1. 1 Teck-Hua Ho April 15, 2006 Auction Principles I. Economic and Behavioral Foundations of Pricing II. Innovative Pricing Concepts and Tools III. Internet Pricing Models

2. 2 Teck-Hua Ho April 15, 2006 Outline  Lessons from Auction Simulation Exercise  Optimal bidding and reserve price  Two important auction principles  Economics of Ebay’s Business Model  Revenue model design

3. 3 Teck-Hua Ho April 15, 2006 Independent Private-value English Auction  Buyers’ valuations (WTPs) are independent of each other (e.g., antique & art, collectibles, Jewelry & Gemstones, etc.) (for own consumption)  In our simulation exercise, buyers’ WTPs for the airline ticket are independent draws from a uniform distribution ([0, 1000])  An open English ascending bid auction  What is the optimal bidding strategy?  What is the optimal reserve price?

4. 4 Teck-Hua Ho April 15, 2006 Optimal Bidding Strategy (one seller)  If there is no snipping (auction is closed only when no bids are submitted for a certain duration), the auction theory predicts that buyers should slowly increase their bids until the highest bid exceeds their WTPs  The open English auction mechanism induces truth revealing of WTPs (price points where bidders drop from the auction)  Revenue = Second highest WTP

5. 5 Teck-Hua Ho April 15, 2006 Predicted Versus Actual Bids and Reserve Price Predicted By Auction TheoryActualBehaviors Bid as % of WTP (except winners) 99%? Reserve Price ??

6. 6 Teck-Hua Ho April 15, 2006 Prices at Each Round Round 5 Round 4 Round 3 610.0 Round 2 732.0 Round 1 3 rd highest WTP Price of 2 nd item Price of 1 st item Round 6 580.0 631.0 671.0 790.0 839.0350.0 850.0 662.0642.0 798.0760.0 630.0613.0 674.0650.0

7. 7 Teck-Hua Ho April 15, 2006 Predicted Versus Actual Bids and Reserve Price Predicted By Auction TheoryActualBehaviors Bid as % of WTP (except winners) 99%95.5% Reserve Price 500

8. 8 Teck-Hua Ho April 15, 2006 Expected Seller Revenue (one seller)  Let buyer WTPs (independently drawn from an uniform distribution) are denoted by WTP 1, WTP 2, …, WTP n-1, WTP n  Arrange them in an ascending order and denote ranked bids by WTP (1), WTP (2), …, WTP (n-1), WTP (n). That is, we have WTP (1) < WTP (2) < …< WTP (n-1) < WTP (n)  Expected Revenue:

9. 9 Teck-Hua Ho April 15, 2006 Expected Revenue versus Number of Bidders

10. 10 Teck-Hua Ho April 15, 2006 Optimal Reserve Price (one seller) (uniform distribution)  Optimal reserve price:  If the reserve price is smaller than the second highest WTP, reserve price has no revenue effect on the bidding process  If it is between the highest and the second highest WTPs, it will force the highest bidder to go beyond the second highest WTP (the point where the second highest bidder drops out).

11. 11 Teck-Hua Ho April 15, 2006 Predicted Versus Actual Bids and Reserve Price Predicted By Auction TheoryActualBehaviors Bid as % of WTP (except winners) 99%95.5% Reserve Price 500289

12. 12 Teck-Hua Ho April 15, 2006 Revelation Principle  Revelation Principle: All buyers (except the winner) end up revealing their WTPs for the item to the sellers. Put differently, sellers can “discover” distribution of buyers’ WTPs via the auction mechanism. This is not the case for other pricing mechanisms (e.g., seller posted price and priceline model)  Application: Use open English auction to discover the distribution of WTPs and then use seller posted price model to maximize share of surplus

13. 13 Teck-Hua Ho April 15, 2006 Efficiency Principle  Efficiency Principle: The auction mechanism guarantees that the item always goes to the buyer with the highest WTP in a market. Again, this is not always the case for other pricing mechanisms  (inefficiency = 0% (predicted) versus 1.6% (actual))  Observation: Auction model is likely to dominate the other price models in terms of total social surplus generated.

14. 14 Teck-Hua Ho April 15, 2006 Maximum Possible Surplus (MPS) Seller 1 c=0 Seller 2 c=0 Buyer 1 40 Buyer 2 20 Buyer 3 15 Buyer 4 90 Buyer 5 60 Buyer 6 50 WTP MPS = 40 + 90 + 60 + 50 = 240

15. 15 Teck-Hua Ho April 15, 2006 The Winning Team  The winning team is: Group 4  The prize is:

16. 16 Teck-Hua Ho April 15, 2006 Disadvantages of Auctions  Can be stressful for some buyers, especially for end consumers (this can be however solved by proxy bidding). Thus, it is less likely to work for low purchase-involvement product categories  There are more losers than winners (and losers are less likely to revisit the website)  Strategic manipulation (e.g., shilling)

17. 17 Teck-Hua Ho April 15, 2006 Next Class: Design of Auction Format  Dutch auction (D) (e.g, www.landsend.com ) www.landsend.com  First-price sealed-bid auction (F) (e.g., US Treasury bills, supply contracts; government procurement (10% GDP))  Second-price sealed-bid (Vickrey) auction (S) (e.g., www.sandafayre.com; NZ’s communication spectrum rights) www.sandafayre.com  English auction (E) (e.g., www.ebay.com ; www.yahoo.com )www.ebay.com www.yahoo.com

18. 18 Teck-Hua Ho April 15, 2006 Ebay’s business model Seller Buyer Seller & Buyer Price Setting Party Price Over Time Static Dynamic ebay.com http://www.ebay.com/

19. 19 Teck-Hua Ho April 15, 2006 Ebay’s Current Status in 2004  Listings - New listings totaled a record 348.0 million in Q3-04, 48% higher than the 234.6 million listings reported in Q3-03.  Confirmed Registered Users - Cumulative confirmed registered users at the end of Q3-04 totaled a record 125.0 million, representing a 46% increase over the 85.5 million users reported at the end of Q3-03.  Active Users - Active users, the number of users on the eBay platform who bid, bought, listed or sold an item over the trailing 12 months, increased to 51.7 million, a 38% increase over the 37.4 million active users reported in the same period a year ago.

20. 20 Teck-Hua Ho April 15, 2006 Ebay’s Original Revenue Model  M = Total number of items listed per year  Fee i = Insertion fee of item i  Com i = Final value fee of item i  I i = 1 if item i is sold; 0 otherwise M depends on number of people in the community Com i x I i increases with price or seller surplus Revenue Levers

21. 21 Teck-Hua Ho April 15, 2006 Ebay’s Original Revenue Model Biggest strength of the revenue model: Revenues increase linearly with M but costs do not increase with M. (scalability property)

22. 22 Teck-Hua Ho April 15, 2006 Ways to Enhance Ebay’s Revenue  Increase M  Increase size of community,  Enter new markets and product categories  Increase turnover (e.g., reduce bidding duration, encourage setting of buyout prices)  Increase Fee i  Encourage more pictures and promotion of items  Increase Com i  Increase average number of bidders / auction (so as to increase seller surplus)  Encourage high-priced items (e.g., electronics, cars)  Increase I i  Increase average number of bidders / auction so as to increase the probability that the highest bid > reserve price  Encourage a lower reserve price (e.g., the recent increase in insertion fee for reserve price auction)

23. 23 Teck-Hua Ho April 15, 2006 EBay’s Revised Revenue Model  Fees to list an item  for regular auctions, fees is a function of starting price  for vehicles, a function of type of vehicles  for real estate, a function of types of properties and listing type  Picture Service Fees—first picture free, additional picture or bigger picture incurs fees  Listing upgrade fees: various options to promote items  Final value fees  for regular auction, charged when reserve met, at a function of the closing bid  For vehicles, charged when the first bid over the reserve price is placed (regardless of whether sale is finally made)  For real estate, a fixed fee for land/time share where there is successful high bid on the item and no fees for other type of real estates  Reservation Price Fees—charged only if item not sold, a function of reserve price

24. 24 Teck-Hua Ho April 15, 2006 Ways to Enhance Customer Experience  Bidder Management  Smart search capability to narrow consideration set  Winner Management  Trust and safety initiatives  Loser Management: For every winner, there are (n-1) losers. Find ways to get them to bid again:  Follow-up emails on availability of related items  Seller Management  Loyalty programs for frequent sellers

25. 25 Teck-Hua Ho April 15, 2006 Recipe for Continued Market Leadership  Liquidity, liquidity, liquidity  Keep Existing Customers Happy  Increase switching costs  Increase post-auction satisfaction  Acquire New Customers  New markets (e.g., Canada, UK, China, etc.)  New products (especially high-priced items)  Direct acquisition of customers / sites

26. 26 Teck-Hua Ho April 15, 2006 Punchline  Open English Auction  Revelation Principle  Efficiency Principle  Ebay’s Business Model  Revenue increases with seller surplus  Liquidity promotes lock-in: Keep existing customers happy and acquire new customers  Diversification: New markets and new products (especially high-priced items)

27. 27 Teck-Hua Ho April 15, 2006 Exercise on Revenue Model Design  Visit google answers: http://answers.google.com/answers/http://answers.google.com/answers/  Figure out its revenue model and levers?

28. 28 Teck-Hua Ho April 15, 2006 Google Answers’ Revenue Model  M = Total number of questions posted per year  $0.50= A posting fee of 50 cents per question  I i = 1 if question i is answered; 0 otherwise  P i = Buyer’s posted price for question i  S i = 1 if question i has sponsored links; 0 otherwise  NC i = Number of clicks for question i  AD i = Average fee per click http://answers.google.com/answers/faq.html#cost