WFA/ANA Northstar Fulfilled by Nielsen ONE

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In February 2019 the World Federation of Advertisers (WFA) and the Association of National Advertisers (ANA) announced their global plan to ensure the kind of cross-platform audience measurement they need. Their main concern was the ability to measure the amount of frequency their ads get within each segment of the audience. They were prescriptive that both big data and panel data were to be used together to provide maximum accuracy, precision, stability and persons level viewing data -- not just household/device level data. They were open-ended in allowing that Virtual IDs ("VIDs") could be used if necessary.

Pilot tests are underway in the U.S. and U.K. and now, in the U.S., Nielsen has delivered the first full-fledged product to meet and even exceed the standards set by the WFA/ANA plan. Where Nielsen ONE exceeds the basic requirements is by basing audience estimates on actual IDs rather than on VIDs. This is accomplished by use of advertiser ad tags and tracking pixels, watermarks, fingerprinting, meters, set top box and smart TV data, and integrations with major publishers.

This provides far superior accuracy to the use of VIDs which entails probability-based estimation – essentially old wine in new bottles – the old wine being reach/frequency estimation methods known to early settlers by names like Agostini and Sainsbury. Use of VIDs is highly similar to the Sainsbury method introduced nearly a hundred years ago, where for example a ten rating is assumed to mean that the ad reached ten percent of each subsegment of the total population. This is empirically known to be counterfactual; nevertheless, the method is a good option where no better option exists.

The better option is actual measurement of the differential reach of an ad by each individual in the measured population. This is what Nielsen ONE has done.

This is how it is possible for Nielsen ONE to report the frequency in each tiny chunk of the Venn diagram showing how TV, CTV, computers and mobile devices carrying the ad work together.

This was the main question the advertisers wanted to solve, and so Nielsen made that solution its top priority. A detailed roadmap exists by which Nielsen ONE (Ads) as the first product is named will evolve and provide all the data clients want in feasible stages.

The clients also want certain of the old-style data to be retained, such as C3 and C7, despite Nielsen ONE’s ability to report audiences for specific ads. And their desire is for good reason: all the network and agency systems are based on C3 and C7, and changing all that overnight or even over a period of years is a lot of work. In particular, buyers and sellers make forecasts based on C3 and C7, and the amount of work involved to predict specific ads is still being studied. Right now, Nielsen is set to retire C3 and C7 reporting at the end of calendar 2024, but Nielsen executives expect to follow the lead of clients in the actual retirement date for those measures, or to extend them in perpetuity.

We wanted to be able to demonstrate some of the actual learnings coming out of Nielsen ONE and so we asked Nielsen if they would be able to supply some sample data focused on the question, "If we have ten million dollars to invest in a U.S. cross-platform brand campaign flight, which allocation combination of the four screens will give us the most reach against our target?"

Nielsen is now approaching each of its Alpha Nielsen ONE clients who have been testing the Alpha version of the system for many months and asked if they themselves had gathered such data or anything similar to it in their testing of Nielsen ONE (Ads) Alpha. Or if they had any interest in doing such runs now for this series of leadership articles to illuminate the industry as to how to most effectively use cross-platform measurement now that it is here.

We are just now beginning to receive Nielsen ONE data and will be publishing analyses here in the weeks to come. The numbers I’ve seen so far shed light on how important linear television is to the achievement of cross-platform reach against any target, and they report not only on the optimal amounts of the other platforms for maximum incrementation of target reach, but also on the beneficial frequency distribution flattening effect of having the optimal allocation.

The advertiser’s concern over excessive frequency is where the WFA/ANA project came from. The user experience with advertising is what is at question. So the learnings of Nielsen ONE have broad implications for consumer experience and how much investment ought to go into each of the four media types. In our upcoming series of posts we shall do our best to accelerate the industry’s learning and benefits received.

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