avant|marketer: Now, real-time optimization inherently involves the testing of ad creative. Often we're talking about the testing of one set of creative against tens of others. Does this mean that the advertising creative itself will have to be developed in real-time? Poindexter Systems, in particular, has been much lauded for developing technology that enables advertisers to change the parameters of a set of creative, in real-time, by allowing the advertiser to pull a wide range of data into that set of creative from an external database. Is this sort of technology going to be required to do real time optimization effectively?

Hitendra Wadhwa: This is a very interesting issue.

If you recall, Mediaplex began doing just this sort of thing a while ago, with their so-called MOJO technology, which involved pulling data in real-time out of say an airlines tickets pricing database, or a Ticketmaster-type ticket database, into an ad to inform that ad of inventory availability, and that sort of thing. While there were certainly a few seductive stories about how this technology was used and could be applied, by-and-large, one has not seen advertisers leveraging this type of technology to very substantially improve performance. So, in my estimation, there are only a limited number of cases in which this pulling of data in real-time into an ad would benefit the performance of a campaign.

From a technological standpoint, though, there is no reason that this couldn't be supported for advertisers that want or need it...

avant|marketer: So this technology will play no significant role? In so far as the process of real-time optimization requires fresh creative to be continually inputted into the mix, it would seem that the real-time construction of ad creative ala Poindexter Systems or Mediaplex has a role to play - and can play that role inexpensively, at that.

Hitendra Wadhwa: I think what has to be looked at with regards to this type of technology is - very practically speaking - what situations there are where, in order for an advertiser to provide compelling creative that results in significant performance boosts, the advertiser needs to pull into that creative some real-time information, from some database.

If you look at it commonsensically, there are relatively few cases in which the advertiser needs to pull into the ad creative information that was not already available in some advanced form when that creative was originally developed.

Still, there could be a few scenarios in which this kind of data would be useful to the advertiser.

One situation that might be compelling is a scenario in which there is some excess product inventory that a company needs to get rid of, at the very last minute. Here they might want to be able to make sure their campaign is able to access an inventory database in real-time, and present remaining product items to prospects in an up-to-the-minute fashion.

But, generally, I think that - incrementally, for the consumer - the addition of real-time data to creative produces creative that has proved not to be anymore compelling than creative lacking this data.

avant|marketer: What then, is the relationship going to be between real-time optimization and ad creative? If real-time optimization is not going to necessitate new forms of ad creative altogether, one would at least expect that it would furnish advertisers with some insight regarding their existing ad creative?

Hitendra Wadhwa: From the advertiser's standpoint, one of the most powerful things about the Internet is its ability to allow them to generate insights as to what works and what doesn't work in a very structured, very rapid fashion. Jupiter[Media Metrix] used to call this "structured experimentation." I think that real-time optimization can actually be used to significantly increase the quality and pace of advertisers' structured experimentation.

As you're alluding to, part of what real-time optimization offers goes well beyond just allowing marketers to get a boost in campaign performance, on a campaign-by-campaign basis. It goes all the way to gathering ongoing insights over the course of multiple campaigns, about what aspects of an advertiser's campaigns are truly driving performace. And, many of these insights are important qualitative insights regarding the ad creative.

The insights regarding ad creative from real-time optimization come at a variety of levels of analysis.

At a high-level of analysis, the advertiser might discover which general elements of their creative have impacts on their campaigns' performance. It might be determined, for instance, that the color or template style that an advertiser is using doesn't matter to the performance of their campaigns, but, by contrast, the type of message they were using within their advertising, was driving performance in a very dramatic and significant way.

At a lower level of analysis, a specific retailer, say, might determine that discount-type messages perform very poorly for them, while humorous advertising messages perform extremely well for them.

With this sort of information, an advertiser is able to home in on what kind of creative it should be focused on developing and using. The advertiser is basically able to say to itself , "people are responding very favorably to funny messages of such and such a color and style, so we should focus on developing more of these."

avant|marketer: These qualitative insights on ad creative, are these company-specific, category-specific, or what? How widely do you believe these insights can be generalized? In other words, will it soon be possible based on this data for advertisers and media planners to say, "we're advertising a financial services product, so here's how we need to design our ad creative"?

Hitendra Wadhwa: Certainly, not all of the qualitative insights we're talking about will be able to be extrapolated liberally from one context to another.

But, I do anticipate that there will be some clear trends in the data that will allow us to draw conclusions about what kinds of creative work, at least at a category-by-category level. So the scenario you're referring to with financial services will eventually be possible.

avant|marketer: If that's the case, then is the availability of this aggregated data on what works in certain categories going impact the way in which ads are targeted online? What do you foresee happening with regards to the impacts of this data on online ad targeting?

Hitendra Wadhwa: Right now in the industry we have the components of a campaign being described in terms that are not very actionable. Media planners are forced to talk about campaigns in terms of "banners A, B , and C" and "[advertising] channels A, B, and C."

What is going to happen over the next couple of years, I believe, is that with the availability of real-time optimization systems and the qualitative insights that they bring to advertisers, advertisers are going to start to be able to talk about the attributes of a campaign in a much more actionable, much more intuitive way.

Instead of talking about banners A, B, and C, what's going to happen is that - using real-time optimization technologies [as a go between] - advertisers and media planners are going to start to be able speak to banner ad servers, commerce servers, email servers, etc. in the language of the actual, common sense attributes of the products being advertised, and the common sense attributes of the creative that is going to be the advertising vehicle for those products.

The trouble is that, right now, data is not even being stored by these systems - these various servers - in a way that would allow this to be possible. The first step in getting us there is getting the data stored in these actionable terms, and this is one of the things that Paramark is seeking to enable.

Ultimately - after this is done - media buyers will be able to slice and dice data in terms of red-colored banners, blue-colored banners, orange-colored banners, rather than in terms of banners A, B, and C, and so on.