StrategyMediaIn Wake of ’09 Data Mergers, Hyper-Targeting to Take Shape in 2010

In Wake of '09 Data Mergers, Hyper-Targeting to Take Shape in 2010

Ramifications of Omnicom, Nielsen, WPP deals should come into focus this year.

The last quarter of 2009 should be partly remembered in the advertising community as a juncture when big agencies — namely Omnicom Media Group, The Nielsen Company, and WPP — announced consumer data mergers. The deals entailed the marriages of offline and online data and appeared to reveal a potentially major stepping stone in the evolution of “hyper-targeting.”

Some of the agencies have trumpeted their newfound ability to create consumer segments related to behavioral elements such as “passion points” (e.g., shown interest in electronics, photography, fantasy football, etc.), as well as geographic location, beverage preferences, favorite social media sites, activity levels at the sites, and so on.

Augustine Fou, group chief digital officer for Omnicom’s Healthcare Consultancy Group and a ClickZ columnist, said that while increased hyper-targeting would likely result from the data marriages, unresolved issues remain before the use of combined online/offline data is widely adopted by brands.

“For example, as diverse data sets begin to be integrated, it will become painfully apparent what data can be integrated — or not — and specific tradeoffs will have to be made to move forward,” he explained. “In particular, privacy policies of sites and ad networks will need to be revisited.”

The growing ability for marketers to target online ads using data gathered offline has generally raised concern among consumer privacy advocates. To that end, Fou suggested that brands are cautiously optimistic about hyper-targeting and slightly wary of public/consumer perception.

“Customers now have the voice to cry foul online if they think a company is using personal information to target them in ways that are unacceptable to them or are perceived to have ‘crossed the line,'” he said. “So, brands are waiting to see more ROI data to judge whether this is something worth rolling out widely or something to be just experimented with in pilot programs.”

Meanwhile, here’s a recap of the data merger announcements:

Oct. 22: Omnicom Gets Access to Fox Consumer Panel
Omnicom fired the first warning shot when announcing access to News Corp.’s Fox Audience Network (FAN) consumer panel, which pulls data from 700 publisher sites. FAN’s audience segmentation system allows Omnicom to group anonymous online consumers who share mutual interests like sports, movies, and music, and then target them. It has been plugged into Omnicom’s multichannel data-driven campaign management tool, Living Segments.

There was also a real-time management component to the deal. Campaign performance data is available for Omnicom’s buyers and brand clients on a back-end dashboard that’s designed to let them pinpoint what sites are producing impression spikes vs. ones that are not panning out as well. Campaign planners can use the impression data to augment other available statistics while finalizing media buys and creative.

Nov. 2: Nielsen in Pact to Use Offline Data for Online Ad Targeting
Two weeks later, Nielsen and consumer data firm DataLogix forged an agreement to allow household-level online ad targeting using Nielsen’s audience cluster PRIZM data. Several ad networks, including Audience Science and Collective Media, are offering the targeting capabilities to advertisers.

In the past, the PRIZM data, which organizes U.S. consumers into audience segments intended to define lifestyles, has been employed to target ads on a zip code level. According to Nielsen, the relationship marked the first time the PRIZM data had been used to target online ads at a household level. The system identifies users through retail transaction related cookies and other data, said Justin Evans, SVP strategy and marketing at Nielsen, who stressed users would be targeted only using non-personally identifiable information.

Nov. 10: Compete & Sister Company Merge Data
Then, Kantar, part of WPP, combined data from its marketing research firms Compete Inc. and Cannondale Associates to help brands link the effectiveness of digital campaigns to in-store consumer purchases. Compete’s online consumer research panel of two million viewers was hitched to its sister company’s ShopperGenetics data platform, which collects info from the loyalty cards of 80 million households.

Matt Pace, managing director for retail and consumer products for Boston-based Compete, said the data will help Cannondale’s mostly consumer packaged goods industry clients determine which banner ads are producing in-store sales. For instance, whenever a consumer that exists in both databases is exposed to a display ad for potato chips and then buys a product with an associated loyalty card, the purchase can be trackable back to the online campaign, Pace said.

Dec. 15: WPP to Leverage Kantar Data
Lastly, WPP Digital said the month-old data merger from its Kantar properties, Compete and Cannondale Associates, would now, in theory, help create better media planning for WPP’s Media Innovation Group (MIG) division.

Stephen DiMarco, CMO for Boston-based Compete, explained, “Since we have ‘matched’ our panel with Cannondale, we can determine what [consumer packaged goods] products our panelists have purchased. This means we can use this information as the basis of our segmentation and then build media plans based on the recency and/or frequency of purchase in a product category like diapers. And in partnership with MIG, we can execute…the campaign.”

According to DiMarco, MIG will be able to analyze the following types of consumer segments: “intent-based,” such as online searchers for hybrid cars; lifestyle-based, such as luxury goods consumers; or content-based, like fantasy sports enthusiasts. “This is done by flagging consumers in our panel who meet certain segment criteria and then scoring all of the other Web sites that they go to,” he said. “The result is an index for virtually every site on the Web based on its composition of all of the segments we track.”


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