
We’re excited to introduce the next segment in our Q&A series, Ask the Expert! Ask the Expert features a series of conversations with product experts where we dive into the areas you care most about like identity resolution, targeting, attribution, and more. Our next segment features a conversation about sell-side targeting.
Mike Chowla, SVP of Product at OpenX joins us to chat with Experian’s SVP of Sales & Partnerships, Chris Feo. OpenX is the world’s leading sell-side platform for audience, data, and identity targeting. In their conversation, Mike and Chris review:
- The shift to targeting on the sell-side
- How first- and third-party data are being used on the sell-side
- How OpenX is thinking about alternative IDs

What is sell-side targeting?
Sell-side targeting optimizes the way buyers and supply-side platforms (SSPs) work together. This approach moves the responsibility of inventory and audience targeting from the demand-side platform (DSP) into the SSP, providing advertisers with increased reach and better performance.
With sell-side targeting, locating your target audience becomes easier as you have a more direct connection with publishers. This increases your ability to scale against a target audience. Specifically, the SSP directly matches the buyer’s audience or data segment to the publisher inventory and audience and automatically sends the impression to the buyer’s DSP of choice via a deal ID, providing advertisers with improved reach and performance metrics as well as control over their inventory. With more direct access, your budget can likely go further, and you can decrease your effective cost per mille (eCPM) and get more working media.
“Supply-side targeting is the next phase of how supply path optimization (SPO) and buyers will need to work more closely with SSPs.” – Mike Chowla, SVP, Product, OpenX
Buying on the sell-side vs. open exchange
When buying on the open exchange, you have access to a vast number of impressions. With sell-side targeting, you can apply your campaign targeting directly on the supply-side and activate those impressions through a deal ID. Sell-side targeting works across various formats including web display, mobile, in-app, and connected TV (CTV) for a seamless advertising experience.
OpenX offers the unique capability to match users using their device graph within their SSP. This means you can target users from traditional data sources such as cookies or mobile ad IDs (MAIDs) and reach them in CTV or app environments. This gives you even more reach and precision in your advertising efforts.
The role of first- and third-party data on the sell-side
Buyers are showing a keen interest in bringing their own first-party data into the process of sell-side targeting. Meanwhile, certain agencies have been actively involved in working with identity and data. OpenX is currently collaborating with several agency ID solutions such as Choreograph, Merkel, and Horizon.
Buyers are also purchasing third-party data and data segments from various providers through OpenX’s platform for sell-side targeting purposes. By utilizing this data on the supply side, buyers are able to increase the match rate against their first- and third-party data segments in all environments. This ultimately maximizes scale against these audiences and drives a more efficient CPM due to eliminating waste.
Measurement and attribution on the sell-side
In the current state of SSP advertising, there is more of an emphasis on targeting capabilities than measurement and attribution. That said, SSPs can provide granular log level reports that can be utilized for multi-touch attribution (MTA) or mixed media models (MMM). These granular insights not only inform measurement and attribution models, but they also provide valuable optimization insights such as clearing price.
Additionally, advertisers have all of the same reporting options that they’re used to getting through their DSP because their buys are activated via deal ID in the DSP of their choice.
What to consider when transitioning to sell-side targeting
There are two primary items you should consider when transitioning to sell-side targeting:
- Supply
- Reach
Reach
Collaborating with partners who have the right capabilities can greatly improve reach and audience extension across different devices. For instance, if you bring your first-party audience or a third-party audience and are identifying that consumer via a cookie or MAID, being able to extend that targeting segment to other devices and platforms can be highly beneficial.
Supply
It’s crucial to collaborate with partners who have the right access to supply and direct connections with publishers. While targeting is essential, it’s equally important to have high-quality supply to drive performance.
Reaching consumers in a cookieless future
Whether you’re targeting on the demand or sell-side, it always starts with the consumer and who you’re trying to reach.
Significant changes in the consumer privacy landscape are impacting advertisers’ ability to access various signals emitted by consumers through their devices and browsers. Recent developments from Apple and Google have further amplified this situation.
Alternative IDs as a solution to signal loss
In response, we’re seeing the emergence of alternative IDs like UID2, Ramp ID, and ID5. OpenX supports these types of IDs and considers them crucial for audience buying in a privacy-centric cookie-less future.
We are still in the early stages of this evolution. While some of the IDs have good coverage, cookies will continue to be the primary targeting method as long as they remain available.
Nevertheless, we see alternative IDs as one of several solutions that will become increasingly important as third-party cookies disappear. Contextual buying will also emerge, and a set of solutions will come together to enable advertisers to keep finding their audience in a cookie-less world.
Overcoming signal loss with identity resolution
Looking ahead, as we continue to lose signals due to the evolving consumer privacy landscape, we will witness two things:
- Continued fragmentation
- A wide variety of identifiers
Content will continue to be available on various devices. We’re currently experiencing the emergence of connected TV, but who knows what other devices will surface over the next five to ten years. As cookies disappear, which have been the primary identifier, and alternative IDs are introduced, the wide variety of identifiers will create further fragmentation. This highlights the need for identity in the future.
Identity resolution at Experian matches fragmented identifiers to a single profile to create a unified, cross-channel view of your consumers. Our identity resolution solutions can help future-proof your marketing strategies.
How Experian and OpenX work together
Experian is a key player in OpenX’s OpenAudience solution and helps to power many of their data segments as well as their identity graph. While OpenX collaborates with a variety of providers and operates a fully interoperable platform, Experian remains valuable to the core technology within OpenX’s SSP.
“Experian powers a lot of the data segments and identity graph that OpenX has in our OpenAudience capabilities as part of our SSP.” – Mike Chowla, SVP, Product, OpenX
Watch the full Q&A
Visit our Ask the Expert content hub to watch Mike and Chris’s full conversation on sell-side targeting. In the Q&A, Mike and Chris also share their thoughts on the impact artificial intelligence (AI) will have on the AdTech industry and their go-to sources for staying up to date on all things AdTech.
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About our experts

Mike Chowla, SVP, Product, OpenX
Mike Chowla is the SVP of Product at OpenX where he leads product development and innovation, from customer discovery and user research to the development, delivery, and support of a market-leading product suite. Chowla holds a BS in Engineering from the University of Southern California, and an MBA from The University of Pennsylvania.

Chris Feo, Chief Business Officer, Experian
As SVP of Sales & Partnerships, Chris has over a decade of experience across identity, data, and programmatic. Chris joined Experian during the Tapad acquisition in November 2020. He joined Tapad with less than 10 employees and has been part of the executive team through both the Telenor and Experian acquisitions. He’s an active advisor, board member, and investor within the AdTech ecosystem. Outside of work, he’s a die-hard golfer, frequent traveler, and husband to his wife, two dogs, and two goats!
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Claritas, known for advanced consumer segmentation, is bringing its premium audiences into Experian Data Marketplace. PRIZM® Premier, P$YCLE® Premier, ConneXions® Premier and CultureCode® audiences are now available, giving marketers access to more than 1,700 syndicated segments in a frictionless, privacy-compliant way. Marketers can move from planning to activation faster, with lifestyle, and financial audiences built for modern media. The value of these insights is clear: richer, behavior-driven audience intelligence that supports more relevant targeting across connected TV (CTV), digital, and linear. How Claritas audiences are built Claritas audiences are built from more than 10,000 predictive behavioral indicators, robust survey linkages, and household-level demographic data. These inputs create deterministic, privacy-safe signals that go beyond broad demographic proxies and help reveal consumer intent. That detail matters in CTV and programmatic environments. Marketers can activate pre-modeled segments tied to automotive ownership, financial behaviors, telecom preferences, and brand affinities. Three ways Claritas audience support omnichannel activation High-fidelity signals for more effective targeting Claritas uses deterministic, behavior-based indicators to add context around lifestyle, purchase patterns, financial posture and technology behaviors. Each segment includes Living Unit ID (LUID) counts, CPM transparency, and match-rate details. Broad reach across channels Many segments include 30M–50M+ active LUIDs, supporting broad reach without sacrificing audience clarity. Activate these audiences in omnichannel campaigns across the destinations that matter most, including CTV, programmatic display/video, paid social, and email, enabled through integrations with major demand side platforms (DSPs) and activation platforms. Privacy-first design Claritas data is built from consented, privacy-safe inputs and does not rely on cookies or exposed personally identifiable information (PII). This approach supports cookieless media, including CTV. Where Experian adds lift to audience activation Experian's data marketplace and our identity and governance tools help operationalize Claritas segments for activation: Enhanced addressability: Deterministic identity resolution maps Claritas signals to reachable, active audiences. It utilizes Experian identity graphs, which are rooted in verified data, spanning 126 million U.S. households, 250 million individuals, and over four billion active digital identifiers. Activation: Integrations with major DSPs and media platforms support fast deployment. Governance: Our controls support responsible data handling through the activation workflow, and ensure available audiences comply to all federal, state, and local consumer privacy regulations. Together, Claritas segmentation depth and our identity resolution support audience planning, activation, and measurement at scale. How marketers use Claritas audiences Automotive: Connect with owners and intentenders A luxury automotive brand can target “Cadillac owners” or “Likely Luxury Intenders” using Claritas behavioral automotive indicators. With more than 42 million available LUIDs for Cadillac owners, original equipment manufacturers (OEM) can support CTV campaigns, conquest strategies, and multicultural initiatives with more confidence. Financial services: Reach high-value households Using P$YCLE® Premier, a card issuer can target consumers who actively use travel reward cards or who fall into specific wealth tiers. These insights help tailor offers, personalize messaging, and reach consumers more likely to convert, supported by Claritas’ AI-driven optimization that can increase conversions by up to 30%. The advantage: Claritas depth plus Experian scale Claritas audiences in Experian’s data marketplace give marketers a direct path from insight to activation. Claritas brings behavioral intelligence and segmentation depth and we bring identity, scale, and governance. Together, you can plan, activate, and measure campaigns with stronger audience clarity from day one. Contact us to get started FAQs What are Claritas audiences in Experian’s data marketplace? Claritas audiences are syndicated consumer segments built from behavioral, lifestyle, financial, and demographic data. Through Experian’s data marketplace, marketers can activate more than 1,700 Claritas segments using privacy-compliant, deterministic signals. Where can marketers activate Claritas audiences? Marketers can activate Claritas audiences directly through Experian’s data marketplace across CTV, programmatic display, social, email, and linear. Integrations with major DSPs and Experian identity resolution support privacy-compliant activation at scale. How are Claritas audiences built? Claritas audiences are built from more than 10,000 predictive behavioral indicators, survey-based insights, and household-level demographics. How does Experian support Claritas audience activation? Experian supports activation through identity resolution, governance controls, and direct platform integrations. Claritas signals are mapped to reachable audiences using the Experian identity graph. Latest posts

Why AI data governance determines trust in automated decisions AI is reshaping audience strategy, media investment, and measurement. Automated systems now make more decisions at scale and in real time. Trust in those decisions depends on the data that informs them. AI data governance provides the framework that allows organizations to answer foundational questions like: Which information or inputs guided this decision? Is the model respecting consumer rights? Could bias be influencing the outcome? If AI made the wrong call, how would we know? Without governed data, these questions remain unanswered. AI data governance creates accountability by establishing quality controls, consent validation and auditability before data enters automated systems. Most organizations are still building their readiness to govern data at scale. Many vendors highlight “fast insights” or “transparent reporting,” but few can support true data governance — the auditability, privacy-by-design, quality controls, and continuous compliance required for responsible AI. That foundation is where responsible automation begins. And it’s why trust in AI starts with data governance. Responsible automation begins with governed data Automation produces reliable outcomes only when data is accurate, current, consented and interoperable. AI data governance makes responsible automation possible by applying controls before data reaches models, workflows, or activation channels. AI systems may interpret context, predict signals, and act in real time. But no model, logic layer, or LLM can be responsible if the data feeding it isn’t governed responsibly from the start. This raises a core question: How do we ensure AI systems behave responsibly, at scale, across every channel and workflow? The answer begins with trust. And trust begins with AI data governance. Governing the data foundation for responsible AI Experian’s role in AI readiness begins at the data foundation. Our focus is on rigorously governing the data foundation so our clients have inputs they can trust. AI data governance at Experian includes: Model governance reviews before releasing new modeled attributes Feature-level checks ensuring no prohibited or sensitive signals are included Compliance-aware rebuilding and re-scoring, incorporating opt-outs and regulatory changes Validated delivery, ensuring attributes reflect the most current opt-outs, deletes, and compliance requirements By governing data at the source, we give our clients a transparent, accurate, and compliant starting point. Clients maintain responsibility for bias review within their own AI or LLM systems — but they can only perform those reviews effectively when the inputs are governed from the start. This is how AI data governance supports responsible automation downstream. Our 2026 Digital trends and predictions report is available now and reveals five trends that will define 2026. From curation becoming the standard in programmatic to AI moving from hype to implementation, each trend reflects a shift toward more connected, data-driven marketing. The interplay between them will define how marketers will lead in 2026. Download Privacy-by-design strengthens AI data governance Privacy gaps compound quickly when AI is involved. Once data enters automated workflows, errors or compliance issues become harder, and sometimes impossible, to correct. AI data governance addresses this risk through privacy-first design. Experian privacy-first AI data governance through: Consent-based, regulated identity resolution A signal-agnostic identity foundation that avoids exposing personal identifiers Ongoing validation and source verification before every refresh and delivery Compliance applied to each delivery, with opt-outs and deletes reflected immediately Governed attributes provided to clients, ensuring downstream applications remain compliant as data and regulations evolve Experian doesn’t govern our client’s AI. We govern the data their AI depends on, giving them confidence that what they load into any automated system meets the highest privacy and compliance standards. Good data isn’t just accurate or fresh. Good data is governed data. How AI data governance supports responsible automation at scale With AI data governance in place, organizations can build AI workflows that behave responsibly, predictably, and in alignment with compliance standards. Responsible automation emerges through four interconnected layers: 1. Input Privacy-first, governed data: accurate, consented, continuously updated, and compliant. 2. Enrichment Predictive and contextual insights built from governed data, ensuring downstream intelligence reflects current and compliant information. 3. Orchestration Reliable, AI-powered workflows where governed data inputs ensures consistency in audience selection, activation, and measurement at scale. 4. Guardrails Transparent, responsible innovation. Clients apply their own model governance, explainability, and oversight supported by the visibility they have into Experian’s governed inputs. Together, these layers show how data governance enables AI governance. AI integrity starts with AI data governance Automation is becoming widely accessible, but responsible AI still depends on governed data. Experian provides AI data governance to ensure the data that powers your AI workflows is accurate, compliant, consented, and refreshed with up-to-date opt-out and regulatory changes. That governance carries downstream, giving our clients confidence that their automated systems remain aligned with consumer expectations and regulatory requirements. We don’t build your AI. We enable it — by delivering the governed data it needs. Experian brings identity, insight, and privacy-first governance together to help marketers reach people with relevance, respect, and simplicity. Responsible AI starts with responsible data. AI data governance is the foundation that supports everything that follows. Get started About the author Jeremy Meade VP, Marketing Data Product & Operations, Experian Jeremy Meade is VP, Marketing Data Product & Operations at Experian Marketing Services. With over 15 years of experience in marketing data, Jeremy has consistently led data product, engineering, and analytics functions. He has also played a pivotal role in spearheading the implementation of policies and procedures to ensure compliance with state privacy regulations at two industry-leading companies. FAQs about AI data governance What is AI data governance? AI data governance is the framework that manages data quality, consent, compliance and auditability before data enters AI systems. Why does AI data governance matter? AI decisions reflect the data used as inputs. Governance provides transparency, accountability and trust in automated outcomes. Does AI data governance prevent bias? AI data governance does not eliminate bias in models. It provides governed inputs that allow organizations to identify and address bias more effectively. How does privacy-first design support AI data governance? Privacy-first governance applies consent validation and compliance controls before data is activated, reducing downstream risk. Who is responsible for AI governance? Organizations govern their AI systems. Data providers govern the data foundation that feeds those systems. Latest posts

A decade ago, you could buy media by broad categories and call it a day. But today, your audience lives in a curated world. They watch what they want, skip what they don’t, and expect what they see to match their interests. Research shows that when ads are tailored to households, people pay more attention, stay engaged longer, and are more likely to remember your ads. That shift in expectations is why addressable advertising continues to grow. It’s a practical response to how media works today, with audiences moving fluidly across platforms, streaming spread across services, and measurement spanning screens and environments. Under these conditions, reaching the right people depends on clarity, not approximation. Artificial intelligence (AI) strengthens that clarity. When applied responsibly, AI helps connect signals, deepen audience understanding, and deliver relevant messages while protecting consumer data. The result is advertising that feels more human, not less. What is addressable advertising? Addressable advertising is the ability to deliver personalized ads to specific individuals or households and measure results using privacy-safe data and identity. It works across digital, connected TV (CTV), linear TV, and over-the-top (OTT) streaming and relies on strong identity resolution and accurate data inputs to ensure your audience definitions remain consistent across channels and over time. Benefits of addressable advertising Addressable advertising changes how advertising performs by delivering messages to defined audiences, reducing wasted impressions, and making results simpler to measure. BenefitWhat it means for youClarityReach the right audience with the personalized messages they want, instead of hoping the right people are watchingEfficiencyAvoid wasted impressions by focusing spend where interest already existsHigher ROIImprove conversion by delivering messages that feel relevantOmnichannel consistencyCarry the same message across digital and TV without starting overMeasurable impactConnect exposure to actions so performance is clearPrivacy and complianceActivate audiences responsibly using privacy-safe data, clear governance, and compliant practices These are some of the reasons that addressable advertising has moved from a niche tactic to a core strategy. When audiences are clear, identity is connected, and measurement is built in, advertising becomes relevant, accountable, and easy to improve over time. Addressable advertising vs. traditional advertising Unlike traditional advertising, addressable advertising doesn’t depend on broad exposure or assumptions. It’s personalized by design and measurable by default, making it possible to connect ad exposure to outcomes. Another distinction is in how addressable delivers advertising to audiences and how performance is measured. Traditional media buysAddressable advertising buysYou pay for broad reachYou pay for relevant reach to defined audiencesAds run by placement or programAds are delivered to known households or individualsPersonalization is limitedPersonalization is built into deliveryMeasurement indicates trends, not who actually actedMeasurement connects exposure to actions by linking ads to defined audiences across channels But before you can activate addressable advertising, you need to understand who you’re actually trying to reach. What is an addressable audience? An addressable audience is a group of people you can identify and reach using data-based targeting. In other words, they’re not anonymous “maybe” viewers. They’re a defined audience you can activate across channels. Here’s what typically builds addressable audiences: FactorWhat it isWhy it mattersFirst-party dataData from your own relationships (site activity, app activity, CRM, emails, purchases)It’s your most direct view of existing customers and prospectsThird-party household and individual dataDemographic, behavioral, lifestyle, interest, and intent attributes from trusted providersIt fills gaps so your audience definitions don’t collapse when your own data is limitedIdentity resolutionA privacy-first way to match people across devices, households, and channelsIt improves accuracy so you don’t over-message the same people or miss them entirelyContextual signalsPage-level, content, or viewing context where ads appearIt reinforces relevance in the moment and complements addressable targeting when identity signals are limited How Experian helps with addressable audiences Experian helps you build and activate addressable audiences at scale without losing accuracy or trust. With more than 3,500 syndicated audiences available, you can activate consistently across 200+ destinations — including social platforms like Meta and Pinterest, TV and programmatic environments, and private marketplaces (PMPs) through Audigent. That means reaching people based on who they are, where they live, and their household makeup, using data governed with care. Our approach is built on accuracy first, which is why Experian data is ranked #1 in accuracy by Truthset for key demographic attributes. And when standard customer segments aren’t enough, Experian Partner Audiences expand what’s possible. These unique audiences are available through Experian’s data marketplace, within Audigent for PMP activation, and directly on platforms like DIRECTV, Dish, Magnite, OpenAP, and The Trade Desk. The evolution of addressability and why it matters more than ever As the media ecosystem shifts, reaching people across browsers, apps, CTV, and streaming platforms has become more complex. Signals are fragmenting everywhere as expectations for relevant, personalized experiences continue to rise, while reliable identifiers become increasingly challenging to access. In response, addressability is shifting from a channel-specific tactic to an identity-driven approach to reach and measure defined audiences across screens. That evolution puts new pressure on performance. Marketing budgets require accuracy and accountability, which means targeting must deliver measurable reach and outcomes you can trust. At the same time, the growth of CTV and streaming is expanding addressable TV opportunities. As CTV inventory grows, so does the need for cross-channel, identity-based activation that works consistently and supports reach, frequency, and measurement in one connected view. That’s why identity has become the foundation for making addressable advertising work today. When to apply addressable advertising You don’t need addressable for everything, but it shines when you need your spend to go farther with accurate targeting and resonant messaging. ScenarioWhy addressable helpsProduct launches and seasonal pushesReach people who are more likely to care without flooding everyone elseHigh-consideration purchases (auto, travel, financial services)Focus on likely intent and suppress audiences that don’t fitCross-channel campaigns (digital, TV, mobile)Keep messaging consistent across screensWhen using first-party data with AIUse AI customer segmentation to scale responsibly and improve performance without sacrificing accuracyRegulated categoriesRely on compliant data practices and clearer controls for regulated industries Addressable advertising is one way to put relevance and respect into practice — but it shouldn’t be the only time these principles apply. Marketers are expected to be thoughtful about who they reach, how often they show up, and how data is used across every channel. Addressable simply makes it easier to live up to that standard when accuracy, accountability, and scale matter most. Addressable advertising and third-party data There’s a common misconception that third-party data is no longer useful, but what’s really changed is the environment around it. In the early days of digital advertising, third-party data often felt like the Wild West. Today, modern third-party data is more transparent, better governed, and held to far higher standards with: Clear data sourcing Documented consent practices Regular quality audits Strict limits on how data can be used Used responsibly, third-party data plays a critical role in addressable advertising by complementing your first-party data and keeping audience strategies flexible as signals change. Benefits of third-party data When paired with identity resolution, high-quality third-party data helps you: Fill first-party gaps: Add demographic, behavioral, and interest-based insight when your own data is limited. Expand prospecting: Reach new audiences through modeling and lookalike expansion. Enrich segmentation: Combine household, behavioral, and interest signals to tailor creative, offers, and messaging to interests for more accurate and personalized activation. Support cross-channel addressability: Maintain consistent audience reach across devices and channels even as individual signals change. Why work with Experian for your data needs? At Experian, we approach third-party data with the belief that trust comes first. Our data is privacy-compliant, ethically sourced, and governed by strict standards so you can use it confidently. Accuracy matters just as much. Our identity and data-quality framework verifies that the data behind your audiences holds up in the real world — a key reason Experian is ranked #1 by Truthset for key demographic attributes. And because addressable advertising only delivers value when audiences move seamlessly from planning to activation, our audiences are interoperable by design. You can activate them across digital, social, and CTV platforms without rebuilding or reformatting your strategy for each channel. How AI is redefining customer segmentation Addressable advertising depends on audiences that stay accurate as people move across devices, platforms, and moments. Traditional segmentation built on static rules and snapshots in time can’t keep up with that reality. AI customer segmentation analyzes massive sets of household and individual data (such as intent, household demographics, purchase behavior, and content consumption) to identify patterns, predict intent, and group people into addressable audiences. As the AI advertising ecosystem continues to mature, reflected in industry frameworks like the LUMA AI Lumascape, segmentation and identity have become foundational layers rather than standalone tools. Those audiences update as conditions change, so they stay relevant instead of aging out. Here’s how AI-driven segmentation supports addressable advertising. What AI enablesWhy it mattersPredictive, intent-based audiencesAnalyze behavioral and transactional data to group people based on likely next actionsBroader audience availabilityAs more data signals are incorporated responsibly, AI makes it possible to support a wider range of addressable audience options without sacrificing accuracyDeeper insights from dataDiscover what people care about, how intent is forming, and which signals are most important with larger, more diverse data setsReal-time audience updatesKeep segments aligned as behaviors change, not weeks laterHigher accuracy, less guessworkRely on data-driven patterns for decision-making instead of assumptionsOngoing optimizationRefine audiences throughout the campaign lifecycle as performance signals come in We’ve used machine learning and analytics for decades to support responsible segmentation — balancing performance with privacy and transparency. That foundation now supports addressable advertising that adapts in real time while staying grounded in trust. Addressable TV: Targeting in the streaming era TV has become an addressable channel powered by data and identity resolution. CTV and OTT streaming are booming, while linear TV continues to decline, reshaping how people watch and how advertising works alongside it. For the first time, CTV spending is expected to outpace traditional TV ad spending in 2028, reaching $46.89 billion and signaling that addressable TV is now central to the media mix. With CTV and OTT platforms, advertising can now be delivered at the household level. That means two homes watching the same show can see different ads based on who lives there and what they like. This is what makes addressable TV possible. Benefits of addressable TV As streaming inventory continues to grow, addressable TV creates new ways to bring relevance and accountability to a channel once defined by broad exposure. Experian links identity data across streaming, linear, and digital platforms to help you manage frequency, attribution, and household-level insights in one connected view. Addressable TV also raises the bar. To manage reach, frequency, and measurement across streaming and linear environments, addressable TV depends on identity resolution that connects households across screens. Here’s how addressable TV helps you when identity is in place. What addressable TV enablesWhy it mattersHousehold-level targetingDeliver messages that reflect who’s watching, not just what’s onFrequency control across screensReduce overexposure and improve viewer experienceCross-channel measurement and attributionConnect TV exposure to digital actions, site visits, and conversionsMore efficient use of TV spendBring accuracy, accountability, and outcome-based insight to premium inventory and improve reach of streaming-first, harder-to-reach viewer segments Ultimately, addressable TV isn’t a replacement for linear TV, but it is an evolution. As streaming becomes the default viewing experience, the ability to engage TV audiences with the same care and clarity as digital is essential. Use cases for addressable advertising Addressable advertising works across industries because it adapts to how people make decisions. The examples below are illustrative scenarios that show how addressable audiences, identity resolution, and AI-driven segmentation can come together in practice using Experian solutions. Retail: Seasonal promotions A home décor retailer could use identity resolution and AI-driven segmentation to build addressable audiences, such as holiday decorators and recent movers, who are more likely to engage during peak seasonal periods. Campaigns could then be activated across CTV, display, and social, helping the retailer stay visible across screens while tailoring creative to seasonal intent. Automotive: In-market car buyers An auto brand might identify consumers nearing lease expiration using automotive-specific data tied to household and individual attributes. By suppressing current owners, the brand could avoid wasted impressions and activate addressable audiences across OTT and mobile to reach likely buyers during active consideration. Financial services: Credit card launch For a new credit card launch, a national bank could use modeled financial segments to reach credit-qualified prospects. Addressable digital advertising campaigns could apply frequency controls and personalized messaging, balancing reach with relevance while seamlessly measuring response. Streaming media: New subscriber growth A streaming platform looking to grow subscriptions could use an identity graph to exclude current subscribers. Likely viewers could then be targeted across CTV based on content preferences and viewing behavior, keeping spend focused on net-new growth. Media and entertainment: Audience expansion for a new release Ahead of a new release, a film studio could use behavioral and lifestyle data to identify likely moviegoers and fans of similar franchises. Addressable campaigns across CTV and digital video could help drive awareness and opening weekend attendance. Travel: High-value traveler acquisition A travel brand could use travel propensity data and household-level demographics to identify frequent flyers and family vacation planners. Personalized offers could then be activated across display, social, and programmatic channels to increase bookings while keeping spend focused on higher-value travelers. How Experian enables more effective addressable campaigns Addressable advertising is most effective when identity, data, and activation are connected from the start. Experian brings trusted household and individual data, privacy-first identity resolution, and broad activation partnerships together so you can move from audience insights to activation with minimal friction. Here’s how that comes to life across our core offerings. Identity resolution with Consumer Sync Consumer Sync connects devices, emails, digital identifiers, and offline data into a single, privacy-safe identity foundation. This connection helps your audiences stay consistent across streaming, linear TV, mobile, and digital despite changing signals. Audience insight and segmentation with Consumer View Consumer View supports clear segmentation, prospecting, and enrichment across industries. It combines demographic, behavioral, and interest-based data to help you build accurate, intent-driven audiences that reflect real people, not assumptions. Data is continuously updated and governed for accuracy. Omnichannel activation with Audience Engine Audience Engine enables direct activation of Experian audiences across CTV, digital, social, and programmatic platforms. It supports suppression, frequency management, and cross-channel consistency to keep messaging aligned and exposure controlled. More efficient media through curation and Curated Deals Curation combines data, identity, and inventory through Experian Curated Deals. These deal IDs, available off-the-shelf or privately, make it easier to activate high-quality audiences and premium inventory in the platforms you already use without custom setup. AI-enhanced segmentation and optimization Our AI-enhanced models analyze large data sets to create and refresh addressable audiences in real time, supporting intent-based targeting and ongoing optimization throughout the campaign lifecycle. These models work seamlessly with demand-side platforms (DSPs), ad platforms, and data clean rooms, so audience insights flow directly into activation and measurement without added complexity. Seamless integration with your ecosystem As an advertiser, you want addressable advertising to fit naturally into how you already plan and buy media. That’s why integration matters as much as insight. Experian integrates with leading DSPs, ad platforms, and data clean rooms, so you can activate addressable audiences in the environments you already use without reworking your strategy or adding complexity. This approach helps you: Build and activate addressable audiences: Reach the people you want with accuracy and respect. Activate across channels: Keep messaging consistent across digital, TV, and streaming. Optimize with data ranked #1 in accuracy by Truthset: Improve performance using the industry’s most reliable data. When identity, data, AI, and activation come together, addressable advertising does what it’s supposed to do: deliver relevance naturally, measure impact clearly, and give you confidence in every decision along the way. That’s the foundation for campaigns people want to engage with. Start creating campaigns audiences want to see Experian can help you apply addressable advertising in ways that respect consumers, perform across channels, and stand up to real-world measurement. Connect with our experts today to explore how addressable audiences, AI-driven segmentation, and identity-powered activation can work together in support of your goals. FAQs about addressable advertising What is addressable advertising? Addressable data-driven advertising involves delivering personalized ads to specific individuals or households using privacy-safe data and identity. What is an addressable audience? An addressable audience is a defined group of consumers you can identify and reach based on known household or individual attributes. What makes advertising addressable? Advertising becomes addressable when it’s possible to identify the audience by linking devices and households to people through identity graphs. This allows you to measure ad performance at the audience level and provide more personalized advertising. Is addressable advertising just for TV? Addressable advertising isn’t just for TV; it also works across digital, mobile, streaming, and social channels. How does AI help addressable advertising? AI improves addressable advertising by analyzing large data sets to predict intent, build more accurate audiences, boost performance over time, and improve your ability to find and build your audiences. Can addressable advertising work without cookies? Yes — identity resolution and first-party data are key to cookieless addressability. How does Experian support addressable advertising? Experian supports addressable advertising by providing trusted consumer data, privacy-centric identity resolution, and curated audience segments that activate across CTV, digital, mobile, and streaming platforms. Latest posts