Third-Party Data Targeting for CTV: Benefits & Tactics

Third-party data. It’s a term that’s thrown around, and yet few take the time to detail its pros and cons — much less strategies for using third-party data effectively in a privacy-conscious landscape.

The truth is that third-party data targeting is just one tool in an advertiser’s belt. It can provide game-changing insight into the broader market and external trends. But overreliance on any single tactic is never the right choice.

Privacy regulation and the deprecation of cookies have given third-party data a bad rap. Concerns about its reliability have also contributed to this. Even so, thinking of the world in terms of first- vs. second- vs. third-party data is reductive when marketers can, in fact, layer several tactics.

In this article, we get into the nitty-gritty of what third-party data is, the conversations surrounding it in 2025, and how it can be used to balance precision and scale in programmatic advertising campaigns — with a focus on connected TV (CTV). 

Third-Party Data Explained

Third-party data is sourced externally, often aggregated and sold by data providers without a direct link to your business. There’s often little transparency into how this data is processed and the origin isn’t always disclosed.

This makes it less reliable than data that is gathered directly by a brand (we’re looking at you, first-party data). After all, what would you trust more: a detailed account of an event from an eyewitness you know well, or a story about the same event that's been passed along through several strangers?  

Concerns about data accuracy are warranted. And yet, third-party data is still a marketer’s best bet for understanding the market at large. This is because it offers unrivaled insight into broad trends, making it particularly valuable for new audience discovery. 

To use another metaphor, consider Who Wants to Be a Millionaire, where contestants had the option to “poll the audience” or “phone a friend.” Phoning a friend works great when that individual has specific expertise on a given topic, but the audiences’ collective opinion often points contestants in the right direction by aggregating so many data points.

Similarly, third-party data may lack the granular detail of first-party data, but it provides a valuable "pulse" on the market — revealing broader trends, interests, and potential audience segments that you might otherwise miss. 

Types of Third-Party Data

Third-party data comes in many shapes and sizes, with some data providers specializing in specific types. But it can typically be classified across one of the following categories.

• Demographic data: This includes basic information like age, gender, income, education, and location. While not as granular as first-party demographics, it provides a starting point for segmenting large audiences.
  
  
• Behavioral data: Behavior data spans online browsing history, purchase patterns, website engagement, and app usage. It focuses on what users are actively doing, offering clues about their interests and preferences.
  
  
• Contextual data: Contextual data has to do with the content users consume. It allows advertisers to target viewers based on the shows a person watches, the articles they read, or the websites they visit.
  
  
• Interest-based data: This data aggregates information about hobbies, passions, and lifestyle choices. It allows marketers to reach viewers based on their affinities, even if they haven't directly interacted with your brand.
  
  
• Intent data: As one of the most valuable types of third-party data, intent data signals a user's active intent to purchase a product or service. For instance, automotive companies use intent-data to identify people who are in the market for a new car. 

Third-Party Data Targeting Tactics for CTV Advertising

Much like the data types listed above, standard third-party CTV targeting spans a few key tactics.

Here’s a closer look. 

Demographic Targeting

Demographic targeting uses detailed demographic information (age, gender, income) to reach the right audience segments for a campaign. Because demographic targeting is so broad, we’d only recommend using it as one parameter layered into a more comprehensive strategy. 

Example: Say a financial services company wanted to promote services like student loan refinancing, investment advice, and credit card options to young professionals. With demographic CTV targeting, the firm could locate individuals between the ages of 25 and 35 within a specified income bracket.

Geotargeting

Geotargeting pinpoints viewers by state, designated market area (DMA), zip code, or distance from a storefront to eliminate ad waste and focus on key regions. This is another tactic that should be combined with additional capabilities for enhanced precision.

Example: A regional grocery store chain could use geotargeting to reach viewers within a specific radius of their store locations. The brand could then enhance its targeting by layering in demographic information, such as household size and income level, to ensure its ads are reaching the most relevant audience. This approach not only maximizes ad spend but also increases the likelihood of driving foot traffic to their stores.

Behavioral Insight

Behavioral insight uses data about viewers’ browsing behavior, shopping habits, and online activities to serve highly relevant ads that align with user interests. 

Example: This could include targeting users who frequently visit travel websites with ads for airlines or hotels. Alternatively, a grocery store chain could locate gluten-free households with a more relevant message.

Purchase History

Insight into purchase history enables advertisers to target customers based on their past purchasing patterns, thereby reaching frequent buyers, high-value customers, or specific product categories. 

Example: Someone who regularly buys organic produce online might see ads for a local farmers' market.

Social Media Activity

By tapping into social media data, advertisers can connect with audiences based on their online interactions, preferences, and engagement levels. This could involve targeting users who follow certain brands or influencers on social media.

Example: A home services company could target users who’ve engaged with posts from a home improvement account.

Intent-Based Targeting

Intent-based targeting uses signals indicating a user's intent to purchase or engage, allowing for precise targeting during key decision-making moments.

Example: An auto dealer could rely on real-time buying signals from Edmunds to reach in-market car buyers.

Contextual Targeting

Contextual targeting involves serving ads that align with the content users are consuming, creating a seamless and top-of-mind ad experience. 

Example: This could take the form of showing an ad for a cooking appliance during a cooking show or an ad for a local golf club during a live golf broadcast.

Going Beyond Standard Targeting With Data Enrichment

While the tactics listed above are useful, we’ve found that the most effective approach is to create a custom audience by layering several targeting tactics. For that reason, we work with brands and agencies to identify the perfect mix of data sources to achieve campaign goals.

This is where data enrichment comes into play. Data enrichment involves merging first-party data with third-party data to create a more comprehensive view of your target audience. For example, a brand might combine first-party CRM data with third-party demographic and behavioral data to identify a new audience that shares similar characteristics.

At Strategus, we call this look-alike modeling and it’s our best-performing tactic. We work with agencies and brands to use data from existing customers, website visitors, and CRM files to create look-alike audiences. This makes it possible to reach new, high-potential users who share similar characteristics and behaviors.

For example, a luxury furniture store might use look-alike modeling to identify individuals who exhibit similar shopping patterns to those of their high-value customers. We could analyze their own data to understand customer demographics, social media activity, and interests to build new audiences that are similar to those buyers.

Meet Your Customers Where They Are

The data-rich world of programmatic CTV lets advertisers pinpoint buyers like never before. While third-party data has come under scrutiny in recent years, it still plays a role in creating data-driven campaigns. 

At Strategus, we go beyond basic demographics to pinpoint exactly who sees your ad — ensuring that every impression drives engagement and action. Our ecosystem of 200+ data providers achieves the perfect balance of precision and scale. 

Ready to get started? Contact us today.