Wrapping up the Media Plan

When last we left our media-planner protagonist, she was overseeing the process of trafficking out ads to the various sites that made the buy. She and her supervisor, along with members of the traffic department and a couple of creatives who happened to walk by at the wrong time, were caught up in a six-hour battle to match the right creative sizes with the right sites and make sure the creative actually made it online.

Over the next three days, more and more of the sites began to show the “flights,” or scheduled runs. The sites that didn’t manage to get the creative up by this point received pointed emails.

Now, in the aftermath of the trafficking process, our media planner slips into work early. It’s 7 a.m., and it’s the first time all her flights have been up for a complete week. In other words, she can begin to look at the data and see what’s happening.

Trying to spot data trends any sooner than this would have been mere speculation (not that she didn’t peek pretty frequently). She now has enough data to avoid misinterpreting trends. The particular day, or time of day, and any number of other errant factors could have skewed the results.

The client has called every morning since the first ad went out, but our planner has refused to divulge any information. If she had stated a click-through rate or a cost per transaction, the client would have accepted this as global gospel and demanded immediate reaction. She’s played that game too many times before to fall into that trap.

Her first task is to assemble all the data. This involves a number of processes. Her agency employs a third-party ad server, which is essentially a web server with the sole job of serving just the banners or other ads. This allows a consistent count across sites.

Or at least it would if all the sites allowed for all the ad servers, which, of course, they don’t. Sites owned by the Excite/MatchLogic network are more likely to allow the use of MatchLogic’s ad server, and sites from DoubleClick’s network are more likely to allow use of DoubleClick’s Dart ad server.

Because of all this, she sometimes has to log on to a special site where one or more publications have special password-protected areas where she can view her client’s results.

If she were working on a huge account with an enormous budget, she wouldn’t have to worry so much, but since her client spends only about $100,000 per month, some of the larger sites and networks get a bit uppity regarding their acceptance policies. The worst part of it is that even when a site allows her to use her own ad server, the site won’t respect her numbers.

When her ad server reports an underdelivery, the site won’t recognize the need to grant a makegood unless its own ad server also reports the same. So she winds up with two sets of data — one that is more accurate and consistent on the agency side and one that is used to resolve discrepancies on the site side.

This morning, though, she doesn’t care about discrepancies; she’s seeking the truth. She creates a spreadsheet by taking the numbers she has from her ad server and adding to them (not really a statistically clean policy) the numbers she gets from the sites where they didn’t allow her to use her own server.

And then she plays. This is the best part of the job. She’s developed hypotheses, she’s negotiated, she’s done all the work. Now the experiment pays off or fails. She may have used 10 different theories to choose these particular sites. She needs to determine which of these theories paid off, which didn’t, and what this implies regarding her future media buying.

She cuts the numbers on the spreadsheet over and over again, looking for intelligence in the mountain of information. Gathering some information is simple, such as which creative works better than another at a given time, in a particular circumstance, etc. Gathering other information is more complex, such as targeting people of a specific background by combining keywords along with targeted content adjacencies and specially designed creative to exploit the adjacencies.

From morning to midafternoon (skipping lunch), she pinpoints evidence of the success and failure of the theories. This will serve as a rough outline for part of the postbuy document that will be prepared after the entire campaign has run.

She comes up with seven theories for the next campaign. This is what excites her. She knows her next campaign for this client will be a better one. Her hard work is the very foundation from which the agency-client relationship will develop. And she feels pride in this — and rightly so.