In our first article on TV’s evolution into a performance-driven medium, we explored how consumers have fundamentally shifted their relationship with television. No longer just a place to passively watch shows, CTVs have become platforms for fitness, health & wellness, education, and smart home control — mirroring the interactivity and utility of smartphones and laptops.

For advertisers, this shift to interactivity opens the door to something revolutionary: the ability to turn television into a real-time conversion channel.

It might feel counterintuitive to think of CTV data as predictive of behavior other than what someone might want to watch, but with smart TVs now a two-way medium, they have become central to household function. This results in innumerable data signals that are predictive of a multitude of behaviors.

As viewers interact with their TVs more frequently and with deeper action across an expanding range of activities, advertisers can benefit from those interactions to close the purchase  loop both on the screen and across devices.

In this article, we’ll explore how the data generated by smart TVs, combined with advances in machine learning and AI, are transforming TV from a branding tool into a performance marketing engine.

The DNA of Performance: Right Person, Right Message, Right Moment

Performance media — search and social in particular — owe their efficiency to a blend of:

• Rich user data at scale
• Rapid feedback loops
• Algorithmic optimization

 CTV checks all those boxes.

The Right Person: Better Targeting Through Science

Targeting on CTV benefits from a similarly data-rich environment that fuels other digital platforms. CTV device manufacturers aggregate thousands of data points from opted-in users to group viewers into precise audience segments using algorithmically driven multivariate clustering techniques. The result is hyper-relevant targeting powered by three key data types: 

• Device-usage data: Logs when and for how long users engage with the TV itself — the TV operating system, the apps on that TV, and the devices plugged into that TV.
  
• Interest data: Goes beyond what content is watched, capturing what types of apps users interact with across lifestyle, entertainment, smart home, and other categories.
  
• Background data: Incorporates external signals predictive of user response such as time of day, internet speed, weather, and other non-TV specific data points.
  

CTV manufacturers use machine learning techniques to discern which users are most likely to convert. These include:

• Look-alike modeling: Using behavioral data to find new users that mirror an advertiser's target audience.
  
• Predictive targeting: Scoring each audience member based on their likelihood to drive a desired action.
  

The Right Message: Optimizing Creative and Inventory in Real Time

The message, including where and how it is served, is just as critical as the audience in driving outcomes. On CTV, as in other digital media, this is where creative and inventory optimization come into play.

Machine learning enables advertisers to test a wide variety of creative formats, placements, and message sequencing strategies to determine what performs best. This includes:

• Traditional :15s and :30s video ads
• Interactive ad formats that invite action
• Vertical video units that match social content
• Native placements on TV home screens that reach every user as they browse

Even if users don’t take action based on an impression, models can assess whether an ad exposure contributed to a downstream conversion and build that information into the model to help meet performance goals.

The Right Moment: Intelligent Bid Optimization

For performance media, timing matters just as much as targeting. Bid optimization on CTV is now powered by data about the audience and the ad opportunity, including the placement and the cost. Optimization occurs via first- and third-party data, which connects ad exposures to real-time outcomes through mobile measurement partners (MMPs) and other attribution tools.

These advanced algorithms can:

• Forecast likelihood of conversion based on the audience, opportunity, and message, and bid appropriately on an ad opportunity
  
• Adjust bids in real time to balance cost and expected outcome
  
• Attribute conversions across multiple exposures over time, adjusting the model to improve future performance

The combination of the scale and granularity of data alongside adaptive machine learning intelligence ensures that budgets are allocated where they’ll deliver the highest return on ad spend (ROAS).

Samsung Ads’ Performance Stack: Building CTV for Conversion

At Samsung Ads, we’re building performance solutions that demonstrate that CTV data is predictive of behavior – ushering in the era of “Conversion TV.” Our solutions are meeting and beating client goals on specific actions and ROAS expectations, positioning us directly against social and search as effective performance media.

Reaching nearly 80 million U.S. households across our smart TVs mobile phone footprints, we bring greater scale and diversity of data to our performance stack. By combining our exclusive TV and mobile data with machine learning, we target and convert users efficiently. Ads are delivered across premium Samsung CTV inventory, driving users to take action across devices and in person. Attribution is calculated via leading MMPs, and pricing is based on driving your business – so you only pay for the outcomes that we deliver.

The Future of TV is Measurable

The expectations Americans have of TV today are the same ones they have of every other screen: personalization, immediacy, and interactivity. As smart TVs evolve into dynamic platforms for everything from entertainment to ecommerce, the opportunity for advertisers is clear: This is the moment to stop using TV as a one-way broadcast and start leveraging it as a performance channel. Because when you combine the impact of TV with the precision of digital, you don’t just reach audiences, you move them.

In our next article, we discuss why it’s more important than ever to expand performance efforts away from search and social, which are being challenged by gen AI solutions and stalling audience reach.

Want to talk about how Conversion TV can optimize your campaigns now? Connect with us today.