For the last 75 years, the national television audience measurement currency has been based on an area probability sample panel using metering technology and delivered by the Nielsen company, which is one of my consulting clients.
This year, with MRC Accreditation and a vote by Nielsen clients, the shift was made to a far more complex methodology integrating panel data with big data (BD) collected through set-top boxes, smart TVs, and direct integrations with media partners’ server data. The big data were carefully edited, where panel and big data were collected from the same device; the Nielsen meters were taken as more accurate than the BD, and new methods were developed and refined to adjust for missing data in the smart TV BD, mostly due to channels and programs that were not tracked. All of these data were statistically combined to provide the weights that science required.
Science also provides a Z Test as a means of determining how much to expect the differences to be between different samples. The Z Test in this case, based on assessing the differences versus the sampling variation inherent in the panel measurement across 174 networks, predicted that there would be more difference between the old and new Nielsen methods than actually appeared.
The preponderance of Z-scores closer to zero than a normal distribution shows that the two measurements are more closely aligned than expected, given the inherent sampling variation in the panel measurement.
Here is a more detailed look at the data:
The largest effects of the Nielsen methodology seen in the above graph come from the Nielsen streaming meter, in ~26,000 of the national panel homes. This technological invention is what powers the popular Gauge, the currency for the streaming networks, and is the industry’s only source of viewing data on streaming, the most dynamic part of television today, accounting for 47.3% of all viewing. Most streaming networks do not allow the smart TVs to measure them, and set-top boxes cannot measure them either. Other large effects of the Nielsen corrections and completions to big data include omission of large numbers of television programs by smart TVs, undercounting of time shifted viewing by smart TVs, errors in program logs used in set top box data (such as when sports events run overtime), TV sets not measured at all in homes with some smart TV sets and some other TV sets, and of course the viewing by people in the big data homes.
Posted at MediaVillage through the Thought Leadership self-publishing platform.
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