The integration of targeting data from online users and network/cable TV viewers has taken another step closer, with the announcement by video ad platform Videology that it is stepping up its use of data from audience measurement firm Nielsen.
Videology previously had been able to match its database of anonymized online users with Nielsen’s TV and online users, Videology VP of Data and Analytics Aleck Schleider told me.
But that was utilized only for the targeting of online ads, he said. Now, the same matching is being expanded to inform TV ad buying. Videology buys TV time for ad serving by others, as well as buying and serving online ads.
Although the arrangement is not exclusive, Schleider said that Videology is “the only video and tech platform that has a true one-to-one integration” with Nielsen’s panels to cover the same user across broadcast/cable TV and online.
This means, according to the New York City-based company, that it can “plan, buy and measure the same audience across TV and digital,” tying TV viewership to online and offline behavior, including offline purchases.
The result, Videology claims, is a reach for TV ad campaigns that is 18 percent greater than the same budget employed for separate online and TV campaigns, because of the additional insights into audiences and into the ads they’ve already encountered.
“Look-alike” matching
Videology issues anonymized IDs to visitors of its clients’ websites for its online ad targeting, and, like many other platforms, it assembles online profiles of their behavior on desktop and mobile devices.
Nielsen has several large panels of users. The People Meter panel signs up about 50,000 TV viewers who agree to monitoring of their broadcast/cable viewing and other behavior, like offline purchases. This becomes the large sample by which Nielsen extrapolates who’s watching specific TV shows or ads.
About 25,000 people on that People Meter panel are also tracked as online users, in a People Meter subset called the Cross-Channel panel. Plus Nielsen maintains an online-only Fusion panel of about 175,000 users.
Nielsen does “look-alike” matching of the profiles of those 25,000 TV/online users in the Cross-Channel panel with the larger Fusion panel, so as to make inferences about the Fusion panel’s TV viewing habits.
TV/online users in the Cross-Channel panel who are, for instance, 30 to 45 years old and male, and who regularly visit ESPN.com, Space.com and other specific interest sites, might also be shown as a group to watch the “Scorpion” broadcast TV series and buy luxury cars. So, online users in the Cross-Channel panel with the same age, gender and online profiles are assumed to similarly watch “Scorpion” and buy luxury cars.
Videology can see which Cross-Channel and Fusion users have both a Videology cookie ID and a Nielsen one, so it can cross-match. While Videology previously was using this data and matching for online targeting, it did not have the rights to employ it for buying TV ad time on cable and broadcast, as part of a campaign integrated with online marketing.
Now it does.
TV habits of online visitors
Schleider said this lookalike matching allows Videology to infer, for instance, that a given segment of online users might have already seen a Choice Motels ad in a particular TV show, because their TV/online user look-alikes had.
Another example: A major retailer, which allows Videology to drop a cookie ID on all of its website visitors, can now understand which TV shows a large sample of those site visitors watch, in case the retailer wants to advertise to them in those on-air or cable programs. This is because the Videology ID of the retailer’s visitors is also present on, say, 3,000 visitors spread across Nielsen’s Cross-Channel panel (whose TV viewing habits are known) and in Nielsen’s Fusion panel (whose TV habits are inferred).
“You can now push your first-party data to Videology and we can [match] on Nielsen,” Schleider said. “So, you can place and buy media across digital and TV with your first-party data.”
Videology’s new capability is part of a trend to match viewers of TV — in all its incarnations — with online users for more unified campaigns.
Recently, for instance, Tru Optik announced it was marrying its tracking of Over-The-Top TV viewing (such as Hulu) with Experian’s massive consumer marketing database.
Data Management Platform (DMP) Lotame said recently it is working with an unnamed TV set maker to merge anonymized Smart TV viewing data with online profiles. And Adobe recently announced an expanded version of its Adobe Primetime that offers a greater integration between OTT TV and the Adobe Marketing Cloud, which has been focused largely on online marketing.
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