! Search engines are highly profitable. n 99% of Google s revenue from ads. n Yahoo, bing also uses similar model

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1 Search engine Advertiement The Economic of Web Search! Search engine are highly profitable Revenue come from elling ad related to querie 99% of Google revenue from ad Yahoo, bing alo ue imilar model CS315 Web Search and Data Mining Slide adopted from a talk by: Hal R. Varian, Google Chief Economit, UC Berkeley Economic Prof.! Banner ad (Doubleclick) Standardized ad hape with image Looely related to content! Context linked ad (Google AdSene) Related to content on page! Search linked ad (Google Adword) Related to earch term Content ad Promoted ad Organic earch reult Banner ad Sponored ad Search engine ad! Ad are highly effecxve due to high relevance But even o, adverxing Xll require cale w 2% of ad ( impreion ) might get click w 2% of click might convert into ale w So only 4 / 10,000 who ee an ad actually buy w Cot Per Million impreion (CPM) will not be large w But thi performance i good compared to convenxonal adverxing!! Search technology exhibit increaing return to cale High fixed cot for infratructure, low marginal cot for erving What ervice do S.E. provide?! Search engine are matchmaker Match up thoe eeking info to thoe having info Match up buyer with eller! The aignment problem: Match efficiently provider to conumer! Computer Science meet Economic 1

2 The advent of the web! By mid IR algorithm were very mature Very liale difference in IR TREC compexxon motly DARPA- ponored Excluively baed on claic IR content matching! The Web come along CS reearcher were quick to react Crucial NSF grant: 1993 to UIC - NCSA (Moaic); 1994 to Stanford (Digital Librarie IniXaXve)! Link tructure improve relevance of earch reult dramaxcally Google wa not born to be an ad co.! Brin and Page tried (and failed ) to ell algorithm to Yahoo for jut $1 million Yahoo believed that earch wa in a commodity buine, nothing new to find Yahoo wa in the Directory buine, adding value to informaxon Mot people thought thi way, banner ad were the only (boring) game! Google i created in late 1998 with no real idea of how they would make money Put a lot of effort into improving algorithm Started elling intranet earch device Then tried elling keyword (like everyone ele) via negoxaxon Online v Brick & Mortar buine! Kaizen (Jap.): conxnuou improvement You need to experiment conxnually in order to improve! Hard to conxnually experiment for offline companie (they ell a product) Manufacturing! Very eay to experiment conxnually for online companie (they ell online ervice) Amazon, ebay, Google Lead to very rapid (and ubtle) improvement Yellow or blue ad background? What ize font? Learning- by- doing lead to ignificant compexxve advantage Buine model (aka: how to make money out of it?)! IniXally: ell keyword college fellowhip priced at $5/million impreion. Why $5? All SE and Dir did it; it doe not cale; it doe not feel fair! Then: Sell earch ranking They plit the reult: ome organic, ome ad- driven (2000) But people did not like their rank be ad- driven! GoTo Ad AucXon GoTo model wa to aucxon earch reult did not work Changed name to Overture, aucxoned ad looked promiing Google liked ad aucxon, tried to improve on Overture model (2001) Lawuit by Overture (2002) ealed in 2003 Google licene technology from Yahoo (bought Overture for $1.63B) 2

3 Original Overture/Yahoo Model Google Ad Model! Rank ad depending on bid Higher bidder get higher up lot! High bidder pay what they bid (1 t price aucxon) (about $0.50)! How- to bid example: Converion Rate = 1% ale per click Net profit per ale = $20 If you bid PPC=$0.20/click, you are expected to break even Negotiation-baed (ued to) Auction-baed! Ad are elected baed on query+keyword! Ranking of ad i baed on expected revenue! Now alo ued by Yahoo/Overture, bing Google Auction Verion! S.E. really aucxon impreion, o it can et price /impreion = Price /click * click /impreion! Rank ad by expected revenue expected revenue = bid * expected click Thi make economic ene: revenue = price * quanxty! Next- bidder- price: Each bidder pay price determined by bidder below Price = minimum bid neceary to retain poixon MoXvated by engineering, not economic: People would do it by trial & error anyway, conxnuouly manipulaxng price, overloading your erver, Auctioning in Game Theory! When everyone bid opxmally, we have Nah equilibrium! Baic principle of equilibrium: each bidder prefer the poi>on he i in to any other poi>on You are in poixon 3; If you bid a liale more, you end up in poixon 2, where you get more click and gain ome more money. I the bid increae worth the extra gain? Similarly if you bid a liale le i bid decreae worth the aving?! It give et of inequalixe that can be analyzed to decribe equilibrium InequaliXe can alo be inverted to give value a a funcxon of bid The highet value people end up in higher poixon 3

4 Implication of analyi! Baic theorexcal reult: incremental cot per click ha to be increaing in the click through rate.! Why? If incremental cot per click ever decreaed, then omeone bought expenive click and paed up cheap one. Simple example! Suppoe all adverxer have ame value v for click! Two cae: Underold aucxon: There are more lot on page than bidder. r = The minimum price per click (the reerved price ) (ay, 5 cent). Overold aucxon: There are more bidder than lot on page. Lat bidder pay price determined by 1 t excluded bidder. Underold Auction Example of Underold cae! Equilibrium mean: Bidder in each lot mut be indifferent to being in lat lot ( v p ) x = ( v r) x v = value you get p = price you pay at lot x = number of click in lot r = reerve value x m = number of click in lat poixon p x = rx m + v(x x m )! Price you pay for lot = payment for lat poixon + value of incremental click m! Two bidder x 1 = 100 click x 2 v = 80 click = 0.50 r = 0.05! Solve equaxon P 1 * 100 = 0.05 * * (100-80) p 1 = 14 cent, p 2 =5 cent ( v p ) x = ( v r) x Google Revenue = 0.14 * * 80 = $18 p x = rx m + v(x x m ) m 4

5 Overold Auction How to determine how many ad to how! Each bidder ha to be indifferent between having hi lot and not being hown:! So (v p )x = 0 p = v! Example: 2- lot, 3 bidder: p =50 cent for each lot, and Google revenue = 0.50 x (100+80) = $90! Revenue take big jump when adverxer have to compete for lot!! The vat majority of Google revenue come from overold aucxon.! Showing more ad Puhe revenue up, parxcularly moving from underold to overold But relevancy goe down (irrelevant ad will neak in) => Uer click le in future ( ad blindne )! Google emphaize Ad Quality What doe thi mean, really?! An ad that look a good a the organic reult?! Other form of online ad Analytic: Monitoring & fine-tuning! Top- of- organic v RHS ad IniXally top ad old negoxated, but RHS revenue much higher Now all are aucxoned, but for top ad are only elected if they are very relevant If you only ee RHS ad: good enough to be hown, but not relevant enough for top of organic! Contextual ad AdSene put relevant text ad next to content Treat the content of the page a a query! Publiher (content owner) put ome Javacript on page and hare in revenue from ad click! Ad effecxvene Increae reach Target frequency Privacy iue 5

6 Google Analytic Tag <cript type="text/javacript"> var gajhot = ((" == document.location.protocol)? " : " document.write(unecape("%3ccript rc='" + gajhot + "googleanalytic.com/ga.j' type='text/javacript'%3e%3c/cript%3e")); </cript> <cript type="text/javacript"> var pagetracker = _gat._gettracker("ua "); pagetracker._etdomainname("none"); pagetracker._etallowlinker(true); pagetracker._etcookietimeout(" ") pagetracker._initdata(); pagetracker._trackpageview(); Teting enable marketer to improve ite performance by making incremental change Identify variable of the page (homepage, landing page) and tet combination to determine what work bet together. Example Variable: Headline, Button, Offer, Button Text, Color, Text, Picture Create a client ide log file, intead of a erver log Google Web Site Optimizer What happened to Spammer? 6