The Economics of Internet Search

1. The Economics of Internet Search Slides adopted from a talk by: Hal R. VarianGoogle’s Chief Economist UC Berkeley Economics Prof. Sept 31, 2007

2. Search engine Advertisement • Search engines are highly profitable • Revenue comes from selling ads related to queries • 99% of Google’s revenue come from ads • Yahoo, MSN also uses similar model • Banner ads (Doubleclick) • Standardized ad shapes with images • Loosely related to content • Context linked ads (Google AdSense) • Related to content on page • Search linked ads (Google Adwords) • Related to search terms Banner ad Content ads

3. Search engine Advertisement Top-of-organic ads RHS ads Organic search results • Search engines are highly profitable • Revenue comes from selling ads related to queries • 99% of Google’s revenue come from ads • Yahoo, MSN also uses similar model • Banner ads (Doubleclick) • Standardized ad shapes with images • Loosely related to content • Context linked ads (Google AdSense) • Related to content on page • Search linked ads (Google Adwords) • Related to search terms

4. Search engine ads • Ads are highly effective due to high relevance • But even so, advertising still requires scale • 2% of ads (“impressions”) might get clicks • 2% of clicks might convert into sales • So only 4 / 1000 who see an ad actually buy • Cost Per Million impressions (CPM) will not be large • But this performance is good compared to conventional advertising! • Search technology exhibits increasing returns to scale • High fixed costs for infrastructure, low marginal costs for serving

5. Advertising industry economies • Entry costs (at a profitable scale) are large due to fixed costs • Very low incremental cost for 2nd ad • User switching costs are low • 56% of search engine users use more than one • (but 44% use only one…) • Advertisers follow the eyeballs • Place ads wherever there are sufficient users, no exclusivity • Hence market’s structure is likely to be • A few large search engines in each language/country group • Highly contestable market for users • No demand-side network effects that drive towards a single supplier so multiple players can co-exist

6. What services do S.E.’s provide? • Google is yenta (matchmaker) • Matches up those seeking info to those having info • Matches up buyers with sellers • Relevant disciplines • Computer Science: • Theory of information retrieval • Economics: • The assignment problem: Match efficiently providers to consumers

7. The advent of the web • By mid-1990s IR algorithms were very mature • Very little difference in IR competitions (mostly CIA sponsored) • The Web comes along • IR researchers were slow to react • CS researchers were quick to react • Crucial NSF grants: 1993 to UIC - NCSA (Mosaic); 1994 to Stanford (Digital Libraries Initiative) • Link structure of Web became new explanatory variable • PageRank improved relevance of search results dramatically

8. Google’s birth • Brin and Page tried to sell algorithm to Yahoo for just $1 million • Yahoo did not buy it;they believed that search was in a commodity business, nothing new to findwhile Yahoo is in the Directory business, it adds value to information • Most people thought this way, banner ads were the only (boring) game • They formed Google in late 1998with no real idea of how they would make money • Put a lot of effort into improving algorithms • Started selling intranet services (they still do) • Then tried selling keywords (like everyone else) via negotiation

9. Why online business are different • Online businesses (Amazon, eBay, Google…) can continually experiment • Hard to really do continuously for offline companies (they sell a product) • Manufacturing • Services • Very easy to do continually for online companies (they sell online service) • Leads to very rapid (and subtle) improvement • Learning-by-doing leads to significant competitive advantage

10. Business model (aka: how to make money out of it?) • Initially: sell keywords • All SE’s and Dir’s did it; it does not scale • Then: Sell search ranking • But people did not like their ranks be ad-driven • They split the results: some organic, some ad-driven (2000) • GoTo Ad Auction • GoTo’s model was to auction search results • Changed name to Overture, auctioned ads • Google liked ad auction, tried to improve on Overture’s model (2001) • Lawsuit by Overture (2002) settled in 2003 • Google licenses technology from Yahoo (bought Overture for $1.63B)

11. Original Overture model • Rank ads by bids • Ads assigned to slots depending on bids • Highest bidders get better (higher up) slots • High bidders pay what they bid (1st price auction) (about $0.50) • How-to bid example: • Conversion Rate = 1% sales per click • Net profit per sale = $20 • If you bid PPC=$0.20/click, you are expected to break even

12. Google ads • Ads are selected based on query+keywords • Ordering (Ranking) of ads based on expected revenue Negotiation-based (used to) Auction-based

13. Google’s auction version • Rank ads by expected revenue • This makes sense: revenue = price * quantity • Expected revenue = bid * expected clicks • But you sell impressions, so price /impression = Price /click * clicks /impression • Each bidder pays price determined by bidder below him • Price = minimum bid necessary to retain position • Motivated by engineering, not economics • People would do it by trial & error anyway… • Overture (now owned by Yahoo) • Adopted 2nd price model in 2007 • Increased their revenues

14. Google and Game theory • When everyone bids optimally, we have Nash equilibrium • Basic principle of equilibrium: each bidder prefers the position he/she is in to any other position • Gives set of inequalities that can be analyzed to describe equilibrium • Inequalities can also be inverted to give values as a function of bids • The highest value people end up in higher positions

15. Implications of analysis • Basic theoretical result: incremental cost per click has to be increasing in the click through rate. • Why? If incremental cost per click ever decreased, then someone bought expensive clicks and passed up cheap ones. • Similar to classic competitive pricing in economics • Price = marginal cost • Marginal cost has to be increasing

16. Simple example • Suppose all advertisers have same value vfor click • Two cases: • Undersold auctions: There are more slots on page than bidders.r = The minimum price per click (the “reserved price”) (say, 5 cents). • Oversold auctions: There are more bidders than slots on page. Last bidder pays price determined by 1st excluded bidder.

17. Undersold pages • Bidder in each slot must be indifferent to being in last slotv = value you getps = price you pay at slot sxs = number of clicks in slot sr = reserve valuexm = number of clicks in last position • Payment for slot s = payment for last position + value of incremental clicks

18. Example of undersold case • Two slots • x1 = 100 clicks • x2 = 80 clicks • v = 0.50 • r = 0.05 • Solve equation • P1 * 100 = 0.05 * 80 + 0.50 * (100-80) • p1 = 14 cents, p2=5 cents • Google’s Revenue = 0.14 * 100 + 0.05 * 80 = $18

19. Oversold pages • Each bidder has to be indifferent between having his slot and not being shown: • So • For previous 2-slot example, when 3 bidders: ps=50 cents for each slot, and Google’s revenue = 0.50 x (100+80) = $90 • Revenue takes big jump when advertisers have to compete for slots!

20. How Google determines number of ads shown • Showing more ads • Pushes revenue up, particularly moving from undersold to oversold • But relevancy goes down (irrelevant ads will sneak in)=> Users click less in future (“ad blindness”) • Optimal choice • Depends on balancing short run profit against long run goals • Top-of-organic vs RHS ads • Initially top ads sold negotiated, but RHS revenue much higher • Now all are auctioned, but for top ads are only selected if they are very relevant • If you only see RHS ads: they were good enough to be shown, but not so relevant to be on top of organic

21. Other forms of online ads • Contextual ads • AdSense puts relevant text ads next to content • Treats the content of the page as a query! • Publisher (content owner) puts some Javascript on page and shares in revenue from ad clicks • Display ads (aka “Rich Media Ad”) • Advertiser negotiates with publisher for CPM (price) and impressions(at specific time, for specific audience, for up to X impressions/viewer) • Ad server (e.g. Doubleclick) serves up ads to pub server • Are more sophisticated than simple ads (e.g. max num of impr/IP addr.) • Ad effectiveness • Increase reach • Target frequency • Privacy issues

22. Monitoring and fine-tuning

23. Opportunities for employment • “Marketing as the new finance” • Availability of real time data allows for fine tuning, constant improvement • Market prices reflect value • Quantitative methods are very valuable • We are just at the beginning…