Microsoft and Yahoo, kissing behemoths

It looks like we have a Microsoft-Yahoo deal. If you smack two amorous giants together enough times, I guess you are going to get a love child.

I doubt Google has much to fear from the laggard that likely will result. Just as two wrongs don't make a right, combining two struggling organizations is unlikely to fix dysfunction.

I hope I am wrong. If the deal provides focus rather than distractions, if it allows both organizations to rapidly iterate on, develop, and deploy products people actually want, it has some chance of succeeding.

But, as separate groups, both organizations barely can control the internal squabbling of hordes of product managers, "none f-ing getting anything done", as Carol Bartz colorfully put it. Combined, someone will have to keep these beasts from pulling on and tripping over each other while they desperately pursue the leader of the pack.

Update: Excellent commentary on the deal by Danny Sullivan, Jason Calacanis, and Saul Hansell.

Facebook versus Google?

Greg Sterling has some good thoughts on why Facebook and Google are not in competition:

Currently the use cases for Facebook and for search are quite different.

Facebook is entertaining, Facebook is fun, Facebook kills time, Facebook enables me to keep in touch with people. But Facebook, generally speaking, is not "useful" in the sense that Google is.

For its part, Google delivers information efficiently but is generally not "entertaining" or "fun."

It's very likely that the two sites will simply co-exist fulfilling different types of needs and interests ... Neither can be expected to fundamentally undermine the core business of the other.

But what are Facebook and Google's core businesses?

It is true that the uses of Facebook and Google differ. People mostly seem to go to Facebook because they find it entertaining. People mostly go to Google because it is useful.

But, the core business of both, where they get their revenue, is from advertising. And, while Google's search advertising does quite well, they have struggled much more in non-search advertising. And non-search advertising is the problem Facebok needs to solve.

Toward the end of the Fred Vogelstein's Wired article (which Greg Sterling references), Fred pinpoints the critical area of conflict:

Facebook [is] confronted with a difficult challenge: turning [their] massive user base into a sustainable business.

[Google] inked a disastrous $900 million partnership with MySpace in 2006, a failure that taught them how hard it is to make money from social networking. And privately, [Googlers] don't think Facebook's staff has the brainpower to succeed where they have failed.

"If [Facebook] found a way to monetize all of a sudden, sure, that would be a problem," says one highly placed Google executive. "But they're not going to."

Google's thin client distraction

Recently, Chris O'Brien at the San Jose Mercury News wrote:

It's getting harder every day to articulate what Google is. Is it a Web company? A software company? Something else entirely?

It's not just that it's hard to see how [Google's operating systems] fit into Google's stated mission. It's also that it's hard to explain to someone exactly what they are, or why they might, or might not, want to use them. Or to communicate why they are different from or better than any other things out there.

These new products have the whiff of engineers building things for other engineers, rather than you and me.

Even worse, these new products have the whiff of executives being unable to let go of their past battles.

For decades, Google CEO Eric Schmidt led Sun and Novell in mostly failed attempts to build thin client computers. At Google, Eric appears to be doing it again.

But Google is not a computer company. It is an advertising company. Google makes its money from advertising.

It is not as if there isn't enough to do in advertising. Despite Google's success in making search advertising more useful and helpful, most other advertising remains awful.

Fixing advertising not only would be lucrative, but also it directly fits into Google's mission to "organize the world's information and make it universally accessible and useful." At their best, ads provide useful information about interesting products and services. Right now, most contextual and display advertisements are more annoying than useful. It doesn't have to be that way.

If Google could be the solution to annoying advertising, it could reap all the rewards. Instead, Google is being led off by its generals to fight the last war.

Time effects in recommendations

The best paper award at the recent KDD 2009 conference went to Yehuda Koren's "Collaborative Filtering with Temporal Dynamics" (PDF).

The paper is a great read, not only because Yehuda is part of the team currently winning the Netflix Prize, but also because it has some surprising conclusions about how to deal with changing preferences and interests over time.

In particular, it is common in recommender systems to favor recent activity, such as more recent ratings by a user, either by only using the last N data points or by weighting more recent data more heavily. But Yehuda found that ineffective on the Netflix data:

The consistent finding was that prediction quality improves as we moderate ... time decay, reaching [the] best quality when there is no delay at all. This is despite the fact that users do change their taste and rating scale over the years.

Underweighting past action loses too much signal along with the lost noise, which is detrimental given the scarcity of data per user .... We require an accurate modeling of each point in the past, which will allow us to distinguish between persistent signal that should be captured and noise that should be isolated .... for understanding the customer ... [and] modeling other customers.

As in some of Yehuda's past work, he combines two models, one a latent factor model, the other an item-item approach. The models yielded "the best results published so far" on the Netflix data set by allowing them to represent temporal effects such as finding stronger relationships between items related in a short timeframe, handling that people tend to give higher ratings to older movies (if they bother to rate them at all), allowing for people to shift to giving higher or lower ratings on average over time, and capturing that people tend to use the same rating for multiple items rated in a short timeframe.

The paper is full of other cute tidbits too, like that they tried to detect day of the week effects -- do people rate lower on Mondays? -- but could not. They also discovered an unusual jump in the average rating in the data in 2004, which they hypothesize was due to features launched on the Netflix.com site that started showing people more movies they liked. Definitely worth a read.

Ad fatigue and relevance

At the recent Ad Auctions Workshop, I had a paper (PDF) and talk (PDF) that argued for discounting relevant advertisements more than we currently do.

To briefly summarize, if seeing bad ads causes people to look at ads less in the future (aka ad fatigue), then we should change our pricing in advertising auctions to promote relevant, useful ads. Likewise, we should charge bad ads more to compensate for the damage they cause.

The paper is not trying to be definitive. The paper only shows that ad fatigue could matter, not that it does actually matter. More work needs to be done to measure how much ad fatigue actually exists.

But, I hope this paper might motivate others to look more at ad fatigue, think more about long-term revenue instead of short-term revenue, and consider how it might be beneficial in the long-term to lower our pricing on relevant and useful advertisements.

The paper was done with Chris Meek from Microsoft Research and Max Chickering at Microsoft. It reports on a side project I did a year ago while at Microsoft Live Labs.