Exponential-owned performance display provider unveils Audience Efficient Real-time Optimization (AERO). New technology applies transparent behavioral audience modeling directly to ad decisioning for the first time; increases campaign performance by an average of 24 percent.

Tribal Fusion, the Exponential-owned performance display advertising provider, today announced the debut of an innovative new campaign optimization algorithm to transform the performance of online campaigns.

For the first time, Audience-Efficient Real-time Optimization (AERO) applies transparent behavioral audience models directly to campaign optimization in real time, all the time. The technology incorporates the behavioral lift, or ‘audience efficiency’, of every user impression to determine which impression is best suited for each campaign. Tests using the new technology indicated that AERO can increase campaign performance by an average of 24 percent.

The new technology uses the proprietary interest-based audience dataset and transparent audience modeling technology housed in Exponential’s e-X Advertising Intelligence Platform. E-X identifies the unique performance lift of 50,000 different user interests and intentions against any campaign. AERO applies that information in real time to expose campaigns to the users most likely to convert, improve the relevance of campaigns for users, and minimize media waste for advertisers.

Doug Conely, chief strategy officer at Exponential, said: “We are using our strongest assets –best-in-class audience modeling and proprietary behavioral data – to meet the advertiser’s most crucial demands: campaign optimization and superior performance.”

“Having complete transparency about how our audience profiling and modeling works has given advertisers a level of trust they cannot find in ‘black-box’ technologies for behavioral advertising. We’re now bringing the effectiveness and transparency of our platform directly to bear on the way we optimize campaigns in real time.

Conely added that the new technology also helps eliminate wasted online display media spend by enabling campaigns to be optimized from the very start.

“Most traditional optimization processes rely solely on machine learning to improve display campaigns as they progress. Large amounts of data are needed over time to recognize statistically significant patterns and make better decisions. As a result of that learning phase, campaigns are exposed unnecessarily to users, creating discomfort and annoyance among consumers and budgetary waste for advertisers,” he said.

“However, AERO enables each campaign to own a specific, transparent interest-based audience model from the outset —before the learning phase begins. This eliminates potential waste and enables immediate optimized performance by optimizing the degree to which campaigns are exposed to users that are likely to convert.”

He added: “Online display advertising continues to represent a huge, growing opportunity for brands and advertisers. With AERO, we can help deliver on the promise of optimized, efficient display campaigns that not only impact conversions, but also awareness and consideration.”