Aggregate Knowledge Lets Advertisers See 'What If?'

Aggregate Knowledge has added new features to its Media Intelligence Platform (MIP) that lets marketers see what the results of media spending adjustments would be before they pull the trigger.

The newest generation of the platform also comes with a money-back guarantee for new customers.

Aggregate Knowledge’s MIP, is a data management application targeted toward Fortune 500 customers that combines audience and media data into one platform, tracking cross-channel performance and customer touch points, including email, search, Facebook, display, video and ad exchanges.

The enhanced platform “could help inform other products that we’re using. Depending on how we want to activate against it, it could work in conjunction with other products like a trading desk or other solutions we’re using,” said Julian Zilberbrand SVP, global digital director, strategic partnership and technology solutions for Starcom MediaVest Group. Several SMV clients are Aggregate Knowledge customers.

This latest version of MIP delivers improved “what-if” tools that include cost data, so that marketers can adjust their media spends on the fly, based on the budget impact, rather than simply on impressions.

“The interface is evolving to not only contain the information you need to make decisions but also to bring more of it to the forefront,” said Rob Gatto, president.

Aggregate Knowledge has found that, on average, between 20 and 30 percent of any media buy is wasted, due to things like duplication of audience members, advertising to the same person on multiple channels or saturating an audience member.

“As a neutral, agnostic party that sits between media that an advertisers runs and the audience, we help them take a look at the media they’re pushing out into the marketplace and how that’s performing in the context of the audience,” said Gatto. The new tool “helps an advertiser find waste in the media buy, extract the waste and redeploy it.”

The what-if tools model prospective inventory mixes, so that an advertiser could, for example, drop the bottom 10 percent of underperforming media or audience segment and reallocate it into the top 10 percent.

“You can overlay potential decisions and see how they affect your cost or interaction; there are a number of different metrics you can use. For example, an advertiser could see how many additional people the change would reach or how much it could lower the cost per action,” Gatto said. “It tells you not only recommendations on where to move but also, if you made those moves, what would happen to your key metrics.”

The newest release also provides new publisher views, so that marketers can understand which media performed best over time. The company says this can reduce overlap and increase efficiency of the media spend.

For example, Aggregate Knowledge has found that media plans that include Facebook drive 24 percent more new sales than those without it. It’s also found that most marketers should reinvest 26 percent of their ad spend to reach 40 percent more customers. From data aggregated across the client base.

This kind of tool doesn’t fit the needs of every client, Zilberbrand said, but, “For heavily data-focused clients that are looking at multiple sets of data, tools of this nature help centralize a lot of the information and provide analytics, so they are very useful from that standpoint.”

The company processes more than 3 billion ad events per day, and it integrates with Google, AOL, MSN, Facebook and 25,000 other publishers.

Aggregate Knowledge is going after new clients in the Internet 100 with a no-risk guarantee. “We will guarantee a 10 percent increase in either reach or a sales metric,” said Leslie Petry, director, product marketing. The company will baseline sample campaigns and provide recommendations the customer can implement for 60 days. If it doesn’t gain 10 percent, they will get their money back.

Aggregate Knowledge provides the Media Intelligence Platform as SAAS, with pricing based on the volume of media run. Most clients go into proof of concept mode for 60, 90 or 120 days, paying a fixed amount for the test before moving to volume-based pricing. Testing typically costs between $30,000 and $50,000 per month, Gatto said, with ongoing clients spending from $16,000 up to $300,000 per month.