7 essential CTV targeting strategies for B2B marketers

Types of CTV targeting methods

Connected TV offers a powerful suite of targeting capabilities that move far beyond traditional television advertising.

For B2B marketers, the key to success is layering these methods to move from broad audience segments to precise, account-based engagement.

Understanding each method is the first step to building a high-performance CTV targeting strategy.

1. First-party data targeting

First-party data targeting is the foundation of any high-performing CTV strategy.

It uses data that you already own (from your own CRM records, website visitors, event registrants, email subscribers, or past customers) to deliver ads to your most relevant audiences across connected TV platforms.

Unlike third-party data (which we’ll discuss next), first-party data give you direct access to verified buyer relationships.

And because first-party records already include firmographic and demographic targeting details, you can personalize creative with near-perfect accuracy.

This form of precise targeting allows you to connect with decision-makers who already know your brand or resemble your best customers—but in a more engaging, visual format.

Common applications include:

• Account-based targeting: Match CRM or ABM account lists to CTV audiences, ensuring your ads reach buying committees within key accounts you’re actively pursuing.
• Lead nurturing: Retarget existing prospects who’ve downloaded resources, visited pricing pages, or attended webinars, reinforcing your brand message through video storytelling.
• Customer retention: Serve tailored campaigns to existing customers. E.g., announcing updates, renewals, or cross-sell opportunities—to keep your brand top of mind.
• Upsell and expansion: Use behavioral data from product usage or customer health scores to deliver feature or upgrade-focused ads to current users.
• Event promotion: Target contacts in your CRM to drive attendance for upcoming webinars, conferences, or product demos.
• Churn prevention: Identify disengaged customers through low engagement signals and re-engage them with thought-leadership or success-story content.

2. Third-party data targeting

Third-party data targeting expands your reach beyond your owned audiences. It helps you connect with ‘net-new’ prospects who match your ideal customer profile but haven’t yet engaged with your brand.

This method relies on information aggregated and collected by external data providers. It includes behavioral, firmographic, technographic, and intent-based data sourced from publishers, platforms, and trusted data marketplaces.

For B2B marketers using CTV, third-party data is essential for scaling campaigns across multiple advertising platforms to new but relevant audiences.

This lets you reach decision-makers researching relevant topics, visiting competitor sites, or showing early signs of purchase intent, even if they’ve never interacted with your company before.

Common applications include:

• Market expansion: Identify and reach companies in new geographies or verticals that fit your ICP but aren’t yet in your CRM.
• Lookalike audience building: Use third-party data to find specific audiences that behave like your best customers, matching attributes such as company size, industry, and buying signals.
• Intent-based activation: Deliver CTV ads to organizations actively researching relevant topics or keywords across the web, signaling early-stage buying intent.
• Top-of-funnel awareness: Reach new prospects who fit your ICP but haven’t yet interacted with your owned channels.

3. Geographic targeting

Geographic targeting or geo-targeting in CTV marketing allows you to deliver ads based on the viewer’s physical location. This includes broad regions like continents or countries to granular levels like states, cities, ZIP codes or even specific business districts.

This approach ensures that your campaigns align with regional markets, sales coverage, and localized buying behaviors.

Due to CTV’s precision, geo targeting is far more advanced than traditional TV ads. You can combine it with firmographic or intent data to ensure your ads reach the right roles in the right region.

For example, IT leaders at manufacturing firms in Northern Europe or healthcare procurement teams in the U.S. Midwest.

Common applications include:

• Regional campaign alignment: Deliver CTV ads that match your active sales regions or field marketing territories.
• Localized messaging: Adapt creative and language for region preferences or industry trends within that area.
• Event and conference promotion: Target viewers near upcoming trade shows, summits, or in-person events.
• New market entry: Run brand awareness campaigns in newly entered regions to establish presence and recognition.
• Franchise or partner network alignment: Coordinate with channel partners or distributors in specific regions for co-marketing visibility.
• Geo-based performance optimization: Analyze campaign performance across markets to identify which region drives the strongest pipeline or conversion outcomes.

4. Contextual targeting

Contextual targeting delivers your CTV ads based on the content being watched— and not just on the profile of who’s watching.

This method doesn’t rely on personal identifies or behavioral data, instead, it aligns your brand message with relevant programs, topics, or themes at that moment.

For example, when someone is streaming a Bloomberg segment about digital transformation, or a YouTube TV discussion on cybersecurity, your ad for enterprise software, automation tools, or data protection slides right in.

That sort of ‘timely relevance’ builds credibility and increases the likelihood of engagement or recall later in the buying process.

Common applications include:

• Competitive positioning: Serve ads around content where competitors advertise or appear, keeping your brand visible within similar audience contexts.
• Cross-channel continuity: Mirror the same contextual themes used in display, search, or social advertising to maintain consistent brand association.
• Top-of-funnel brand awareness: Align with broader business or innovation-themed shows to build familiarity with emerging audiences.
• Content-based intent: Target ads alongside content that reflects active research interests (e.g., supply chain innovation series).
• Thought-leadership content: Deliver CTV ads alongside professional or educational video content that supports your brand’s expertise narrative.

5. Advanced retargeting

Advanced retargeting allows you to re-engage decision-makers and accounts who have already interacted with your brand across other channels, and continue the conversation.

When your brand appears across a buyer’s favorite streaming platform after they’ve engaged with your product page or webinar, it strengthens recognition and recall at the exact time when decisions are being shaped.

And on top of that, advanced retargeting uses device graphs, account-level mapping, and cross-channel data, allowing you to target entire buying committees.

In this case, when one contact from an account visits your site, your message can reach others within the same organization via connected TV.

Common applications include:

• Website retargeting: Serve CTV ads to users who have visited high-value web pages (pricing, product, or demo pages).
• ABM audience retargeting: Re-engage accounts that have interacted with earlier campaigns but haven’t yet converted.
• Event follow-up campaigns: Retarget event or webinar attendees with messaging that continues the conversation.
• Content engagement sequencing: Deliver video ads to individuals or accounts that downloaded whitepapers, case studies, or guides.
• Intent-based retargeting: Reconnect with organizations showing increased research activity or topic-level interest signals.

Related → How to Level Up Your B2B Advertising Campaigns with ABM

6. Lookalike audiences

Lookalike audience targeting takes what you already know about your best customers (their firmographic traits, behaviors, and buying patterns) and uses it to find new audiences that share the same profile.

Here’s how it works: It starts with your first-party data, typically a list of high-quality accounts, engaged leads, or closed-won customers. CTV platforms then use this “seed audience” to identify other companies or viewers who exhibit similar characteristics, interests, or intent signals.

Since this is your own data, the targeted audience are more likely to convert and become long-term customers. It’s an effective way to expand your TV campaigns using high-quality CTV inventory, ensuring your message appears only in premium, brand-safe placements.

Common applications include:

• Demand generation: Build awareness among lookalike audiences to feed the top of the funnel with better-fit leads.
• Re-engagement support: Identify audiences similar to previously churned customers, offering them updated messaging or new solutions.
• ABM list growth: Supplement your account-based marketing lists with net-new but high-probability targets.
• Cross-sell and upsell: Find adjacent segments with similar pain points or use cases as your current customers.
• Event promotion: Build lookalikes from past event registrants or attendees to attract similar professionals to upcoming webinars or conferences.

7. Device and platform targeting

Device and platform targeting allows you to control where your CTV ads appear across specific devices, operating systems, or streaming services.

It’s how you ensure your campaigns reach the right audience depending on their device type or platform— whether they’re watching via a smart TV, gaming console, mobile device, or desktop streaming app.

This mode of target is quite precise. It understands that not all viewing environments carry the same level of attention, engagement, or professional overlap.

Decision-makers might catch business content on a Roku TV during early hours, stream webinars via YouTube TV on desktop, or use mobile devices for short-form thought leadership content.

Common applications include:

• Smart TV targeting: Deliver premium, large-screen ad experiences for brand storytelling and awareness among executive audiences.
• Streaming platform targeting: Choose specific networks (like Hulu, YouTube TV, or Sling) aligned with your audience’s viewing habits. Some marketers even explore Netflix and other premium streaming services now offering ad-supported tiers.
• Cross-device retargeting: Maintain message consistency by following prospects from CTV to mobile or desktop environments.
• Device-based optimization: Adjust ad creative lengths, formats, and calls-to-action based on the device type.
• Frequency capping across devices: Prevent overexposure by managing how often a user sees your ad across different platforms.

Related → Mastering Account-Based Advertising 

How CTV platforms identify audiences: Deterministic vs. Probabilistic data

Effective CTV targeting depends on how accurately a platform can identify who’s watching. In a channel where multiple users may share the same screen or household, the precision of that identification is quite important.

To make that possible, CTV platforms rely on two primary data models to match viewers with audiences: deterministic data and probabilistic data.

Deterministic data

Deterministic data uses verified, first-hand identifiers such as email addresses, login information, or customer IDs, to match ad impressions to specific individuals or accounts with a high degree of certainty.

On Connected TV platforms, deterministic matching typically happens when a user logs into a streaming app or device using credentials tied to their identity (for example, a business email or a single sign-on account).

This login event links the viewer directly to a confirmed data source like a CRM record, subscription database, or identity graph, allowing advertisers to target or measure with near 100% accuracy.

Because deterministic data relies on verified identifiers, it’s considered the most accurate and reliable method of CTV targeting. It ensures that when you deliver a CTV ad, you’re reaching exactly who you think you’re reaching.

How it works:

• A user logs into a streaming app (like Hulu or YouTube TV) using an authenticated account.
• That login connects to a persistent identifier (email, device ID, or subscription record).
• The CTV platform matches that identifier to advertiser-supplied data—often from CRMs, DMPs, or ABM platforms.
• Once matched, the platform can deliver ads to verified users or accounts with deterministic precision.
• Performance and engagement data feed back into the advertiser’s system for closed-loop measurement.

Strengths of deterministic data

• Accuracy: Deterministic targeting provides near-perfect match confidence, ensuring ads reach verified users and accounts.
• Compliance and privacy alignment: Because data is based on consent and first-party relationships, it aligns well with GDPR, CCPA, and other privacy regulations.
• Granular measurement: Enables clear attribution between ad exposure and downstream outcomes like website visits, pipeline influence, or conversions.

Probabilistic data

Probabilistic data uses statistical modeling and machine learning to predict who a viewer is. It analyzes factors such as IP addresses, device types, time of usage, app installations, and shared viewing habits.

By layering these signals, the model predicts with a high probability  that multiple devices belong to the same user or household.

For B2B marketers, that means your message can reach a wider audience without being restricted to logged-in or verified accounts.

How it works:

• The CTV platform collects device-level and environmental data such as IP address, device type, time of day, and viewing behavior.
• Machine learning models analyze these signals and cross-reference them with known datasets (like household demographics or browsing trends).
• The system then assigns probability scores estimating which household, company, or user segment is most likely associated with that device.
• Advertisers use these modeled audiences to serve ads that are contextually and demographically relevant, even without verified identity data.
• Performance data continuously refines the model, improving targeting accuracy over time.

Strengths of probabilistic data

• Scale: Expands audience reach beyond logged-in or CRM-matched users, increasing overall campaign exposure.
• Speed: Enables faster audience activation and broader campaign launches without dependency on authenticated datasets.
• Adaptability: Works across devices and platforms where deterministic identifiers aren’t available (e.g., household TVs, shared work devices).

Note: The most effective CTV strategies combine both. They start with a deterministic foundation to reach their core target accounts and then use probabilistic data to intelligently scale their campaigns and find new opportunities.

Recommended → Beyond the basics: Enhanced strategies for next-level advertising

Best practices for CTV Targeting

Build a high-fit audience before you narrow in

A common problem with B2B CTV campaigns is ‘over-targeting’. Marketers often narrow their criteria (e.g., layering on zip codes) so tightly that their potential audience becomes too small to deliver meaningful results.

A fix to this is to start with a broad but strategic foundation. Build your target account list with 200-500 high-fit companies and layer criteria thoughtfully. Use firmographics, industry segments, and intent data to guide the mix, but avoid stacking too many filters at once.

For example, a cybersecurity SaaS company targeting enterprise IT buyers might begin with a national campaign across the financial sector, then refine over time based on which sub-segments engage most (e.g., regional banks vs. global institutions).

Align your targeting layers to the buyer’s journey

For a successful campaign, you need to layer multiple targeting options to strengthen both relevance and reach.

A strong framework might look like this:

• Start with first-party data (e.g., CRM accounts, known buyers).
• Layer third-party data to narrow by job function or seniority.
• Add contextual targeting to place ads alongside relevant business or industry content.

For example, a SaaS brand targeting CFOs might use first-party CRM data to identify key accounts, overlay third-party data to isolate finance leaders, and then run CTV ads during programming related to business strategy or market trends.

Match your strategy to the outcome you want

Your targeting strategy should always reflect your goal— whether that’s awareness, engagement, or conversion.

• If you’re running a brand awareness campaign, broader targeting (like industry-level or lookalike audiences) works best to increase recognition within your total addressable market.

The metrics here should focus on reach, completion rates, and brand lift.

• For pipeline-driving or performance campaigns, tighten your scope. Use first-party and intent data to target accounts already engaging with your content or being pursued by sales.

Here, success metrics should shift toward account engagement, pipeline influence, and ROAS.

Design creative that mirrors what your audience cares about

Tailor your creative to the context of the campaign:

• For broad, contextual campaigns, lead with an aspirational or thought-leadership message (e.g., “Empowering the Future of B2B Finance”).
• For retargeting campaigns, use urgency or specificity (e.g., “See how 200+ CFOs cut reporting time by 40% with our platform”).

This ensures that your messaging reaches the right people at the right time, and also resonates with their stage in the journey.

Related → What Is People-Based Advertising? 

Control ad frequency to maximize attention

B2B audiences are smaller and more defined than B2C, which means repetition fatigue sets in faster.

If a VP of Regional Sales sees the same ad ten times a week, they’ll become resistant—and likely even lose interest.

To maintain balance, set frequency caps, typically 3-5 exposures per household per week. This ensures your message stays top-of-mind without becoming intrusive.

Adopt a full-funnel approach

CTV works best when you integrate it as part of the buyer’s journey. That means implementing different targeting types to support different stages of the funnel.

For example:

• Top of funnel: Use lookalike audiences and contextual targeting to drive broad visibility and awareness.
• Middle of funnel: Use intent and advanced retargeting to keep engaged accounts warm.
• Bottom of funnel: Use deterministic, first-party targeting to keep your brand visible to decision-makers during active evaluation.

For example, a SaaS provider might start with broad awareness ads on business news channels, then retarget viewers who visited their pricing page with customer proof videos, and finally show short “why us” messages to accounts in active pipeline.

Continuously test and optimize your targeting accuracy

A/B test your creatives (CTA, visuals, length), targeting combinations (first-party + contextual vs. lookalike + intent), and even delivery timing.

Then use engagement metrics and post-view conversions to fine-tune both audience and creative direction.

Monitor key KPIs such as completion rate, cost per completed view, and post-view conversions to measure campaign performance accurately and justify further optimization.

Related → How to Use Advertising Performance Metrics to Elevate Your Account-Based Strategy

Common challenges in B2B CTV targeting (and how to overcome them)

While CTV is a powerful channel for reaching B2B buyers, it comes with a unique set of challenges that don’t exist in traditional B2C advertising.

Below are some of the common challenges, and how to overcome them:

Fragmented data

CTV audiences are dispersed across multiple streaming platforms, apps, and devices. And unlike cookies or web tracking, there’s no single identifier that connects them all.

As a result, marketers struggle to unify viewer data into a consistent identity. This makes it difficult to know if impressions came from the same account, household, or even person.

Difficulty linking CTV ads to pipeline impact

An extension of the challenge we discussed above is measuring the true business impact of CTV ads.

This is because compared to display or search, CTV isn’t a click-based medium. That makes it harder for B2B marketers to connect impressions or completed views to actual business outcomes.

There’s also the issue of complex DSP setups, and inconsistent partnerships between platforms, creating gaps in measurement and optimization. It gets worse in multi-touch sales cycles where attribution is already complicated.

Privacy changes and data Regulation Pressure

As data privacy regulations evolve (GDPR, CCPA, and pending U.S. state laws), CTV targeting faces increasing scrutiny.

The depreciation of cookies, device IDs, and cross-platform identifiers threatens many known targeting methods. This leaves B2B marketers struggling to maintain reach and compliance.

Related → Digital advertising strategies for a cookieless world

Data latency problems

CTV campaigns often suffer from data lag—which means performance metrics like view completion, reach, or account engagement aren’t always available in real time.

As such, B2B marketers find it difficult to adjust targeting, creative, or bidding strategies dynamically. In fact, by the time insights surface, the budget may already be wasted on underperforming segments.

Demandbase: The only CTV platform built for B2B

Demandbase CTV is the first and only Connected TV advertising solution designed exclusively for B2B marketers.

Built from the ground up for complex, account-based environments, it gives marketing and sales teams the power to reach verified decision-makers across premium streaming environments with precision no consumer DSP can match.

Powered by Piper, our proprietary B2B DSP, Demandbase goes far beyond household demographics. It does what no other CTV solution can: connect your ads directly to the buying committees within your most valuable target accounts.

With Demandbase, you get:

• True B2B audience intelligence: Target by account, buying committee, and intent.
• Cross-channel orchestration: Connect CTV with display, social, and sales touchpoints in one unified motion.
• Account-level measurement: Attribute influence directly to pipeline creation and deal acceleration.
• AI-driven optimization: Refine campaigns automatically based on real-time account engagement.

Explore how Demandbase connects your CTV ads to the accounts that actually move pipeline.

FAQs: CTV targeting strategies for B2B marketers

What is CTV advertising, and how does it differ from linear TV?

CTV advertising (Connected TV advertising) delivers targeted video ads through internet-connected televisions and devices, rather than traditional broadcast channels.

This is different from ‘linear TV’, where ads are shown to everyone watching a particular program at a set time. Instead, CTV allows you to target viewers based on firmographics, interests, or account lists.

Is Connected TV advertising the same as OTT advertising?

They’re closely related but not identical.

• Connected TV advertising refers to ads shown on internet-connected televisions;
• while OTT advertising (over-the-top) encompasses all streaming devices and apps. This includes mobile, desktop, and smart TVs that deliver content outside of traditional cable or satellite providers.

In short, all CTV is OTT, but not all OTT is CTV.

How can I measure success in CTV advertising?

You can measure the success of your CTV advertising by using engagement and completion-based metrics.

Key indicators include completed view rates, reach, frequency, cost per completed view (CPCV), and post-view conversions.

There’s also modern platforms like Demandbase that lets you link those metrics to CRM or pipeline outcomes for deeper attribution insights.

Is CTV advertising expensive compared to traditional TV ads?

Yes, it is.

However, while CTV advertising can appear ‘costlier’ on a per-impression basis than traditional or linear TV ads, it’s typically more efficient because you’re only paying to reach qualified, addressable audiences.

Do I need a DSP to run CTV campaigns?

Not necessarily. Some CTV platforms (like Demandbase) include built-in buying tools.

However, a DSP becomes essential if you want full control over your ad buys, bidding strategy, and cross-platform frequency management across multiple streaming networks.