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Marketing without segmentation is a lot like shouting into a crowded room and hoping the right person hears you. Without a clear way to communicate in a noisy marketing environment, your message gets lost in the mix.
With segmentation, you can identify your target audience, speak to their needs, and deliver the right message at the right moment. Companies that use segmentation are 130% more likely to understand customer motivations, resulting in more effective campaigns and deeper audience relationships.
In this article, we’ll break down four of the most effective customer segmentation methods, when to use each, and how Experian’s audience solutions can help.
What is segmentation in marketing?
Segmentation is the process of splitting a large audience into smaller groups that share similar traits, like demographics, location, behavior, or firmographic characteristics. As a marketer, these segments enable you to choose channels, messaging, and offers that resonate with each group.
Whether you’re targeting new homeowners in Texas, loyalty shoppers in retail, or small business decision-makers in finance, segmentation helps you stand out to them and get results.
Why should marketers segment their audiences?
Effective audience segmentation fuels accuracy, performance, and personalization at scale. Here’s why you should invest your time and marketing budget in honing your audience segments.
Maximize your marketing ROI
Nobody wants to waste money talking to the wrong crowd. Using various methods of segmentation, you can focus on those who want to hear from you — and the payoff can be huge. For marketing channels like email, segmentation can drive up to 760% more revenue than non-segmented campaigns. The more targeted your message, the better the return.
Create a unified omnichannel strategy
Segmentation helps ensure that every channel, from email and social media to display, SMS, and direct mail, operates from the same playbook.
Once you define your target audience segments, you also need a trusted identity partner to sync them across platforms and environments. This ensures you can deliver consistent, personalized experiences at every touchpoint and your audience receives the same message in the proper context, regardless of where they engage.
Strengthen customer loyalty
Roughly 75% of consumers are loyal to brands that “get” them. When you strive to understand your customers, they’re more likely to stay. Segmentation enables you to personalize communications based on your target segment’s values, behaviors, or preferences, encouraging repeat business.
Expand into new markets
With segmentation, you can analyze existing customers to identify common traits and use that data to pinpoint similar groups in new regions or markets. For example, if your top customers are middle-class parents in suburban areas, you can target lookalike segments in other cities with tailored messaging.
This makes it easier to expand with confidence, knowing you’re reaching people who are more likely to convert.
Lower customer acquisition costs
Rather than forcing you to cast a wide net, segmentation enables you to focus your budget on high-potential audiences across channels, reduce acquisition costs, and minimize wasted spend on low-intent audiences.
Four segmentation methods and examples
Let’s look at four different methods of market segmentation. We’ll define each, share when to use them, and give real-world examples to help you apply them.
1. Demographic segmentation
Demographic segmentation breaks your audience into groups based on gender, income, age, education, marital status, occupation, and household size. It’s one of the most foundational segmentation methods because it’s easy to implement and often tied directly to buying behavior.
Demographic data makes it easier to get the tone, offer, and channel right from the start. And when you combine demographic segmentation with other segmentation methods, such as behavior or location, the impact multiplies.
When to use it
Use demographic segmentation when your product or service is clearly more relevant to people in a specific life stage, income bracket, or household type.
Among all methods of market segmentation, demographic data is often the easiest starting point. It’s especially effective for industries such as financial services, healthcare, education, retail, and others, where consumer needs change based on demographics.
Examples
As a real-world example, a health supplement company used Experian data to segment its ambassador program audience into four demographic groups based on lifestyle and household makeup. These included younger singles, value-seeking families, high-income spenders, and older empty nesters.
Applying these insights at registration allowed the brand to deliver personalized, channel-specific communications that boosted acquisition and retention. The approach led to stronger engagement and more meaningful customer connections.
2. Geographic segmentation
This method of market segmentation categorizes people by location, including country, region, state, city, zip code, or even climate. It’s a simple yet effective way to tailor your marketing, as location often influences everything from lifestyle and language to shopping habits and product needs. It’s most often used among brands with physical locations or region-specific campaigns.
Whether you’re promoting snow boots in Colorado or sunscreen in California, geographic segmentation helps you stay relevant to the local context.
When to use it
Geographic segmentation is ideal when your offer or message changes depending on climate, culture, availability, or local regulations. It’s also helpful for planning market expansion or testing the performance of different methods of market segmentation across regions.
Examples
One home furnishings retailer partnered with Experian to understand how customer needs varied across store locations. Using a mix of client data and Experian demographics, we segmented stores based on their surrounding customer base, like urban, white-collar shoppers in metro centers versus lower-income households in more remote cities.
These insights enabled the retailer to tailor inventory, marketing strategies, and ad copy for each store type, resulting in more relevant customer experiences.
3. Behavioral segmentation
Behavioral segmentation centers on how people live their lives — their interests, habits, and decision-making patterns. It includes factors like past purchases, engagement frequency, brand loyalty, product usage, browsing patterns, and responsiveness to offers or promotions.
Among all of the segmentation methods, this one provides insight into intent, helping you go beyond who your audience is to understand what they do. You can use behavioral insights to re-engage former customers with relevant offers, reward loyal buyers with personalized perks, or guide high-intent shoppers toward conversion with timely nudges.
When to use it
Behavioral segmentation is best when you want to personalize based on intent, habits, or engagement stage. It’s particularly useful for retention, reactivation, or cross-selling strategies.
Examples
In practice, a national big-box retailer partnered with Experian to better understand customer behavior during grocery store visits. The goal was to identify distinct “trip missions” that could drive category trial and increase basket size. We analyzed everything from basket contents to customer composition and segmented visits into 11 unique missions.
For example, the “All Aisles Online” segment represented large households (often homeowners with families) stocking up on household staples through online orders. In contrast, the “Marketable Mission” segment captured smaller, likely renter households making quick trips for non-essentials.
These behavioral insights empowered the retailer to adjust promotions based on the intent behind each visit, strengthen customer relationships, and drive growth.
4. Firmographic segmentation (B2B)
Firmographic segmentation is like demographic segmentation for businesses. It groups B2B audiences based on attributes such as annual revenue, location, company size, industry, and organizational structure. You can also segment by job title or decision-maker role to better target key stakeholders.
This method is great for aligning your messaging, sales strategy, or product offerings with the unique needs of various business types. A startup in the tech sector will likely respond to a very different pitch than an enterprise manufacturer, and firmographic data helps you speak to both with precision.
When to use it
Use firmographic segmentation when marketing to other businesses, especially when your product or service has different benefits depending on business size or sector.
Examples
Recently, a B2B client partnered with Experian to gain a deeper understanding of the revenue potential of their existing business customers. Using firmographic data, we segmented the client’s customers into distinct groups based on the characteristics most strongly tied to spending behavior.
For each segment, we calculated potential spend, defined as the 80th percentile of annual spend within that segment. This allowed the client to identify high-value accounts with untapped growth potential.
For example, one customer, ABC Construction, had spent $4,750. But based on their segment’s profile, their annual potential was $9,000. That insight revealed a $4,250 opportunity to deepen the relationship through more targeted marketing and sales efforts.
Best practices for market segmentation
Regardless of the segmentation method you use, the following best practices will help you maximize the benefits of your efforts.
Start with clean, reliable data
Segments are only as good as the data behind them. If your data is outdated, inaccurate, or incomplete, your segments will result in ineffective targeting and a wasted budget. Utilize accurate, compliant, up-to-date sources like Experian Marketing Data, ranked #1 in accuracy by Truthset, to ensure your targeting is on point.
Test and refine segments continuously
Business goals, market conditions, and behaviors are constantly changing. What worked last month or even last week might not work today. By adjusting your segments over time, you make sure your marketing stays relevant, focused, and effective. Use A/B testing, performance metrics, and audience analytics to iterate on your segments and improve results over time.
Align segments with personalized messaging and offers
Each segment has distinct needs, preferences, and motivations, which means generic messaging won’t resonate effectively. Once you’ve built your segments, personalize your creative, copy, and offers to appeal to each group and increase the likelihood of engagement and conversions.
Integrate segmentation across all platforms
If someone sees one message in an email and a completely different one in an ad or on your website, it creates confusion and weakens trust. From CRMs and email platforms to ad tech and analytics tools, make sure your segmentation method is applied consistently across every channel to improve performance and build a cohesive brand experience.
Segment your audiences with Experian
Effective audience segmentation is at the heart of every successful marketing strategy, but in this fragmented, privacy-conscious landscape, grouping your audience into meaningful, actionable subgroups is more challenging than ever. That’s where we come in.
With coverage of the entire U.S. population, Experian helps marketers define and categorize broad audiences into precise segments using rich data on demographics, behaviors, financial profiles, and lifestyle traits. These insights make it easier to personalize messaging, optimize media spend, and drive better outcomes.
From ready-to-use syndicated audiences to custom segments and even Contextually-Indexed Audiences that align targeting with content, Experian offers flexible segmentation solutions that perform across digital, TV, programmatic, and social channels.
In our most recent release, we introduced over 750 new and updated audience segments across key categories, including a brand-new category for Experian, giving marketers more accurate, behavior-based targeting options than ever before.
- 135+ new CPG audiences, a brand-new category for Experian, built from opt-in loyalty card and receipt scan data
- 240+ new automotive audiences covering ownership and in-market shoppers
- 100+ new high-spending behavior audiences focused on specific merchant categories
- 24 new wealth and income segments with refined household net worth tiers
- 13 new lifestyle-based housing audiences for family- and household-focused targeting
- 250+ refreshed financial segments with improved naming conventions for better discoverability and clarity
Together, these segments give marketers more accuracy to reach high-intent consumers based on real-world behaviors, spending patterns, and financial capacity.
Audience solutions powered by consumer insights
Experian Marketing Data, one of the most comprehensive and accurate consumer databases in the U.S., is the core of our segmentation capabilities. Backed by over 5,000 demographic and behavioral attributes, it helps you understand not just who your customers are but how they live, shop, spend, and engage, too.
Each audience segment is built with privacy and precision in mind, using a blend of demographic data, financial behaviors, lifestyle signals, and media habits. With these consumer insights, we’ll help you uncover meaningful patterns that lead to smarter strategy.
Experian’s pre-built audiences
Our syndicated audiences are pre-built, ready-to-activate segments based on shared characteristics from age and income to purchase behavior and lifestyle indicators. When speed and scale are a priority, these segments offer a fast, effective way to reach your target audience.
Experian’s 2,400+ syndicated audiences are available directly on over 30 leading television, social, and programmatic advertising platforms, as well as within Audigent for activation within private marketplaces (PMPs).
Here’s what’s new from our August 2025 release:
- CPG shoppers by category (e.g., Frozen Food Shoppers, Multi-Vitamin Shoppers)
- Luxury EV owners and auto brand shoppers (e.g., Rivian, Polestar, Cadillac)
- High spenders in specific categories (e.g., men’s grooming and women’s accessories)
- Ultra high-net-worth households (e.g., Net Worth $50M+) and likely home sellers
- Young Family Homeowners and Growing Family Apartment Renters
Custom audiences for specialized targeting
Need a custom audience? Reach out to our audience team, and we can help you build and activate an Experian audience on your preferred platform. Additionally, work with Experian’s network of data providers to build audiences and send to an Audigent PMP for activation.
Contextually-Indexed Audiences
Experian’s Contextually-Indexed Audiences offer a privacy-safe way to reach relevant consumers in the moments that matter without relying on identity signals or third-party cookies. These segments combine Experian’s consumer insights with page-level content signals, enabling you to align targeting with intent and mindset, even in cookieless or ID-constrained environments.
Want to take your segmentation strategy to the next level? Let’s talk. We’ll help you define your audience in ways that drive real results.
Talk to our team about your segmentation methods today
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Claritas, known for advanced consumer segmentation, is bringing its premium audiences into Experian Data Marketplace. PRIZM® Premier, P$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