Measuring national viewing with set-top-box and smart TV data

Measuring national viewing with set-top-box and smart TV data

Tom Weiss, Mon 10 December 2018

It used to be that we could all rely upon Nielsen or a local joint industry committee's measurement panel to tell us everything that we needed to know about TV viewing. As consumer behaviors have changed, with time-shifted viewing, streaming video, and the launch of more and more niche channels, it has become clear that panels can only show a part of the picture.

Low resolution viewing

This image of the Mona Lisa on Wikipedia is 7,601 x 11,348 pixels in size, which is about 86 million pixels in total, a number not significantly smaller than the number of homes in the US. If we create another version of this image with only around 25,000 pixels in it, then we have a view comparable to what the Nielsen panel sees. Comparing the two, we can immediately see that the granularity we get from panel data is only going to be sufficient for a very high-level overview of consumer behavior. All of the details and the emerging patterns are missing.

Comparing panel data with reality

Adding in Census set-top-box data

The conventional wisdom is that we can fix the low-resolution problem with panel data by moving to census data from set-top-boxes, but there's a big problem with set-top-box data: it doesn't show the entire market. As well as significant geographic gaps, it's missing any viewing of streaming video and over-the-air broadcast services. Both are growing areas, and without these two elements, you only have a very skewed picture of the emerging new consumer behaviors.

Comparing STB data with reality

Smart TV data

Smart TV data fixes the problems with set-top-box data in that glass level automatic content recognition includes both broadcast viewing and streaming video through external devices like Roku. There are however still gaps in smart TV data, but these are typically smaller. Older and poorer people, in particular, are much less likely to have connected smart TVs. These groups are therefore under-represented in Smart TV data. Smart TV datasets - like Nielsen - also don't measure long-tail time-shifting DVR behavior beyond the initial broadcast window.

Comparing Smart TV data with reality

Fusing the datasets

The trick to getting a complete picture is to fuse in all of the different data sets you have available: panel data, set-top-box data, smart TV data, and first party OTT streaming data. You can use set-top-box data to provide full coverage of cable viewing in areas where you have the data. Adding smart TV data on top of that gives you coverage of non-cable viewing and also geographic areas where set-top-box data isn't available. Finally, you can layer in panel data to provide the picture for the older and more deprived parts of the population and also layer in individual viewing behaviors that are not apparent in the household level data from set-top-boxes and smart TV.

Comparing fusion TV data with reality

With these in place, you get the most accurate picture of reality you can reasonably expect to achieve in 2019.

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