1. The Economics of Internet Search
Slides adopted from a talk by:
Hal R. Varian Google’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
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
Top-of-organic ads
RHS ads
Organic search
results 3

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
CPM: actually, Cost per Million impressions.
Web: $2 PPI
Conventional advertising: $10 CPM (superbowl far more expensive)
Bcast model: Radio was initially to communicate with ships; not a good pt2pt so turned into entertainment. Lots of debates on how to support it. Eventually commercially support radio was the winning model.

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
No exclusivity: 90% of users use Google AND 80% use Yahoo AND 75% use MSN…
Ads can play multiple roles: An impression could have javascript that goes to doubleclick
$5 to set up an AdSense account at Google!

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
Assignment: match efficiently providers and 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: to UIC - NCSA (Mosaic); to Stanford (Digital Libraries Initiative)
Link structure of Web became new explanatory variable
PageRank improved relevance of search results dramatically
Mature: CIA sponsored competitions of fast retrieval; winner was only slightly ahead of the next place

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 find while 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 1998 with 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
kaizen (Jap.)= “continuous improvement”
Every moment are 400 experiments going on at Google trying new ways of promoting ads etc.

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)
Initially they tried selling the engine to search client’s intranet
Then they tried to sell keywords - price negotiable b/w google and seller - IT DOES NOT SCALE
Overture founded by CalTech student who took a course from economist Charlie Plott (auction specialist),
who thought of auctioning off search results – went off to Bill Gross (idealab)
But people did not want their results to be auctioned off.
So they decided to split off the results! Some organic, some auctioned ads.

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 11

12. Google ads Ads are selected based on query+keywords
Ordering (Ranking) of ads based on expected revenue
Negotiation-based (used to)
Google saw Overture’s model in the Fall Came up with variation above.
Initially:
Top 2 ads sold by negotiation (price per impression)
Right 8 ads sold by auction;
TODAY: All go through auction, as we will see from the analysis later
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
There is another strategy VCG pricing: charge each advertiser with the cost he imposes on the other advertisers:
What would happen if you took each bidder out of the system? In this case the optimal value would be to bid your true value per click, no matter what the others are doing.

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
Gives set of inequalities that can be analyzed to describe equilibrium I.e., I get more value in, say, pos. 3 than I get in pos. 2.
If I increase my bid by 10%, I will increase my sales, but I pay more. Are the extra costs worth the extra value I pay?

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 v for 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.
There are 8 ad positions on the RHS.
Say there are only 4 advertisers: undersold.
The last person pays 0.05$ per clicks. The guy above him has to pay enough to capture the extra clicks.
Say they are 20 advertisers: oversold

17. Undersold pages
Bidder in each slot must be indifferent to being in last slot v = value you get ps = price you pay at slot s xs = number of clicks in slot s r = reserve value xm = 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 * * (100-80)
p1 = 14 cents, p2=5 cents
Google’s Revenue = 0.14 * * 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
Ad blindness: the average American sees 3000 ads a day; they ignore most of them!
TODAY: top ads are shown because they also have relevance, (as measured by click through, too) not just are winners of auctions
Avoid ad blindness that way!

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
AdSense gives incentives to publishers to produce new content! (even if Google were to make no money off these ads)
Google tries to buy DoubleClick; claims it is complementary business
Yahoo is power into display ad, google in contextual ads.

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…
To increase revenue, look at your “creatives” (the text around the ad)
Diamonds (want to buy some) is a more expensive keyword than Diamond (school report)
Repeating the query in the ad is better than not
Google will let you use 3 creatives, and will use the one that gives more traffic (on the fly experimentation)
Landing page should be related to the ad they clicked on – many advertisers miss it!
Once on the landing page, make it easy for them to buy it.
Maybe it may not be worth being the top bidder. Maybe too expensive.
Wine market – words to advertise: Cabernet, etc. Every wine advertiser does that, it is expensive
But “gourmet gift basket” gets a lot of relevant clicks!!! Less obvious are cheap
Keep it simple, keep it clean
But still try to figure out how to monetize YouTube: should not be intrusive
Froogle is revampled, it was not working well. Product Search now
Behavioral search does not seem that relevant!! If you are shopping, you are behaving different than your usual search.
Lots of research on Behavioral Search, not much in terms of development