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Leverage TV data to maximize Addressable TV Advertising opportunity

While deployment of Targeted TV Advertising, AKA Addressable TV Advertising solutions, is ramping up across the industry, its power is truly unlocked once AI is used to extract cross-system insights.

Addressable TV AdvertisingTargeted advertising holds a significant monetization opportunity for todays Pay-TV operators. If we look at the VO Targeted TV advertising solution, we see that it enables them to diversify their revenues and launch new services in an effort to mitigate revenue stagnation and cope with the industrys main challenges of recent years. 

Amongst other factors, these include the drop in subscription prices, the rising cost of content rights, and the loss of their traditional role as home network providers due to growing cord-cutting and cord-shaving trends, which are expected to further intensify with 5G. 

Targeted TV Advertising increases both the yield and the revenue for the same inventory. For example, Instead of running two commercials in a one-minute break, operators can run 10 commercials, with each one targeting a different, highly relevant audience segmented via their own usage data.

Furthermore, utilizing artificial intelligence with TV and first-party data can provide invaluable insights into viewerspreferences, behavior, and household composition, enabling operators to personalize both their content offerings and advertising, thus creating highly engaging, profile-based viewing experiences alongside highly rewarding audience segmentation. 

Targeted TV Advertising web banner

Inventory or non-inventory? It doesn’t matter

Targeted TV Advertising holds great opportunities for all kinds of operators, from the largest to the smallest, and whether they have a pre-existing inventory or not. VO Targeted TV Advertising solution, for instance, provides a unified platform to serve advertising for Live, VOD, cloud DVR, OTT, IPTV, cable, satellite, networks — you name it! —  on STBs and connected devices.

The key is that beyond the ability to manage it wisely and effectively, operators with an existing inventory can boost their reach and overall revenues through AI-based insights and analytics, which enables them to not only optimize performance but also to actually extend viewing time through the increased engagement afforded by the analytics.  

In other words, the AI-based insights help operators gain a better understanding of user behavior and preferences to not only optimize their ads in real-time and target specific – and local -audiences but also to create additional opportunities for them to show targeted ads to their increasingly engaged viewers. 

For operators without an inventory, the Targeted TV advertising solution provides the opportunity to use the ready-made, off-the-shelf smart infrastructure to connect with various TV channels and support multi-ad servers. This allows them to leverage their existing first-party usage data to offer highly attractive and equally rewarding segmentation while extending their ability to support and measure ad-insertion.

Challenges in delivery

One of the main challenges of advertising-based services is, first and foremost, maintaining user satisfaction. The solution is aimed at increasing revenues, not causing user frustration by closely monitoring exaggerated ad load. Indeed, using the addressable TV advertising model enables the reduction of ad loads, which contributes towards higher user satisfaction and reduces churn.  

The second challenge, as with anything related to data, is obviously data privacy. Protecting viewers' data in compliance with the GDPR and other privacy-related legislation at first seems to be a challenge, but for TV operators is actually an opportunity. As TV is a close and controlled trusted environment by viewers and advertisers alike, operators have the edge to ensure that no personal data is being shared, keeping operators in full control over data at any given time via the right set of tools.

Moreover, as a result of the GDPR and similar privacy regulations, the value of first-party data has increased tremendously due to the lack of data availability and accompanying consent management requirements. These are two areas where TV operators have an advantage, as they are both trusted by their users and in daily communication with them, which enables them to capture consent with relative ease. 

Further challenges include maintaining frame accuracy, establishing connections with multiple advertisers, handling linear peak viewing, and supporting legacy components. To be successful with Targeted TV Advertising, operators need to choose a solution that fully caters for all these and much more, - while also being their bridge between the digital world and their own platform.

How AI helps operators to optimize their service

AI tools are holding a prominent role in optimizing targeted TV advertising for cable and broadband operators. The following flow chart helps define its multi-purpose role.

Addressable TV Advertising flow chart

Put simply, the AI-based insights are the primary wheel driving the whole process into motion; the Embedded AI algorithms produce valuable, in-depth insights on viewers behavior and preferences, resulting in highly-profitable segmentation, including household composition, personal interests, life moment events, and more. There are several different categories of insights: 

  • User Preferences: WHAT do viewers like? These are the insights regarding the interests of the individuals inside a given Household. For example, Real Madrid fans, gadget seekers, tech-savvies, foodies, etc.   
  • User Behavior: the WHEREand HOW? These insights involve the way in which the content is being consumed. For example, through which devices? At home or on the go? Do they indulge in binge-watching etc…
  • Household Composition: a collection of insights on the way a household is structured: how many viewers are there, what is their current life stage (a young family or an elderly couple, etc.) Ultimately, this insight answers the question WHOis using the device? 
  • User Exposure: an important insight particularly for big brands, and a place for collaboration between traditional linear TV advertising and targeted advertising, empowering brands to target potential customers based on their previous exposure to a specific campaign.  
  • Life Moment Events: events of significant change in the life of an individual of a family can also be identified via AI — for example, the birth of a new child, a persons retirement, graduation, relocation etc. — enabling more accurate and relevant advertising.

AI’s Key Role in Addressable TV Advertising

The aggregation of usage data into a holistic overview of users and its transformation into highly specific segments is enabled through ML and AI, which are what empower providers to interact with the ad-tech ecosystem on premium revenue-share rates. 

At VO, our actionable insights are based on heavy AI and ML capabilities that we have developed throughout the last decade while we keep constantly updating our research and algorithms and evolving with the times.

We also use AI to draw insights into the effectiveness of various content sources, enabling personalized and measurable content discovery for maximum user satisfaction and improved content acquisition.

All in all, the data-driven AI analysis of usage flows and consumption patterns enables continual performance optimization and effective segmentation, empowering operators to deliver superior user experiences while maximizing their service monetization and boosting their ROI.

Dror Mangel

Dror Mangel is VP TV Products & Solutions. Prior to joining Viaccess-Orca he gained business development and product management experience from leading startups in Israel’s ‘Start-up Nation’, working with many global Fortune 500 customers. He is an expert in data-driven solution and is driven by data and a passion for creating B2C + B2B products from their early ideation stages to commercial launch, always focusing on the market's needs. He holds a Bs.C. in Industrial Engineering and Management from Technion - Israel Institute of Technology, and an MBA from Tel Aviv University.