TV and streaming bundles have become increasingly popular in recent years as consumers look for more convenient and cost-effective ways to access the content they want to watch. These bundles typically include a variety of streaming services, such as Netflix, Hulu, and Disney+, as well as traditional TV channels, all bundled together into a single package. The benefit of these bundles is that they make it easier for consumers to find and access the content they want to watch, rather than having to navigate multiple apps and subscriptions. Additionally, these bundles can also offer significant cost savings for consumers, as many of them offer a lower monthly rate than subscribing to each service individually.
Panels are making a comeback, but they are not the traditional device-level data panels that were based on set-top boxes and smart TVs. Instead, these are single-source mobile panels that use Automatic Content Recognition (ACR) and cross-device data to validate census-level information. These panels can identify impressions and duplicate audiences by using deterministic ad exposure data methods. With passive mobile ACR panels, advertisers can optimally track what people watch on TV.
TV is becoming increasingly popular, as it allows users to watch what they want when they want, and on the device of their choice. This shift towards CTV has also led to an increase in programmatic advertising on these platforms. Beatgrid real-campaign data shows that CTV reaches between 30-50% of an exclusive, incremental audience that is not reached through linear TV. This means that CTV can be a powerful tool for advertisers to reach new audiences and increase the reach of their campaigns. However, brand advertisers need high-quality CTV data to effectively target and manage this new TV frontier. Without accurate data, advertisers may struggle to reach the right audience and may not get the desired results from their campaigns. Therefore, it is important for advertisers to invest in high-quality CTV data to ensure the success of their campaigns on these platforms.
Programmatic technology has been increasing in popularity for TV advertising in recent years due to its ability to target and personalize ads, track and measure campaign success in real-time, and efficiently buy ad space. This technology allows advertisers to reach their desired audience and can be particularly beneficial for small and medium-sized businesses. Programmatic technology also allows for more efficient ad buying, as it automates much of the process and allows advertisers to quickly and easily reach their desired audience. This can be particularly beneficial for small and medium-sized businesses, as it allows them to compete with larger companies for ad space.
There is also a clear opportunity for OOH (out-of-home) advertising, specifically DOOH (digital out-of-home), to support TV and CTV campaigns. Younger audiences, including millennials and Gen Z, can be reached through unique formats and locations that offer high visual impact and strong brand lift metrics. Real cross-campaign data has shown that OOH reaches around 45% of an incremental audience that is not reached through other channels such as BVOD (broadcast video on demand) and TV.
With the imminent death of cookies and as TV advertising measurement becomes more data-driven, there is a growing focus on privacy and data security. Advertisers are increasingly concerned about the potential for data breaches and other security threats and are looking for ways to protect the sensitive data that is being collected and analyzed. This is likely to lead to the development of more advanced data security measures, such as encryption and secure data storage, as well as increased regulation around the collection and use of data for ad measurement purposes. Not only is it important for advertisers to prioritize data privacy and security for the protection of their own interests, but it is also critical for the end user. Consumers are becoming more aware of their own data privacy and are increasingly concerned about how their data is being used and protected.
This is why it is essential for advertisers to be transparent about their data collection and use practices, and to clearly communicate these practices to their customers. By being transparent and upfront about their data collection and use, advertisers can build trust with their customers and demonstrate their commitment to responsible data management. Furthermore, the importance of data privacy and security extends beyond just the realm of TV advertising measurement. In an increasingly connected world, data privacy and security are critical concerns for all types of businesses and organizations. By prioritizing these issues and being transparent about their data practices, advertisers can not only build trust with their customers but also contribute to the overall protection of sensitive data in the digital landscape. Overall, it is crucial for advertisers to prioritize data privacy and security in order to protect both their own interests and the interests of their customers.
Another trend that is likely to shape the world of TV advertising measurement in 2023 is the increasing use of artificial intelligence (AI) and machine learning. These technologies are being used to automate many of the manual processes currently involved in TV ad measurement, such as data analysis and interpretation. By using AI and machine learning, advertisers can more easily and accurately measure the performance of their ads, and make more informed decisions about where to allocate their advertising budgets. In addition to using AI and machine learning to automate data analysis, many advertisers are also using these technologies to personalize the ads that they deliver to viewers. By using AI to analyze viewer behavior and preferences, advertisers can create more tailored and effective ads that are more likely to resonate with specific audiences. This can help to improve the overall performance of an ad campaign, and can also help advertisers to target their ads more effectively, ensuring that they reach the right people at the right time.
One of the biggest trends in TV advertising measurement is the move towards more advanced, cross-platform measurement solutions. In the past, TV ads were typically measured using relatively simple metrics like ratings and reach, which provided a broad picture of an ad’s performance but lacked the granularity and detail that many advertisers now demand. However, with the rise of Connected TVs and the proliferation of streaming services, it’s becoming increasingly difficult to accurately measure the performance of TV ads using traditional methods. As a result, more and more advertisers are turning to advanced cross-platform measurement solutions that can provide a more complete picture of an ad’s performance across multiple platforms and devices. These solutions typically combine data from various sources, including TV ratings data, digital analytics, and consumer survey data, to provide a comprehensive view of an ad’s performance. They can also provide insights into how different demographics are responding to an ad, as well as how an ad’s performance varies across different geographic regions.
Overall, the world of TV and cross-media advertising industry is undergoing significant changes, and 2023 is likely to see (1) the Netflixization of SVOD being over with streaming bundles becoming the norm, (2) the rise of passive mobile ACR panels, (3) CTV becoming increasingly popular, (4) the increased use of programmatic technology for TV advertising (especially CTV and addressable, (4) OOH advertising adding significant incremental value to cross-media campaigns by reaching younger audiences, (6) a grown focus on privacy and data security, (7) the increasing use of AI and machine learning, and (8) the continued growth of advanced cross-media measurement solutions.
As these trends continue to evolve, advertisers will need to stay up-to-date and adapt their measurement strategies in order to stay ahead of the curve and make the most of the opportunities that these trends present.
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