Audience measurement has traditionally relied on small, representative panels such as those maintained by Nielsen, Kantar Media, AGF Videoforschung and BARB. While these have offered consistent benchmarks for decades, the explosion of viewing options across digital, time-shifted, and connected platforms has outgrown the limitations of small-sample data.
The industry is shifting toward a more comprehensive approach that blends traditional panels with actual data from millions of connected devices – like Smart TVs, set-top boxes, and HbbTV platforms. The result is a more detailed view of what people are watching, when, and on which device – but not without some challenges.
Why traditional panels are losing ground
Traditional panels have been useful, offering things like solid demographic insights (age, gender, household makeup) and a long history of trust. They’ve given broadcasters a standard ‘currency’ to sell ad space and provided advertisers with a verified audience.
Panel-based measurement systems are statistically solid, but their small scale can be a problem. Many shows – especially niche or regional ones – might not get recorded at all if none of the panel households were watching. Nielsen, for instance, found that in just one quarter, over 8,000 programs showed ‘zero ratings’. Not because no one watched, but because the panel missed them.
In a media landscape that values speed, panel systems fall short, taking days to report viewership data, especially for time-shifted content. To add to that, traditional people meters often miss second-by-second behavior and may only track when a person starts or stops watching, or give average-minute data.
Traditional panels have a difficult time accurately measuring mobile and OTT streaming, capturing out-of-home viewing (such as in public transit or coffee shops), or accounting for shared account usage (such as a whole family watching under one Netflix profile). These blind spots are reflected in the data.
While panels still play a core role – especially in modeling who’s watching – they’re now being supplemented (or even competed with) by device-level data and hybrid methods that introduce more speed, scale, and precision.
It’s not the end of panels: it’s the evolution into one piece of a much broader measurement ecosystem.
How big data enhances the picture
To close the gaps in traditional measurement, audience measurement providers have started integrating “big data” from connected devices. These sources include:
- Return-path data (RPD) from set-top boxes
- Automatic content recognition (ACR) from smart TVs
- HbbTV platforms, which enable hybrid data collection from both broadcast and broadband environments
By tapping into these data streams, providers can build a more complete, granular, and real-time view of viewer behavior.
For example, Nielsen now uses data from over 30 million devices in the U.S. to supplement their panel, leading to more accurate readings—especially for smaller or time-shifted audiences.
The same trend is seen on a number of markets where the old TV audience measurement firms have started measuring both linear and FAST channel streaming consumption, as well as VOD viewing by broadcasters. This has prompted them to introduce total reporting on all viewed video on all platforms, or Total Video. It used to be that TV meant broadcast or cable. Now it’s video people view “all the time”: on TVs, phones, tablets, laptops, Live, on-demand, or time-shifted, On broadcast, YouTube, Netflix, TikTok, Disney+, etc., in-house, out-of-home, or on the move.
Traditional measurement systems couldn’t capture this full picture. Advertisers, content creators, and broadcasters need comparable, consolidated, and transparent data to understand audience behavior in this fragmented landscape.
Real life examples are Nielsen One, Kantar CrossMedia or Médiamétrie.
Real-world examples show that audience measurement is changing
In Turkey, the broadcaster ATV adopted an HbbTV-based audience measurement system. It allowed them to collect anonymized viewing data from over 2 million connected Smart TVs through interactive apps, enhanced guides, and catch-up services. This gave the channel deeper insight into how viewers consumed content, without relying solely on estimates.
Austria also offers a compelling case. In September 2024, AGTT (Austria’s TV measurement body) launched Teletest 2.0, which combines its traditional panel data with information from over 1.1 million HbbTV-connected devices. This hybrid model enhances reliability, reduces volatility in small target groups, and better represents niche channels. Time-shifted viewing data is now available as soon as the next day. It’s a strong step toward scalable and stable audience measurement that matches today’s complex viewing environment.
Persidera, Italy’s leading independent digital terrestrial network operator, has also expanded its service offerings to include advanced audience measurement solutions for broadcasters. The accurate and real-time audience measurement allows broadcasters to gain immediate insights into viewer behavior without the delays associated with traditional panel-based metrics. The data is gathered from over half a million daily active devices.
User consent on smart TVs: a critical gatekeeper
A significant element when collecting data from Smart TVs is user consent. Due to privacy concerns and regulations like GDPR and other similar frameworks, manufacturers and content providers must obtain explicit permission from users before collecting and sharing their viewing data. Consent is usually obtained through on-screen prompts during TV setup or app installations. For HbbTV platforms, a consent banner is displayed to the users as soon as they enter a channel.
Although individual opt-in rates differ based on a variety of factors, overall trends indicate that American consumers exhibit higher rates of consent for Smart TV data collection than their European peers. The distinction is primarily governed by local privacy legislation and data privacy attitudes in society. Additionally, the openness and character of the consent mechanism employed by different Smart TV makers significantly affect user opt-in rates.
Some brands have faced criticism for less transparent consent processes, burying ACR (Automatic Content Recognition) opt-ins deep in long terms and conditions so that it becomes hard for users to make an informed decision.
It’s important to mention that these rates have a direct impact on usable data volume for measurement systems. Even when millions of devices are deployed, only a subset of them actually report because of consent constraints.
Challenges in scaling real-time audience measurement
As connected device data becomes central to audience measurement, it brings significant challenges. Measuring millions of devices means collecting, processing, and storing vast volumes of second-by-second data. A single Smart TV might send tuning data every few seconds – multiply that by 10+ million devices, and you’re dealing with petabytes of data each month. This demands highly scalable cloud infrastructure, real-time data processing pipelines (such as Apache Kafka, Spark, etc.), and robust data governance.
Device and platform fragmentation makes it difficult to ensure consistent data collection across all these devices. APIs differ, firmware updates break things, and some platforms (like Apple TV or Netflix) may not allow third-party measurement at all.
For high quality data, identity resolution and deduplication is needed. One person might start watching on a Smart TV in the living room, then switch to their phone in bed. How do you know it’s the same person? And how do you avoid counting them twice?
In many cases device-level data doesn’t reveal who is watching. Panels are still worth it in such cases. On horizontal markets this may be more of an issue than on vertical platforms where you most likely have access to the subscriber data.
All technical challenges can surely be overcome, but building a robust, scalable, privacy-compliant measurement system is expensive. Smaller broadcasters or markets may not be able to afford these capabilities unless they partner with vendors or benefit from national-level solutions. In most cases it is still cheaper than building and running an audience panel with custom hardware.
The bottom line then becomes the quality and trustworthiness of audience data. How can we ensure that it’s valid, correct and reliable? This is where national panels may still hold strong value: to serve as a true currency for advertising, audience data needs to be validated.
The shift is happening, and it will benefit everyone
The shift to real-audience measurement fueled by connected devices is not just a technical change – it’s a cultural one. Advertisers and broadcasters can now gain insight into actual viewership at a level of granularity that is beyond estimates based on small panels. But to realize the full potential of this change, they must balance scale of data with ethical issues around consent and privacy.
As Smart TV and HbbTV adoption continues to grow, the marriage of panel-based and device-based measurement will likely be the industry standard, providing the best of both accuracy and reach.
