CTV Ad Targeting 101: An Advertiser’s eBook to Getting Started

Connected TV advertising is among the fastest-growing marketing channels. Recent reporting forecasts the ad format will increase by 21.2% in 2023, and should see double-digit growth through subsequent years.

What gives connected TV its value? According to a report from Innovid and Digiday, 63% of marketers say CTV advertising allows for more precise audience targeting.

It’s obvious, then, that connected TV offers powerful targeting capabilities. But how can advertisers new to the space ensure they leverage CTV targeting properly? Read ahead to gain a better understanding of ad targeting on connected TV and our best practices for reaching audiences with laser-like precision.

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Why target on connected TV?

Linear TV relies on broad, traditional audience segments. On the other hand, connected TV leverages digital targeting, allowing advertisers to go beyond demographic targeting.

Imagine you’re an advertiser for a beauty store. As an advertiser on linear TV, you can target women between the ages of twenty to forty-five.

Conventional demographics, though, only scratch the surface. Targeting on connected TV allows for a deeper level of personalization that better engages your audience. Want to target your most loyal customers? Retarget those who have recently made a purchase. Need to expand your reach? Build a lookalike audience using any data you have about your ideal customers.

How does CTV ad targeting work?

We know targeting on connected TV is powerful, but how exactly does it work? Let’s break down how this works in the programmatic world.

1. The advertiser first needs to set up their target audience. The requirements of the target audience are translated into signals, like IP addresses and device IDs.
2. The criteria are entered into the demand-side platform, which will bid on ads meeting those requirements.
3. A user watches a show, triggering a bid request.
4. The demand-side platform then examines the bid request. Using a variety of methods, the demand-side platform can gauge if the bid request matches the parameters of the target audience. In other words, the demand-side platform will only bid on requests that match the same people the advertiser is looking to target.
5. If the bid is won, the advertisement is served to the viewer.

The same concept exists for direct deals — or an agreement on the publisher’s part to reserve premium inventory for an advertiser. While inventory is not bought programmatically, a match must still exist in order for the publisher to properly target their audience on behalf of the advertiser.

What are the different types of connected TV targeting?

First-party data

Advertisers who use first-party data targeting use information collected directly from customers or users of a product or service. Advertisers have several options when it comes to using first-party data to target audiences, such as retargeting.

Third-party data

Third-party data targeting occurs when advertisers target viewers using data collected by a third party, rather than by the company or organization that is doing the targeting. Third-party data gives marketers ways to target based on demographics, affinities, hobbies, interests, ownership, lifestyle, purchase behavior, brand propensities, habits, life events, and more. There are several major third-party data vendors, including Experian, Nielsen, and Comscore.

Geotargeting

Geotargeting involves targeting viewers whose TV is located in any specific region or state. By targeting specific audiences based on location, advertisers can drive foot and web traffic, test ad creative for different locations, and even give themselves a competitive edge.

Contextual

Contextual targeting refers to targeting consumers watching specific content genres. This means advertisers can get in front of audiences already consuming content in line with your brand or campaign, increasing the chances a viewer engages with an ad and converts.

Retargeting

Retargeting on connected TV refers to serving an ad to a user previously exposed to a brand. Advertisers can use retargeting to help brands reengage users that have recently visited their site, but have yet to make a purchase.

Lookalike

Lookalike targeting includes identifying a group of individuals who share similar characteristics or behaviors to a company's existing customers, and then targeting advertisements to this group. Because these lookalike audiences are similar to a brand’s actual customers, the chances of converting are higher — making this a great way for advertisers to cost-effectively expand their reach.

Device/Platform

Targeting users based on devices or platforms includes limiting viewing methods to specific device types, like connected TVs/streaming devices, over-the-top (OTT, or its constituent parts, mobile, tablet, or browser, individually), or game consoles.

Data Collection Processes

There are two main ways advertisers and publishers collect data.

Probabilistic data

This approach collects anonymous data from multiple sources, including device manufacturers, streaming platforms, content providers, and third-party data providers. Probabilistic algorithms and statistical modeling techniques are then applied to infer relationships and make educated guesses.

Let’s say your brand’s target audience is female vegan endurance athletes — around 500 users. To make it scalable, you build a lookalike audience.

First, you collect IP addresses, wifi signals, and other probabilistic data points. Then, probabilistic algorithms and methods stitch this information together — almost like putting together the pieces of a puzzle. It finds 10,000 users that are likely to be female, vegan endurance athletes.

This is your new lookalike audience. No — you can’t say the users within this audience are definitely female, vegan, or enjoy endurance sports. But, by using probabilistic data, you can infer how they behave and look.

It's important to note that while probabilistic data collection can provide valuable insights, it inherently carries a level of uncertainty. The accuracy of predictions depends on the quality and diversity of the data sources, the effectiveness of the statistical models, and the underlying assumptions made during the probabilistic analysis.

Deterministic data

Deterministic data collection starts with users voluntarily registering or signing up for CTV services or applications. During the registration process, users provide their personal information such as name, age, gender, email address, and sometimes additional details like ZIP code or household income.

CTV devices may undergo an authentication process to establish a secure connection with the service provider. This authentication can involve device-specific identifiers, such as unique device IDs or MAC addresses, to associate the device with a specific user account.

Once users are registered and authenticated, their interactions with the CTV service or application are tracked. This includes data points such as content viewed, ads watched, duration of viewing sessions, and interactions with the user interface. This data is collected directly from the CTV platform or application

Deterministic data collection relies on the user's willingness to share personal information and authenticate their devices. This approach generally provides more accurate and precise user insights compared to probabilistic data collection. However, privacy concerns and regulatory compliance, such as obtaining user consent and securing user data, are crucial considerations when collecting and processing deterministic data.

First or Third-Party Data: Which to Choose?

There are three buckets of data from which advertisers can target audiences. How do they differ, and when should each be used?

Essentially, it boils down to whether or not you own the data collected. Did the viewer willingly give you this data? Are you retrieving it from an outside party?

First-party data refers to information that advertisers and publishers collect directly from their own customers or audience. Because it comes straight from the source, this data is often more reliable and accurate than that gathered by an outside party.

There are several use cases here for CTV advertisers. Take retargeting, for instance.

Imagine you’re an advertiser who owns an e-commerce store, and you notice web traffic to your site has dropped. With first-party data, you can target your CTV campaign to those who have been to your site and notify them of new updates to your store.

How? You know who's been to your site because you own the site, and subsequently, all of the data collected on those who have visited it. You can then use that information to compile a list of those who have visited in the past and retarget them to capture their attention.

Second-party data can be thought of as first-party data a brand shares with a partner. Essentially, both parties are allowing each other to access their first-party data — creating new insights for each side.

A common use case here is complementary brands sharing audience data with each other. Think of an airline sharing audience data — such as flight information, loyalty program data, and traveler preferences — with a hotel chain. This second-party data enables both parties to create more targeted marketing campaigns.

Third-party data is defined as data a brand obtains from a third party — or someone they don’t have a direct relationship with. In CTV, advertisers can obtain this information from third-party data providers like TruOptik, LiveRamp, and Nielsen.

These data providers aggregate data from a variety of sources, which is then compiled into a singular database. While this allows advertisers to access an incredible amount of data, it has its drawbacks. Because data is sourced from multiple places, advertisers lack visibility into where data is coming from — and can’t ensure its accuracy with 100% certainty.

CTV advertisers can use third-party data for a myriad of reasons, including:

• Reaching a broad audience
• Unlocking new audiences

Best practices for targeting on connected TV

1. Avoid spreading yourself too thin

Connected TV offers incredibly granular targeting capabilities, but as the saying goes, you can have too much of a good thing. While it’s important to identify a range of audience segments, a narrow pool of users can lead to missing prospective customers.

To avoid this pitfall, It’s important to remember to strike the right balance. Rather than creating excessively narrow segments, aim for segments that have sufficient size and represent a meaningful portion of the target audience.

For instance, instead of hyper-specific interest targeting, consider using broader interest categories that still align with the target audience. For example, rather than targeting users interested in "Running Shoes for Marathon Runners," it may be more effective to target a broader category like "Fitness Enthusiasts" or "Sports and Athletics."

2. Go beyond basic demographics

With connected TV, advertisers can target audiences based on how they’re behaving, what they’re consuming, where they’re watching, and more. They can use third-party vendors, first-party data, or a mix of both. In other words, advertisers have extensive options for advanced targeting in the connected TV space.

While demographics provide a useful starting point, advertisers should make the most of all connected TV has to offer. Go beyond age, gender, and location to truly engage your target audience. By delving deeper into behavioral, contextual, and psychographic factors, advertisers can unlock the full potential of CTV ad targeting.

3. Think about your goals before you begin

Your targeting strategy will depend on your brand’s KPIs. Are you looking to increase conversions? Do you want to build brand awareness? Where your metrics fall into the funnel will determine what type of targeting strategy you implement.

Our campaign with Metro Vein Centers is a great example. Based on their core KPs, building brand awareness and driving down CPV, our team decided to run two simultaneous campaigns: a retargeting campaign and a geotargeting campaign.

Why? Retargeting works well for performance-oriented campaigns, thanks to its ability to drive conversions and lower-funnel metrics. Geotargeting, on the other hand, is well-suited for upper-funnel metrics, including brand awareness.

Get In Front of Your Audience With Connected TV Targeting

With countless options and platforms available, precise targeting has proven to be the key differentiator in driving engagement, conversions, and ultimately, business success.

To unlock the full potential of CTV targeting, you need the right strategy and the right tools. Enabled by leading data partners and powerful machine learning, Simulmedia’s TV+ platform uses advanced targeting to generate unmatched levels of reach against your target audience. From content to geolocation to device type and more, we go beyond age and gender demographics to reach target audiences. Get started by scheduling a demo.