Equilíbrio entre a necessidade de inovação e continuidade na medição de audiência

Dramatic changes in TV viewing behaviors over the past decade, driven primarily by widespread connected TV (CTV)¹ adoption and increasing high-speed internet availability, have introduced an array of new data sets that are finding their way into measurement solutions. 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. 

A escala do big data

At a high level, there are two primary sources of big data that are being used in linear television audience measurement:

• Dados de caminho de retorno (RPD) de set-top boxes (STBs) de cabo e satélite
• Dados de reconhecimento automático de conteúdo (ACR) de smart TVs

Com 70,6% das residências com TV nos EUA possuindo uma smart TV, em comparação com 62,3% há dois anos, um dos maiores benefícios do Big Data é a escala. A escala é importante no cenário fragmentado de exibição atual. Nosso conjunto de big data inclui atualmente 45 milhões de residências nos EUA e 75 milhões de dispositivos da Comcast, Dish, DirecTV, Roku e Vizio, o que rivaliza com o de qualquer outro provedor de medição.

No entanto, esses conjuntos de dados não são uniformes ou homogêneos e não foram projetados para uso na medição de audiência. Mas isso não significa que eles não possam ser usados para esse fim. De fato, eles podem ser muito úteis, mas não por si só. Para entender o big data, é necessário um conjunto de verdades que corrija as lacunas, as flutuações e outras complexidades do conjunto de big data.

Ensuring measurement stability & representation

A combinação de big data com um painel representativo é fundamental para contabilizar a visualização em todos os dispositivos e públicos de forma estável. A Nielsen possui um painel representativo de 101.000 indivíduos de aproximadamente 42.000 residências, o que nos permite aproveitar o poder do big data e, ao mesmo tempo, corrigir suas deficiências. 

And the industry agrees. The World Federation of Advertisers’ (WFA) ‘North Star’ principles for cross-media measurement call for a combination of quality panel and big data. In August 2022, both the Video Advertising Bureau (VAB) and the Association of Advertisers (ANA) announced plans to build their own panels, as did Google for use in its online conversion measurement. Put differently, the industry is clamoring for approaches that both ensure representation and harness the power of big data. We believe Nielsen is uniquely positioned to provide these solutions.

Investimos uma década de pesquisa na integração de conjuntos de big data em nossas metodologias de maneiras inovadoras que também garantem a continuidade com nossa medição de moeda. Incorporamos o big data em nossa medição de TV local nos EUA em 2019 e em nossa medição de TV nacional em 2022. Quando usados em conjunto com painéis representativos em nível de pessoas, esses conjuntos de big data podem avançar significativamente a ciência da medição de audiência.

1. Measurement is about people. Big data provides no information about the people who are doing the viewing. By pairing big data with panels, we’re able to understand who is viewing, as well as household makeup.
2. 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. As of November 2023, streaming accounted for 36.1% of television viewing in the U.S. Additionally, 18.1% of U.S. TV households have at least one TV set that accesses content using a digital antenna instead of STBs or an internet connection². Big data viewing sources also may not include all devices in the home. This is particularly an issue with ACR data where the number of devices returning data is about 1.1 per home. The average U.S. TV home has about 2.5 sets. Panels are critical to cover these gaps, and any measurement solution that solely relies on big data would miss these audiences.
3. Measurement is more than just data sources. ACR data, for example, simply identifies images on a screen. If the same piece of content is airing on multiple channels at the same time, the ACR data has no way of accurately attributing viewing to one channel versus the other. Similarly, RPD and STB data are often incapable of verifying if a TV is even on. Different RPD/STB providers and original equipment manufacturers (OEMs) also have different ways of collecting and processing data. This makes ingestion, harmonization, householding, and calibration both critical and extremely complex. 

As deficiências de medição nos dados de RPD/STB e ACR destacam por que é fundamental que esses dados sejam calibrados com painéis baseados em pessoas que representem com precisão a diversidade de uma população. 

Navegando pela evolução da medição

Combinando a escala de big data com informações em nível de pessoa de novos e inovadores medidores de painel, podemos fornecer granularidade aprimorada até o comercial individual. Isso garante que os anunciantes possam entender quem e quantas pessoas viram exatamente seu anúncio. Também podemos oferecer uma segmentação mais avançada para desbloquear a capacidade de capitalizar os recursos endereçáveis lineares, bem como os segmentos avançados de público-alvo. 

There is no shortchanging the benefits Big Data+Panel will bring, but the shifts taking place in the media industry are far too significant to make wholesale methodology changes to data being used as currency on a moment’s notice. Stable transition in times of change will always be better than a very quick pivot. Times of transition also amplify the need for transparency, especially when measurement data underpins a global industry that ad research firm WARC estimates will top $1 trillion next year. 

Recognizing that the industry needs time to adapt to innovations in measurement, we made our national Big Data+Panel data stream available for transactions in parallel with our TV panel currency for the ‘23-’24 television season. For the ‘24-’25 season, we have enhanced our Big Data+Panel stream to include Comcast data (in addition to DISH, DirecTV, Roku and Vizio), and we’re committed to helping the industry navigate through this transition. Well aware that different organizations evolve and adapt at different rates, we will also provide our audited and accredited TV Panel data (average minute), as well as Big Data+Panel (at the average minute and individual commercial minute) during the coming season.  

The evolution of Medição de TV will only happen with industry alignment. And while many agencies and advertisers are interested in moving toward measurement of exact commercials, the overall sentiment in the industry is that it’s not yet ready to retire C3/C7 ratings. We need to balance the equally valid needs for innovation and continuity. With three data sets available, buyers and sellers will be able to evolve systems to truly operationalize the planning, selling and buying of national linear TV at an exact commercial level. 

Fontes:

¹ CTV refers to any television that is connected to the internet. The most common use of the internet connection is to stream video content
² Nielsen National TV Panel, November 2023