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Posts Tagged ‘Google’

For those AGT/E researchers working on questions related to Ad-auctions (like most of those employed by Google/Yahoo/Microsoft), and writing nice theoretical papers for workshops like the coming “Ad auctions workshop“, it is interesting to see an overview of the messy real word, as can be found in keynote talk given by Terrence Kawaja in a recent event organized by the Interactive Advertising Bureau.

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The Future of Journalism

The Atlantic monthly published a long interesting piece on “How to save the news“.  Rather than the usual dark prophesies about how the Internet is killing journalism — “Plummeting newspaper circulation, disappearing classified ads, “unbundling” of content…” — reporter James Fallows presents “the Google point of view” which is quite optimistic.  Google’s involvement in the question may be captured by a quote from Google executive Nikesh Arora:

As long as there is great content, people will come looking for it. When there’s no great content, it’s very hard for people to be interested in finding it.

The general point of view of the article may be summerized by a quote from CEO Eric Schmidt:

Newspapers don’t have a demand problem; they have a business-model problem.

So new business models should emerge that will let newspapers do what they should do in more efficient ways, and then make money.  The current inefficiencies of the industry are of course obvious, and Google’s Chief Economist Hal Varian is quoted as saying:

Burdened as they are with these “legacy” print costs, newspapers typically spend about 15 percent of their revenue on what, to the Internet world, are their only valuable assets: the people who report, analyze, and edit the news.

What these new  business models will be is not yet clear, and the general spirit is captured by a quote from Clay Shirky of New York University:

Nothing will work, but everything might.

So are there any insights from theory?

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Google research awards

Google awards research grants, including in “economics and market algorithms”, with the next deadline coming soon on April 15th.

Proposals are very short, and there are no strings attached, but it is rather competitive and you do need a Google contact.

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Buzzing

My gmail account got “buzzed” yesterday, and I checked it out.  (While I do work for Google part-time, I knew very little about this product previously.) My initial impression is that this is indeed the “social app” for my generation: the email generation.  I have to admit that I never caught up with the younger generation who feels at home at Facebook or Twitter (or, frankly,  even SMSing).  I know that for the young of today email is something that “your teacher uses to talk to your parents”, but, hey, I am these teacher and parents.  So while I wonder with everyone how the Google Buzz vs. Twitter/Facebook thing will go in general, Buzz seems to fit my demographic quite well.

To start with, it lives where I live — in the email.  Just this tiny fact may make a huge difference for me, since I rarely bother entering Twitter or Facebook neither to check things out, nor to write a trivial message.  Now, for example, I can follow Lance’s Twitter on Buzz.  The zero-effort of buzzing means that I can even see myself Buzzing (is this the term that’s go’na catch instead of tweeting?).  Second, as buzz was automatically populated with many of my email contacts, I almost immediately have stuff to look at.  So far certainly almost all buzz that I’ve seen is from the nerdier side of my contacts, but that can change very quickly, if I extrapolate from what I see so far.  Furthermore, as the default of the “profile” page is to show the list of those that you follow or that follow you, it’s easy to “browse the followship graph” and find even more interesting people t0 follow. (Tao is buzzing too, and once you follow him you also get the items he shares from the blogs he reads.)

A bunch of other design choices also seem appropriate for me: from the simplicity of it all, to the directed followship graph (a la twitter) which is easier to swallow for me than the undirected friendship graph of Facebook.  I haven’t tried yet the geo/mobile features (I’m still 2G), or the targeted buzzing to specific subgroups, but at least their description seems simple enough.

To conclude: so far I’m a fan, with two main worries: (1) the overload of information with its time-sink effect will certainly get worse, and (2) while I rarely felt the need to be careful about my privacy online previously, I do feel the need for care in handling my privacy with Buzz.

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Facebook has announced a pretty nice graduate student fellowship program.  The first three reserach areas they mention are:

  • Internet Economics: auction theory and algorithmic game theory relevant to online advertising auctions.
  • Cloud Computing: storage, databases, and optimization for computing in a massively distributed environment.
  • Social Computing: models, algorithms and systems around social networks, social media, social search and collaborative environments.

(Hat tip to TechCrunch.)

Google has its own graduate Fellowship program (Nicolas Lambert got the 2009 Fellowship in “Market Algorithms”.)

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Google gives its employees $1/day of free adwords advertising.  Beyond an employee perk, this gives Google’s employees the experience of being an Internet advertiser, i.e. experiencing the point of view of Google’s paying customers.  I have been using my $1/day account to advertise the divorce-consulting business of my sister in law (In Hebrew) and did indeed find this experience to be quite illuminating.

The first thing I learned is that the ad auction itself is just a small part of the whole thing.  Choosing the right text for the ads (all ten words of it), choosing the right keywords to target, etc, is much more prominent than setting the right bids.  “Tiny” issues come up everywhere, e.g. when I needed to choose keywords to target, it turns out that there are four ways to write divorce in Hebrew: גירושים, גירושין, גרושין, גרושים.  I’m not really sure whether these are all “kosher” spellings, but they are all searched for an do need to be taken into account.  Even more, the whole advertising campaign is peripheral, in principle, to the business itself, and frankly the auction logic is not the first concern of the advertiser.  This is obvious, of course, but is easy to forget for one whose work focuses on the auction logic.

Now for the auction itself: all together I spent several hours setting up the campaign, making up the ads, choosing keywords, looking at reports, and trying a bit of optimization.  The adwords user interface was very easy and convenient to start with, but it didn’t take long until I was attempting things that confused me (e.g. splitting my single campaign into two different ones), at which point I gave up, and stayed with what I achieved, which is quite fine actually.  I was especially impressed with Google’s automatic suggestions of keywords which were cleverer than what I came up with (I know that not really, just some learning algorithm, but they were eerily good.)

I was surprised and disappointed (as an advertiser, but frankly delighted as a Google employee) by the pretty high prices on the keywords that I targeted: my average cost per click is 88 cents, and this is for pretty low slots, on the average.  (Divorce is expensive, it seems, also on the Internet.)  This means that my $1 per day suffices for a single click per day, and no more.  I do get this single click almost every day, but have so far been unable to ever get two clicks in one day: neither optimizing by hand, nor letting Google’s automatic bidder do it.  I was professionally insulted by not being able to beat the automatic bidder, but have still not given up on getting an average of more than one click per day for my $1.  My click through rate is pretty high (compared to my expectations):  0.79%, so I usually get about 150 impressions every day of which one is clicked and results in a visit to the website.  Now these visitors are probably really good leads: not only have they searched for relevant keywords, but they also clicked on a pretty specific ad.  I suppose that if even 1% of them become clients (this is not so little: we are not talking about buying a sweatshirt; this is about handling divorce), then the advertising would be considered quite  profitable even had my sister in law paid for it.  Unfortunately, it is quite hard to gauge whether this is the case: getting and keeping the required statistics is easier to imagine theoretically than to do when you have to handle a small business.  In other words, I haven’t a clue what my valuation of a click is.   (The lack of knowledge of one own’s valuation has been discussed in AGT, but frankly I have not seen really convincing treatment of this issue.)

The set of reports about the performance of the campaign that adwords makes available  is quite impressive, and they are really nicely and simply done, but somehow I still don’t really know how how to optimize my campaign as to get the most and the best customers to the site.  I’m sure that more time on my part, as well as a more data-centric handling of my sister-in-law’s business would improve things, but the difficulty of getting and handling the right data is another lesson that I got from this exercise (again, I knew this theoretically, but now I feel it too).

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Google Ad Exchange

Google just announced its ad exchange:

The DoubleClick Ad Exchange is a real-time marketplace to buy and sell display advertising space. By establishing an open marketplace where prices are set in a real-time auction, the Ad Exchange enables display ads and ad space to be allocated much more efficiently and easily across the web. It’s just like a stock exchange, which enables stocks to be traded in an open way.

Google's Ad-exchange

There are some existing competitors, but Google’s entry may be game-changing.  Lots of research problems beg themselves.

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HTML considered educational

My 9 year old girl is going now to an HTML summer camp. This was her choice, rather than, say, horseback riding or “molecular cooking”, mostly due to the influence of a friend (a girl too, mind you). Needless to say I was shocked by this choice: of all things related to computers, HTML syntax seems the most useless for humans to learn. And, yes, they are really learning to write these little HTML tags themselves — in notepad.

I have to admit that I’ve changed my mind. This is the first exposure that she has had to a formal language: some strange syntactic set of rules that has an attached semantic meaning. It is empowering: you can write some symbols and it does something that you intended it to do. You get immediate feedback, and can fix things if they are wrong. It is the first time that she sees why you need to follow the rules — otherwise it just won’t work. This is in contrast to what usually happens in school where all the rules for organizing her notebooks or homework may be safely ignored unless the teacher “catches” them. (Example: The way she solves 1 \frac{1}{2} + 3 \frac{1}{3} is 1 \frac{1}{2} + 3 \frac{1}{3} = \frac{3}{6}+\frac{2}{6} = 4 \frac{5}{6}, where the point is that it’s wasteful to copy the integer parts when you’re doing the common denominator.)

Now this friend of hers is really into scratch, which is real programming, and my own daughter seems to be getting into it too. Even though I did accidentally mention that scratch is programming, this didn’t seem to turn them off or appear “un-girly” to them (in fact my daughter’s first free association with programming was the Segway and free ice cream that she’s seen in Google). Starting to program may turn out to be another benefit of HTML summer camp.

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The current “killer application” for algorithmic game theory is certainly on-line advertising. The traditional advertising industry is  undergoing great turmoil due to this on-line advertising as well as other technological changes which may not only give viewers more relevant and less annoying ads, but also may start addressing the main problem from the point of view of advertisers, captured by the famous quote  “Half the money I spend on advertising is wasted; the trouble is I don’t know which half”.

This highly entertaining video is from the point of view of traditional advertising (thanks to Eyal Manor for the link).

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There are usually two different measures that auction designers attempt optimizing for: efficiency (social welfare) and auctioneer revenue. A “better” auction often improves both efficiency and revenue but in other cases these are conflicting goals. It is well known that efficiency is optimized by Vickerey Auctions while revenue is optimized by Myerson optimal auctions. I often hear cynical doubts about whether anyone optimizes efficiency rather than revenue, and specifically such disbelief regarding the big companies running ad auctions (such as my current employer, Google). As far as I can tell, reality seems to be quite the opposite: companies aim to optimize their long-term or middle-term revenue rather than the revenue of a single auction. In a competitive environment the only way of optimizing long term revenue is by gaining and maintaining market share which in turn requires providing high “added-value” i.e. optimizing efficiency.

In any case, this post points out to a paper by Gagan Aggarwal, Gagan Goel and Aranyak Mehta recently posted to the arXiv. Complementing a result of Jeremy Bulow and Paul Klemperer, they show that the difference between the two different optimization goals is not very large compared to increasing the number of bidders. The setting is the classic one of selling a single indivisible good in the private value model with a commonly known distribution over bidders’ valuations (with some mild restrictions on the distribution). The BK paper shows that the revenue of an efficiency-maximizing auction with k+1 bidder is at least as high as that of the revenue-maximizing one with k bidders. The new AGM paper shows that the efficiency of a revenue-maximizing auction with k+logk bidders is at least as high as that of an efficiency-maximizing one with k bidders (and that the logk term is necessary).

[Added on 10.6: Thanks to Tim Roughgarden for pointing out to me his closely related joint paper with Mukund Sundararajan that generalizes the BK result to an ad-auction setting, as well as provides direct revenue guarentees without increasing the number of bidders.]

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