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How to Better Monetize Video Advertising: First-Party Data Is King

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New consent-based opt-in policies across apps and websites, like Apple’s App Tracking Transparency in the iOS 14.5 update and Google’s move to retire third-party cookies, give more control to consumers, but certainly hamper advertisers who rely on third-party data to build user profiles.

Addressable advertising—the ability to serve up video ads to specific individuals, rather than large demographic groups—is therefore becoming more challenging. Advertisers clearly want to reach people who are most likely to buy, but how do you find these people and what is the most effective way to reach them?

An important, but too often overlooked, component is the ability to generate sophisticated viewer profiles that advertisers are demanding. And this starts with first-party data, which is the information collected directly from your subscribers and includes more in-depth behavioral data points than third-party data.

First-party data is already becoming a prerequisite in media owners' programmatic ad sales. Some have spent years trying to develop their first-party data sets, with mixed results. In 2020, they saw those data sets become more important when pitching advertisers, and in 2021, most expect to make that data the pillar of their programmatic advertising sales, especially in light of third-party data collection.

Advertiser demand has also accelerated that push. Not only are advertisers more frequently asking about deal options involving first-party data, but operators are finding the deals employing those options are likely to be more lucrative. Advertisers signing private marketplace deals, including first-party data as an option, spend more than twice as much compared to deals that don’t include the data, according to insider sources.

The increased importance of first-party data has coincided with heightened interest among buyers in the quality of the data and how it is packaged and made available as audiences or attributes. While basic attributes should be straightforward for an operator to create, they don’t provide sufficient differentiation or the level of hyper-targeting required to significantly uplift campaign performance. More sophisticated attribute creation is not cost-effective for an operator to undertake themselves, requiring teams of data scientists as well as the experience and ability to productionize outputs at scale. The cost-benefit analysis does not justify operators doing this in-house.

First-Party-Based Profiles Are Essential for Advanced Addressable Advertising

An advanced addressable advertising solution must have the capability to generate highly predictive profiling attributes gained from AI and machine learning algorithms to build a detailed picture of individual-level viewing behavior over time. It is critical that such profile generation features rapid automated development and recalibration and is both highly scalable and industrial in its operational deployment into ad tech systems. 

Rich, actionable, and differentiated subscriber profiles are far more attractive than standard demographics for advertisers to be able to hyper segment audiences. Benefits of first-party data include:

  • Superior targeting results beyond basic gender, age, household, and geography 
  • Profiles that best represent the current first-hand behavior of subscribers
  • Access to insights not available from third-party data suppliers 
  • Profiles that are less costly than purchasing third-party data for use as targeting attributes

A fully mature profiling solution should also be able to pinpoint audiences who have intent to purchase as well as those who demonstrate affinity for a broad listing of specific sectors, such as arts & crafts, consumer electronics, finance, travel, and more. The ultimate goal is to create attributes based on current actual behavior (not claimed behavior) in order to provide significantly more accurate and meaningful target audiences to advertisers.

First-Party Profiling Must Clearly Demonstrate Payback

Video service providers looking to better monetize using first-party profiling in advanced advertising need to address two big challenges from advertisers: measurability and targeting payback. Measurability is a big issue in the industry. Advertisers want to know if the ads they have paid for are being viewed for the durations and frequencies they required and by the audiences that they specified. For this reason, an assured and independently auditable measurement is crucial. This is more challenging for broadcasters but can be achieved using a representative viewing panel. However, this requires suitable analytical expertise to develop.

Targeting payback is the second big challenge and refers to the need for targeting attributes that are offered to be suitably discriminating. In short, they must demonstrate uplifts and returns that are greater than not using any targeting at all. Addressable advertising is more expensive and operationally complex for an advertiser to deploy compared to broadcast linear campaigns. If the results are not better than just broadcasting your advertising, then why bother with targeting?

A huge ecosystem of adtech already exists to support targeted digital advertising and there are many vendors with platforms for deploying addressable TV. However, there are very few solutions for predictive automated first-party profiling and manual approaches can be costly, risky, and slow.

Advanced ad solutions can provide an effective way to reach relevant audiences with relevant ads that resonate with viewers and help build new revenue streams but predictive first party audience profiling is a key component of success.

[Editor's note: This is a contributed article from ThinkAnalytics. Streaming Media accepts vendor bylines based solely on their value to our readers.]

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