually click • Assume actual clickthrough rate is also C
Question 3 • What’s in it for the advertisers? • Revenue depends on • C: average clicks per hour • R: average revenue per click • C * R: average revenue in dollar per hour • Call this the valuation of the ad space to the buyer
Auction • From Roman Empire to eBay and Google • 1 seller (Google) • N buyers (advertisers) • K items (ad spaces) • Buyers: submit bids • Seller: • Allocate items to buyers • Charge each buyer
Single item public auction • Ascending price • Descending price
Single item sealed envelope • First price • Second price • Does it make sense?
Multiple items • Generalized Second Price (GSP) • Vickrey–Clarke—Groves (VCG)
Why auctions? • Resource allocation • Private valuation • Independent valuation
What does each party want? • Seller: revenue • Buyers: payoff • Auction designer: • Efficient and fair • Truthful bidding
Auction as a game • Set of players • Strategy space per player • Payoff function per player
Designing an auction • Different auction rules induce different bidding behaviors • First price: • Second price:
Second price (single item) • Decoupling of allocation and pricing • Truthful bidding is a dominant strategy: b=v • Why not b < v ? • Why not b > v ?
Still a mystery? • Why not third price? • Anything special about second price? • Internalize the negative externality • Pay for what you damaged
eBay • Second price with 4 twists: • (Optional, secret) reserve price • Some information displayed • Fixed and public horizon • Proxy agent
Example: Day 0 • Duration: 5 days • Start price: $5 • Minimal increment: $1 • Reserve price: $5
Day 1 • Alice users proxy agent • Maximum bid: $12 • Highest bid: • Ask price:
Day 2 • Bob bids $8 • Highest bid: • Ask price:
Day 3 • Bob bids $10.5 • Highest bid: • Ask price:
Day 4 • Bob bids $17.5 • Highest bid: • Ask price:
Day 5 • Chris bids $18 • Highest bid: • Ask price:
End • Winner: • Price:
GSP • Bidding: • Allocation: • Charging:
Detour • Why not let each buyer submit multiple bids? (not just all multiples of a common number R) • Other types of bipartite graphs and matching
Example • Bidding: Assume truthful • Allocation: • Charging:
Example • Revenue to Google: • Payoffs to buyers: • Total payoff:
GSP or VCG? • Beyond Google ad search: e.g., AppNexus • Truthful bidding • Simplicity of explanation • Multiple parallel auctions • Irrational behavior
Many more we haven’t • Simultaneous auctions • Reverse auctions • Multiple winner auctions • …
Summary • Auctions allocate items among competing buyers • Different auction rules induce different bidding behavior • Pricing based on externality induces truthful bidding