Dramatic changes in TV viewing behaviors over the past decade have introduced an array of new data sets. Generically referred to as big data, these data sets provide the opportunity to advance audience measurement to help both buyers and sellers better understand how TV programming—and ads—are performing.
The scale of big data
At a high level, two primary sources of big data are used in linear television audience measurement:
- Return-path data (RPD) from cable and satellite set-top boxes (STBs)
- Automatic content recognition (ACR) data from smart TVs
According to Nielsen's National TV measurement as of October 2023, 70.6% of US TV homes own a smart TV, up from 62.3% two years ago. With this growth, the scale of big data is more necessary than ever to decode today's fragmented viewing landscape. Nielsen's big data set currently includes 45 million households in the US and 75 million devices, which rivals that of any other measurement provider.
However, these big data sets are not uniform or homogeneous, and they were not designed for use in audience measurement. Making sense of big data requires a truth set that corrects for gaps and fluctuations.
Ensuring measurement stability and representation
Pairing big data with a representative panel is critical to account for viewing across all devices and audiences in a stable way. Nielsen has a representative panel of 101,000 individuals from approximately 42,000 households to harness the power of big data. When used in concert with representative, persons-level panels, big data sets can significantly advance the science of audience measurement.
- Measurement is about people. Big data provides no information about the people who are doing the viewing. By pairing big data with panels, Nielsen is able to understand who is viewing, as well as household makeup.
- Measurement must be representative. Big data provides an incomplete picture of TV viewing. For example, RPD/STB and ACR data lack streaming coverage and over the air (OTA) viewing. Nielsen’s robust panel ensures all viewing is represented.
- Measurement is more than just data sources. On their own, ACR and RPD/STB providers have different ways of collecting and processing data. Nielsen data scientists ingest, harmonize, and calibrate big data.