Mike On Ads

Not too long ago I wrote a post One buyer, many cookies, now what?. In that post I promised that I would write about how buyers can best operate in the coming market with multiple platforms — and hence multiple cookies & adservers.

A quick refresher

In prior posts I have stressed the following:

1. An exchange or ad platform, fundamentally an adserver
2. Adserving is still tied to one cookie.
3. Behavioral targeting is tied to knowledge about a user
4. Knowledge about a user is stored in the cookie (whether as a unique user id or the actual data)

If that didn’t make sense — go read some of my older posts first.

Behavior is the future!

A single exchange with a single cookie space would have enabled true global internet wide behavioral targeting. Lets imagine I wanted to remarket to mikeonads.com users. All I would have had to do in a single platform market is add my visitors to one behavioral segment on one exchange and then place buys on that segment. Sadly this is not likely to happen since the three major internet giants swooped in and acquired practically every adserving/exchange/marketplace up for grabs. So what would I do in a world with three platforms? Lets talk about some options.

Option #1: A global user-id

Imagine this — an independent entity that offers a global user-id database. Every marketplace, ad-network or exchange subscribes to this UID service and syncs their user-ids with the global user-id. So even though Google might think that you are user #12345 and Yahoo might think you are user 54321, I can use global UID database to map your mikeonads UserID of #164 to Yahoo’s 54321 and Google’s 12345. I then simply signal to Yahoo that user 54321 is a mikeonads.com user and similarly to Google. Now each exchange knows who my users are and theoretically I can then target campaigns to my users.

Chances of this happening? Pretty close to nill. First off you’d need an independent company to provide the global UID space because none of the giants would want to give up control to another on this front. Then this conglomerate would have to get past scrutiny from the FTC, FCC, FBI, CIA and who knows who else before being able to launch, and then finally somehow convince end users, who would have probably gotten wind of this from all the press coverage, that this wouldn’t be an invasion of privacy.

Option #2: Massive user-segment mapping

In theory this solution isn’t too different from the above except that it requires browser-side communication of segments. Instead of having a global user database which allows companies to merge and map their data you simply signal each individual piece of information to each platform. If I were Revenue Science, Exelate or Tacoda I could sign up with Google, Yahoo & any other source of supply and set up my user category mapping in each system. Then, when I decide whether to add a user to a segment I fire off pixels (or whatever method to add a user to a segment) for each system.

Lets go back to remarketing to mikeonads.com users. Some people might find this a little confusing, so I made a little diagram:

Lets walk through the steps (btw, this is hypothetical, I’m not actually tracking you like this!)

1. You come to mikeonads.com
2. The html for the site contains three img tags that point to various platforms
3. Your browser loads the Google pixel
4. Google updates it’s user database and adds info to your cookie
5. Your browser loads the Yahoo pixel
6. Yahoo updates it’s user database and adds info to your cookie
7. etc.

Why does this have to work this way? Cookies! Each company has a different UID and each UID is stored in a cookie. For Yahoo or Google to store data on this user they must know who the user is, for which they need access to the cookie, which means the user’s browser has to request content from their servers.

The above is actually a perfectly feasible model and practiced a fair amount today. The problem is that it’s difficult to scale — sure if all I want to do is tell each platform that you visit my site it’s pretty easy. But what if I have thousands of different user segments and then have weights and scores on each?

Option #3:Tagging users based on value

Instead of building a mapping of a thousand different categories across five different platforms there is another solution — flagging users based on value. Lets say I rank my behavioral segments into ten different buckets, from very low to very high value — for example, users interested in credit-cards are far more valuable than users interested in harry potter. After having assigned a value priority I can then create ten different segments in each supply platform that I want to work with. Each time I have access to a user’s browser I fire off one of the ten segments to each of the supply platforms to signal the value I place on this user, much like option #2 above. Note that I still place the exact category in my own user database.

Once I have flagged users based on value I can then place a media-buy with each platform at different price points based on the ten user segments. For example, I can have one $5.00 CPM campaign for all the high value users, credit-card and auto buyers, and a $0.50 campaign for the less interesting behaviors — low-income family, under 18, etc.. Each time I win a campaign I have the platform redirect the user to my adserver where I pick my own ad to serve based on the exact categories that the user in. The major draw-back of this approach is that it forces third party adservers. To some extent this is inevitable but this is non-ideal from a creative review, discrepancy and user experience perspectives.

Final Thoughts

Even though the industry won’t be standardizing behind one platform there are several methods of enabling cross-marketplace behaviors. Obviously there are some privacy concerns that will have to be ironed out, but those are independent of the platform being used. Also, if you own a site and are interested in remarketing to your users in ways I describe above you should check out Advertising.com’s LeadBack service which allows you to do just that!

Microsoft has bought adECN. Still sitting in your chair? Yup, the ‘exchange’, which in reality is just the network ExperClick, was acquired by Microsoft today. I’m really at a loss as to what to say. AdECN isn’t really an exchange, more a loose consortium of ad-networks, and loose in the sense that they’re primarily based around one single ad-network. Why buy a crappy exchange instead of building on top of DrivePM, one of the top ad networks in the US?

I’d like to continue my series. If you haven’t already, be sure to read Part I and Part II first.

After my first two points I received multiple questions around the lines of “Who will make money off of this?”, and “Who benefits most?”, “How will ad-networks survive in this environment?”. Well, I thought we’d take a look at the various types of players in the market today and discuss how they will thrive/survive/die in the exchange environment. When discussing each of these I imagine a world in which there are two or three major ad-exchanges. Say, Googleclick, Righthoo & Micro7 … Any business that wants to play has to in involved with one or more of the exchanges as in this new world, 95% of all inventory gets sold on the exchange.

Read the rest of this entry »

If you haven’t already, be sure to read The Ad-Exchange Model (Part I) first as this is a continuation of that post.

Technology Integration

I’m sure you’ve got a picture in your head by now that there’s an annoying manual process here. Well, the technology piece gets worse. Today, most technologies that companies will consider “competitive advantages” are either optimization/prediction algorithms, contextual engines or behavioral datasets. Say we have this company called Google that has a great technology that matches ads to page content. The payout on each click depends greatly on what the ad is for. Pages relevant to autos or medication will net far higher payments than pages about the local pizza joint. So how is the publisher to decide when to show ‘Adsense’ over the $1.00 CPM deal he just signed? There’s absolutely no way for the Publisher to know the effective CPM of the adsense ad before he shows it.

Currently there are two ways that publishers manage this problem. The first is to simply accept an inefficiency in pricing. He may prioritize Google Adsense at $0.95 CPM across all pages because on average that’s what he can expect to receive at the end of the month. The other option would be to setup tens or hundreds of different tags targeted to different types of pages and then setup different prices for each. Again, this would require setting up tens or hundreds of categories in Adsense and then trafficking tens or hundreds of different tags into the Publisher’s adserver. Not really the best solution.

What about a behavioral advertiser that wants to buy New York Times traffic because he thinks he has data on some of the users. Since the behavioral data is stored in his cookie (see my post here about behavioral advertisers) there is no way for the Publisher to know which of his users will be valuable to the advertiser! How is he supposed to price this? This one isn’t so easy. One way is for the advertiser to simply buy a flat rate for all New York Times users and then simply count the users for which he doesn’t have data as a loss. The other would be some sort of rudimentary integration where the advertiser drops a pixel for the Publisher’s cookie domain for his users. Again, not ideal, not simple and INEFFICIENT!

High Latency/Slow Adserving

Each call to a different adserver costs time. The more hops that a user’s browser has to go to to receive the actual ad, the more likely that he is to click-off to another page before he actually sees it. Try it, go to myspace.com and click through on a few links. How often did the actual ad finish loading? The higher the number of systems involved in an ad call, the higher the difference between how many impression the Advertiser and Publisher’s systems count. Last I heard, 5-10% of impressions are lost for each additional adserver that is added to an ad-chain.

The Exchange Model

Fundamentally I believe people don’t quite understand why Ad-Exchanges are key is because they don’t realize that an ad-exchange is simply a glorified adserver. Really… nothing special, just one centralized system instead of three or more. Take a look a the following diagram:

Notice a difference? In this case, there’s only ONE request to ONE system, the ad-exchange. The exchange is the ecosystem through which advertisers, publishers and networks all manage their businesses. Some may integrate their contextual technologies, some may simply use the system to set prices. But it’s ONE ADSERVER! Lets revisit the three main challenges we listed before.

Pricing/Operational Inefficiency — On the Exchange

Now that the advertiser and the publisher are both on the same system the whole world changes. There is no longer a need to transfer “tags” back and forth, as all the data is in the same system. Pricing is also no longer an issue as the advertiser has integrated his technology solution with the exchange and can now bid a different price on each ad impression depending on the page the user is visiting.

Technology Integration

Although there is still a significant amount of work to be done to integrate an Advertiser’s technology solution with the exchange, it’s worth it since it’s work that only needs to be done once. Once done, this technology will work across any and all publishers. Imagine this, the New York Times starts using Googleclick as their adserver, which is, of course, fully integrated with adsense. The NYT no longer has to worry about inefficient pricing for Adsense as the technology will be integrated with exchange. On every ad-call, Adsense can check the page content and place and appropriate bid according to the types of ads that it would place. Genius right?

Now what about the Behavioral network? Of course it will integrate it’s data with the exchange, and again, on every ad call it can enter bids on the users that it has data on and even price differently based on the types of data. Of course it will be slightly more difficult to integrate technology with the exchange adserver as by nature it’s more complex than a basic adserver, but this doesn’t really matter. Since the Advertiser only has to integrate his technology once, with one adserver it’s worth the effort.

High Latency/Slow Adserving

This one should be pretty obvious. Since there is only one request, ads serve faster and fewer impressions are lost.

Final Thoughts

I realize this post is long, but I think it’s important that people realize the true value that Exchanges bring to the market. It’ll be fascinating to see how the market changes as Google and Yahoo each attempt to take control of the billions of dollars of advertising that flow through the internet every day. This new model will truly change the online advertising world for the better, except perhaps for those ad-networks out that there purely benefit from the pricing and operational inefficiencies that exist in todays world.

Stay tuned for more thoughts on the potential acquisition of 24/7 by Microsoft, securing an exchange, ‘broker networks’!

Clearly the recent acquisitions of both Doubleclick and Right Media by Google and Yahoo respectively signal a strong vote of confidence in the ad-exchange model. Reading all the news coverage of these two acquisitions made me realize that very few people out there realize the true value proposition of a centralized exchange. Sure, “transparent marketplaces”, and “auction models” are great, but why is this better than any of the existing ad-networks — Google Adsense, Advertising.com, YPN, etc.?

The Basics — A simple publisher serving ads

First lets start with a really basic question — What is an adserver? Before we can talk about an exchange, you have to understand how adserving works today. In it’s most basic form an adserver serves ads on web pages, tracks clicks on those ads and then provides reporting on the ads served and the number of clicks received on those ads. In the online space today, the vast majority of publishers, networks and advertisers all have their own adservers.

Ok, so how does it really work? Well, the first thing you need to understand is how the ad-request actually happens. To request an ad from an adserver the publisher, or website, must place an ad-tag on their page. An ad-tag is simply a snippet of HTML, generally either some Javascript or an IFRAME that tells the browser to request some content from the adserver. Here’s an example tag:

<IFRAME FRAMEBORDER=0 MARGINWIDTH=0 MARGINHEIGHT=0 SCROLLING=NO WIDTH=468 HEIGHT=60 SRC=\"http://ad.yieldmanager.com/imp?Z=468x60&s=2948&t=3\"></IFRAME>


This little snipper of HTML, when placed on a web page, informs the browser to open a small window (460×60 pixels), and in that window place whatever content is returned from “http://ad.yieldmanager.com/imp?Z=468×60&s=2948&”. When I loaded this in a browser I got the following response (truncated for clarity):

<a target="_blank" href="http://ad.yieldmanager.com/click,AAAAAIQL[...]AOUINkYAAAAA,,,"><img border="0" alt=""height="60" width="468" src="http://content.yieldmanager.edgesuite.net/atoms/8c/21/8c21402b07a3ca60e6af42e48b09a3cc.gif"></a>

Which essentially tells the browser to load an image from content.yieldmanager.com (the ad), and then when the user clicks to send him to ad.yieldmanager.com/click. Here’s a basic little diagram that outlines this simple process:

Ok, so you understand the most basic implementation of a web-page with an adserver. Now lets look at reality.

Life gets complicated — the advertiser has his own adserver

In the example above, when an ad was requested the adserver immediately responded with an image. This implies that when it comes time to pay for the ads served that the advertiser is going to rely on the Publisher’s reporting system to determine how much money he owes. In reality the advertiser is interested in tracking information as well. What this means is that both the advertiser AND the publisher need to have their own adservers. Now, the publisher’s adserver can’t immediately return an ad, instead it returns a SECOND ad tag that points to the advertiser’s adserver. Here’s another pretty diagram:

Now imagine that there’s an ad-network representing the advertiser that’s sitting in the middle, in which case what we get is:

What’s wrong with this picture?

So by looking at the diagrams above I hope you get a sense that this isn’t the most efficient of ways to buy and sell media. Think about it, for each individual ad we have to request content from three different systems! This means three times too much work is being done. So lets dig a little deeper. Essentially, the traditional adserving model has three key problems:

1. Pricing/Operational Inefficiency
2. Technology Integration
3. High latency / Slow Adserving

Lets dig into these three.

Pricing/Operational Inefficiency

One of the things I forgot to mention above is that each point of integration between two adservers is manual work. If the Advertiser wants to buy 10 million impressions at $1.00 CPM from a Publisher the following process generally happens:

1. Publisher sales rep contacts advertiser
2. Publisher and advertiser negotiate contract terms (e.g. 10M @ $1.00)
3. Publisher and advertiser sign a contract
4. Advertiser sets up the ads in his adserver and sends over the “ad-tags” for the media buy
5. Publisher has trouble trafficking ad-tags into his system and contacts his support department
6. 5 days later, Publisher finally manages to get the ad-tags live and the campaign starts

So what’s wrong here? First off, there’s a certain inefficiency here. When the advertiser decides he wants 10 million impressions he probably specifies a certain set of targeting parameters to ensure that the Publisher sends him users that will be likely to be interested in his offer. For example, he may want over 18 males with a maximum of 4 ads shown to each user every day. Clearly there is a problem here. Depending on the offer, 18-25 males might be far more valuable than 50-85 year old males. Also, the first ad the user sees is far more likely to elicit a response than the second or third. So what do people do? Well, instead of setting one fixed price for all over 18 users he could setup 20 difference prices. Ten different age buckets (e.g. 18-25, 25-30, 30-35, 35-40) and two different frequency buckets (e.g. first ad, second through third ads). Well, this makes life a little bit better but there are still some problems here. First off, the higher the number of pricing points, the longer the entire process outlined above takes. 20 price points means 20 different tags in the Advertiser’s adserver, and 20 tags to upload into the Publisher’s adserver, and 20 different tags for which the Publisher may need to contact his support department for help. Here’s a nice little diagram –

In this new digital age of APIs and digital systems, why the hell does this take so much work? Can’t we do this in a better way? Well, at some point people realized that pricing flat CPM rates for inventory wasn’t the most efficient way to do things and came up with Cost Per Click (CPC) and Cost Per Acquisition (CPA) pricing models. In these systems the advertiser simply specifies how much he’s willing to pay per Click or Acquisition (generally a purchase, or lead form) and lets the publisher’s system determine the best users to deliver ads. Although this system is better than the above it introduces another set of problems. The advertiser now becomes wholly dependent on the Publisher’s optimization/prediction algorithms, which may or may not be any good! I can continue here for ages, but I’m pretty sure you are getting a sense of how inefficient the current system is.

Enough for one post. Stay tuned tomorrow for Part II — Tech issues and how the exchange model helps.

Update: Part II is ready, read on here: The Ad-Exchange Model (Part II)