Can Facebook feed its ad brains?

Facebook is now valued at $15 billion by many estimates. Soon the young company will have to prove it's really worth it.

Next week in New York, Facebook is expected to unveil its new advertising strategy on the heels of an expanded advertising partnership and $240 million investment from Microsoft. The company will likely talk about selling targeted ads to members, but experts say that to build its own ad serving system, Facebook must figure out how to serve the right ads to the right people in real time.

"That's a very difficult problem at large scale, with so many ads and millions of people," said Greg Linden, founder of Findory and an architect of Amazon.com's early product recommendation and personalization engine. "And the data's not well tied to purchases like at Amazon, or even like Google, where so many Web searches are about products."

The predominant question on everyone's mind is: Can Facebook build an ad system clever enough to keep pace with the passing fancies of its social-networking members? Facebook will have to get really good at processing all of the data it has collected on its reported 49 million members--demographics, personal preferences, and social histories--to predict what advertisements they might actually like and respond in their "news feed" or next to their "wall," according to industry executives.

That's no small task. In fact, it's a massive computing problem and one that very few companies apart from Google and Amazon have mastered. That's why Facebook--a company known for its young, fun culture--has been trying to hire more seasoned experts in so-called machine learning who can develop the right algorithms for a new generation of targeted advertising, people familiar with the company say.

One tech executive characterized the challenge like this: "The company that can process the most data will win." That maxim has proven true of Google in Web search and Amazon in e-commerce sales and product recommendations. Now Facebook must figure out how to take billions of data points about its members and turn that into an automatic ad machine.

A Facebook representative declined comment for the story.

There's no question Facebook is sitting on a data goldmine, with an exhaustive amount of information on people's preferences, backgrounds, and social histories--all given voluntarily by members. Facebook has profiles that include people's favorite music, television shows, books, and hobbies; their job history, education, birth date, and marital status; as well as daily activities, social networks, and interest groups. Traditional ad networks would kill for all that information in one place.

But with that data comes some interesting machine learning problems, experts say.

"The problem isn't that they can't make revenue, it's that the expectation is so high on the amount of revenue that they can make."

--Greg Linden, Findory founder

Machine learning is a broad term in the field of artificial intelligence. It refers to developing algorithms that can discover patterns in data and learn from them. Google, for example, has used probabilistic Bayesian models to serve results to data searches based on keywords. With advertising, it's all about matching the right person to the right ad. And on an individual level, that's a tall order.

So some technologists focus on lumping people into groups or types, tracking their typical behaviors in aggregate, and then trying to predict what they might want or do next.

Machine learning in online advertising might involve trying many different techniques on affinity groups to figure out which work best. That's because no one obvious technique is the silver bullet for social networks--no one has solved the problem of serving ads in that setting before.

Many thorny issues can arise, too, such as trusting what people post about themselves. Social networks can be noisy in terms of data, meaning that one day a member can say he broke it off with a girlfriend and change everything about his music and film tastes. On social networks, people are prone to misspellings, random statements, and exaggeration. Also, Web surfers are on Facebook to socialize, network, or be entertained, not to buy something. In that kind of social environment, ads can be ineffective or annoying.

That's why Facebook must perfect a subtle product placement or recommendation system. To do it, it will have to invent algorithmic tricks. For example, knowing a list of people's friends isn't necessarily useful unless the system could automatically remind people of birthdays, and then advertise a specific gift the friend might like based on his or her preferences.

Aggregate Knowledge in Palo Alto, Calif., which is backed by Google investor Kleiner Perkins Caufield & Byers, may also have an ad solution for social networks. Aggregate has developed algorithms to determine what are called "affinity clusters" of people and, based on the personality profiles of those people, targets ads. It does this by looking at people's habits in aggregate, rather than as individuals.

[Ouch!]

Big Fat White Elephant

BaceFook will prove to be MicroGate's Big Fat Elephant in the room:

48 million clients? No @$%*^# way! Did they start April 1st?

And No doubt everyone is sitting at their keyboards waiting for the next ad to be flashed at them!

100 to 1 this will turn out to be a hoax! Watch out for the knock-on effect!

[Tomcat Adam]

...

Obviously you have never been to the site...

[Broward Horne]

Consolidation Phase

Facebook's current growth rate is unsustainable and will peak out around summer of 2008.

http://www.realmeme.com/roller/page/realmeme?entry=social_networking_meme

My email to Facebook in 2006 suggested that social networking was entering a consolidation phase. With the introduction of their API and now Google's OpenSocial API, it's clear that the context is now about taking existing customers from other social networking sites.

My extrapolation of Facebook's growth rate is based on the concept that there are finite # of customers and most of those are already in play.

[Sea of Cortez]

Face book = being scammed by Nigerians

I posted a few things for sale on Facebook and I all have gotten is one message from Nigerian scam artists after another :(

You the messages that goes like we want to buy your car, but to buy it you need to ship to us, so send us $1250 for the shipping cost and
we will then send you $15K for your car.

Have Facebook display the IP location of the so called Facebook members and you will see more than half of them are mapping to locations in West Africa. I mean the girl says she is a beautiful blond from Charleston USA, but if you start talking with her you see that she wants you to wire money to Gahna for her to come and visit you
because her sick dad who is Ambassador Johnson is in Gahna. And Billions of other similar scams.

So join Facebook, if you want to be scammed to death.

[Rossjb]

Can-Facebook-feed-its-ad-brains? - Yes.

"For now, Microsoft will be serving Facebook's graphical ads, but it remains to be seen how the social network will tackle the ad issue on its own."

Looksmart's AdCenter + "Bid4Keywords" ='s Facebook...

"Looksmart's AdCenter allows publishers and advertisers to fully control their campaigns in all facets including their daily spend & the ability to fully target Looksmart's rich (& concentrated) content that does provide a wide range of topic appeal, particularly on a contextual basis."

And Network Solution's "Bid4Keywords" will suit Facebook, accordingly. That they have been found using Ads (a friend was served a "contextual") coming direct from an NAI member, would indicate this to us .... And they will probably be using Looksmart's AdCenter they have Licensed from Looksmart.

This will be "huge" news on Tuesday, if it is to be so. And it does appear to be. And the massive scale involved within the NAI (alone) should prove irresistible for them. There are at least a "half dozen" Networks forming, having compatibility with Looksmart's AdCenter. Learn of the NAI from within these posts here:

http://www1.investorvillage.com/beta/smbd.asp?pt=m&SearchBy=MessageText&SearchFor=Tacoda&clear=1&mb=3240&Search=Go

Last Thursday came the rumour of an AOL buy-out of Quigo for $300M. [And almost confirmed, just a few hours ago]

With AOL already heavily "involved" with the NAI (Network Advertising Initiative), it has "advertising.com" and "Tacoda" any such purchase would thereby introduce the Quigo customer base (those that are not there already via FAST's AdMomentum), and would include ABCNews.com, CNNMoney.com, Forbes.com, and USAToday.com.

http://www.quigo.com/

As said earlier .......Facebook will be "huge" for Looksmart as an Adcenter partner! And "huge" for all advertisers involved. IMHO.

:)

Rossjb

[ceoballmer]

With a little help from their friends!

They can do anything!
http://****************.blogspot.com
Why do ya think I "gave" them 256 million?