Mike On Ads

I really wanted to write a post about the difficulties in monetizing small websites but I realized to best have that discussion I would have to explain behavioral networks first! So, here goes.

A few months ago I was trying to explain to my girlfriend how advertising works. After a couple discussions she said a rather interesting thing — “How come the travel industry seems to be the biggest advertiser out there? All I see are travel ads, no matter where I go!”. Well, turns out my girlfriend is a travel fanatic and it’s behavioral networks that have picked up on the fact and no matter what the content of the site she’s visiting they manage to find a relevant travel related ad to show her. Try it, go to travel.nytimes.com and click through to a couple articles. Then go to a random section of the site, say ‘health’, and chances are you’ll see a travel ad! (see screenshot below) Sounds like voodoo or big brother right? Wrong!

And peeking into my cookies, indeed there is some travel related fun in there (hard to tell what all means, since most cookies are encrypted):

There are many different behavioral players out there in the world each with varied success. Perhaps the most successful behavioral company on the internet is this small company based out of California called Yahoo. There are also a couple ad-networks that dabble in this space, one of the most popular is Tribal Fusion. Each approaches the challenges in a different way, but the core of how it works is the same for all.

So how does it work? It’s actually an amazingly simple concept. Lets say we have four websites:

1. gizmodo.com
2. engadget.com
3. slashdot.org
4. myspace.com

I am a user, and I visit each of these websites. Each of these websites also works with a brand new (not real of course) behavioral network called “BigBrother2.0″. On every page of these sites there is a little thing known as an ad tag that points to BigBrother’s adserver and requests an ad. Just for fun, lets assume that gizmodo also know your age & gender and passes that information to BigBrother. So you visit the first page, and an adrequest goes to BigBrother as follows:

http://ad.bigbrother.com/request?site=gizmodo.com&age=25&gender=m

When your browser requests the URL above, the following sequence of events happens:

1. Browser Requests content from ad.bigbrother.com
2. Server requests cookies (if any)
3. Browser sends over cookies
4. Server does some crunching, picks and ad
5. Server returns new cookie data & url to get get ad
6. Browser shows ad

Now the magic here is in the cookies. Even though you are visiting the site gizmodo.com, the cookie is under the domain ‘ad.bigbrother.com’. In step 5 where the server returns new cookie data, they’ll put in there when you last visited gizmodo.com and how many times you’ve been there today.

Now lets say I spend the morning checking out my tech-news, all the while receiving ads from ad.bigbrother.com. Each page I view gives them a little bit more information about me, and even though I’m on three separate sites, because the cookie spans all three they get a holistic view of what I”m doing.

So now I go to Myspace.com. This is a big site. Normally it’d be difficult to pick a good ad to show you. You’re one of the 18 billion myspace users and all you really do is upload photos and post silly comments about your friends on their blogs. BUT, when Myspace decides to let BigBrother2.0 show an ad something interesting happens. Lets walk through the steps of this new ad call in more detail:

http://ad.bigbrother.com/request?site=myspace.com

1. Browser Requests content from ad.bigbrother.com
2. Server requests cookies (if any)
3. Browser sends over cookies
1. Cookie contains your age & gender (25 & male) (encrypted)
2. Cookie shows you visited gizmodo.com 12 times this morning
3. Cookie shows you visited slashdot.org 3 times this morning
4. Cookie shows you visited engadet.com once this morning
4. Server does some crunching, picks and ad
1. Server plugs user data (25, male, 16 visits to tech sites) into a ‘profile engine’
2. Profile engine spits back ‘categories’, lets say ‘male, technology’
3. Server looks for ad campaigns targeted to ‘male & technology’
4. Server picks highest paying ‘male & technology’ targeted campaign
5. Server returns new cookie data & url to get get ad
6. Browser shows ad

Instead of showing you a random ‘punch-the-monkey’ ad, BigBrother is able to show you a highly relevant and targeted advertisement that you are far more likely to click on. The end result? Better ads for you and more money for the websites that you visit.

You can see from the above that building a behavioral adserver really isn’t the most difficult thing in the world. All you need to do is track history & have some sort of ‘mapping engine’ that says that slashdot.org is a tech site. The real challenge for behavioral companies is the classic chicken & egg problem. Without a rich user-base, the ad-network won’t be able to sell deals. Without deals the network won’t be able to convince publishers to put their tags on pages. This makes it very difficult for new behavioral players to enter the marketplace, although emerging marketplaces such as the RMX will make it easier in the future.

So what’s my opinion on all this? As long as the data that is being stored is encrypted and no Personally Identifiable Information (PII) is stored I’m all for behavioral targeting. As I mentioned before, the more relevant the ad is to my interests, the more pleasant my browsing experience is going to be.

Related Posts:

• Battle over the Cookie
• How can ad-networks monetize small websites?
• The Ad-Exchange Model (Part II)
• One buyer, many cookies, now what?
• RTB Part III — Cookies & User Data