AI-powered media measurement for OTT (over-the-top) and streaming platforms : The future of TV and video analytics

Mar 21

Introduction

The media industry is experiencing a period of rapid change, driven by the emergence of new platforms and devices. Media measurement has not kept pace with these changes, however, and the traditional TV measurement methods used today are outdated. Nielsen and other traditional TV metrics cannot accurately measure audiences who watch content online or on mobile devices—and this lack of accurate data creates problems for marketers, content creators and distributors alike.

What is OTT?

Over-the-top (OTT) is a technology that allows consumers to access content via the internet, instead of through a cable or satellite provider. OTT services include Netflix, Hulu, Amazon Prime Video and HBO Now.

The term “over the top” refers to delivery of television content without using cable TV operators as intermediaries. It was originally defined as being delivered over public Internet Protocol networks without requiring users to subscribe to traditional cable television service.[1] The popularity of high-speed broadband has allowed for growth in online streaming sites that offer digital video recorder (DVR) functionality and video on demand (VOD) services.[2]

Why are traditional TV measurement methods outdated?

Traditional ratings are based on TV viewing, which is increasingly being replaced by streaming. Traditional ratings don't include OTT viewing and they don't include mobile viewing. Traditional ratings are based on a sample of the population rather than all people who watch TV or stream video, so they're not representative of the entire audience that's actually out there watching content.

In other words, Traditional methods for measuring TV audiences have become outdated because the way people consume content has changed.

Why is OTT measurement different than traditional TV measurement?

How is OTT measurement different from traditional TV measurement? The answer is: it's more complex, more accurate, and much more granular.

In traditional TV, you're looking at a sample of households that may or may not be representative of the broader population. In OTT and streaming platforms, you can measure every viewer who streams your content—and every second that person watches. That's because these platforms are highly granular in their metrics. You can see exactly how long someone spent watching an episode of your show or what they did before they started watching it (or after). And because these platforms don't just report video consumption but also engagement metrics such as clicks and shares (among others), you have detailed data about how your content is performing on social media—and other channels beyond just streaming video services like Netflix or Hulu.

The ability to process and analyze large amounts of data in real-time, providing more accurate and up-to-date understanding of audiences.

With the ability to process and analyze large amounts of data in real-time, providing more accurate and up-to-date understanding of audiences. AI can also identify audience segments with high engagement or churn risk. This level of visibility into your audience is not available today with traditional measurement tools that are still used by most companies.

The ability to gain insights into audience behavior at a granular level, including information on individual viewers, their viewing habits, and the content they consume.

This information can be used to inform content strategy, distribution, and advertising decisions.

Data can help you better understand your audience and their needs, which makes it easier to create content that resonates with them. In addition, with the right data on hand, you’ll be able to make strategic decisions about how best to reach your audience.

The ability to identify patterns and trends in audience behavior, which can be used to inform content strategy, distribution, and advertising decisions.

With AI-powered media measurement, you can understand what content people are watching, how they watch it and what they do with it. You’ll also gain insights into the audience that is engaging with your content online.

You’ll be able to see how people engage with your content, including:

What parts of your content are most popular?
Which ads are most effective?
How much time people spend watching each clip?

AI will give you a complete picture of how users interact with all aspects of your OTT/streaming service — from on-demand viewing to live events and catch-up TV — across different platforms (e.g., set top boxes, smart TVs).

The potential to improve targeting and personalization of content and advertising, by understanding the preferences and habits of individual viewers.

Advertisers can use AI-powered media measurement to target specific audiences. For example, if you're an advertiser looking to reach new parents who live in Los Angeles, AI can help you reach your target audience with greater precision—and at a lower cost. By using machine learning techniques like natural language processing (NLP), advertisers are able to understand which consumers are most likely to respond positively to their ads based on what they've said in previous conversations about parenting or raising children.

Similarly, advertisers have the ability to understand more about who their customers are by tracking what they view on TV or online video services: What genres do they like? When do they watch? Who else watches with them? These insights can help them better understand how best utilize relevant content for each viewer's unique viewing habits when it comes time deliver targeted ads through OTT platforms like Sling TV or Hulu Live TV

The ability to measure the performance of content across different platforms and devices, providing a more comprehensive view of audience engagement.

We're seeing an evolution in the way marketers measure their campaigns, with AI-powered media measurement for OTT (over-the-top) and streaming platforms emerging as a key part of this. With the ability to measure the performance of content across different platforms and devices, providing a more comprehensive view of audience engagement.

This is more important than ever before, as marketers are faced with the challenge of measuring the impact of their campaigns across a rapidly changing media landscape. The rise of OTT and streaming platforms means that consumers can now watch content on any device they choose, meaning that it’s harder than ever to track whether viewers are actually engaging with your campaign or brand message.

The potential to improve the value of data-driven insights, by incorporating data from external sources, such as social media and search data.

The ability to combine OTT audience measurement with data from other sources will open up new opportunities for measuring multiple areas of the media landscape. This can be achieved through:

Integrating OTT content consumption statistics with social media analytics to understand what audiences are talking about around a specific show or streaming platform
Combining OTT content consumption statistics with search engine optimization (SEO) statistics to better understand how well an online video is performing in relation to other videos on a particular platform

The ability to monitor and track changes in the streaming landscape, providing early warning of emerging threats or opportunities.

For media companies, understanding how viewers are consuming content is critical for creating a product that meets consumer demand. The ability to monitor and track changes in the streaming landscape—whether it be for OTT platforms such as Netflix or Amazon Prime Video, or streaming services like HBO GO or Hulu Live TV—provides early warning of emerging threats or opportunities. It’s important to understand what’s happening with your content on these platforms so that you can make adjustments where necessary before they become an issue.

The ability to optimize the use of resources, by identifying the most effective marketing and distribution channels.

When you use AI-powered media measurement, you can understand the behavior of your target audience and optimize their experience. You'll know how they are likely to respond to different types of content and what type of content resonates best with them. You'll also be able to see if a particular marketing campaign was successful or not, which helps improve future marketing efforts and make better decisions about where to allocate resources.

Using AI-powered media measurement, you will have access to the following:

Detailed insights into audience demographics - age range, gender breakdown etc.
Audience engagement with your content (what platforms do people use most often? How long do they watch?)
Top performing players/channels used by this audience segment (e.g., YouTube stars vs traditional celebrities) - for example, what is their favorite music genre? What kind of news sources do they prefer?

The ability to support the creation of new revenue streams, by identifying new opportunities to monetize content and data.

With that in mind, here are some ways AI can help you make money:

Monetizing content and data. AI can identify more ways to monetize your original content by referencing what's already successful in the market (and hopefully better than what you're currently doing), including ads or even subscriptions. The same goes for how you analyze viewership data—AI will find patterns that allow you to charge advertisers more effectively based on their target audience's preferences.
Creating new revenue streams. An AI-powered platform can also help creators identify new sources of income, like sponsored content or products they can sell through their YouTube channels directly—or even completely unrelated businesses they'd like to start from scratch!

Conclusion

The future of TV and video analytics is bright, with new opportunities for innovation and monetization on the horizon. The key will be to understand how OTT and streaming platforms are different than traditional TV measurement methods, so that you can get ahead of the curve by incorporating these new insights into your content strategy, distribution plans, advertising decisions—and any other aspect of your business that’s affected by viewership data.

Vikas Gupta