At A Glance
Your audience strategy works like a story. First-party data sets the outline, but scale and relevance come from connecting additional signals such as contextual, geographic, and behavioral data. Experian helps CMOs unify these inputs through identity, enabling consistent activation, privacy-forward targeting, and measurable outcomes as marketing strategies evolve in 2026.How should CMOs think about data as part of their audience strategy?
The best digital marketers possess excellent storytelling capabilities—and they fuel the plot with data.
When you think about it, your audience strategy is the whole story, and the type of data you use helps create each chapter. Just as any good book incorporates numerous literary devices, you must use more than one type of data to develop a dynamic, relevant, and timely narrative that captures your target users’ attention.
In 2026, marketers should prioritize and invest in data and targeting strategies beyond just first-party to drive growth, improve efficiency, and strengthen customer relationships.
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.
Why is first-party data not sufficient on its own?
First-party data provides a strong foundation for targeting and measurement. It reflects information consumers have shared directly through brand interactions. That makes it reliable and central to audience strategy.
That foundation alone does not tell the full story. First-party data defines known customers, but limits reach and frequency. Growth depends on expanding beyond existing relationships.
Think of first-party data as a way to create an outline, not the whole story, about your target audiences—the main characters in your marketing. To flesh out the entire narrative about them, you must source, connect, and activate additional data.
The ability to unify different data sources with accuracy, scale, and privacy at the forefront sits at the core of Experian’s business. We unify household, individual, device, demographic, behavioral, and first-party signals, along with contextual and geographic data points, to build a reliable view of consumers, even when specific signals are missing. This clarity helps you personalize, target, activate, and measure with confidence.
By layering third-party data, contextual data, and geolocation data onto your first-party data foundation, your advertising strategies become stronger than if you used any of these sources as standalone solutions.
How do different types of third-party data add depth to audience profiles?
Third-party data expands understanding beyond known customers. If first-party data is the outline, third-party data helps with “character development”—a.k.a., addingdetailto your audience profiles. Good third-party marketing data complements first-party insights with demographic, behavioral, and transactional context, providing the missing puzzle pieces to complete the full customer profile. Filling in gaps in customer understanding helps youidentify, reach, and engage current and new customers more effectively. Third-party data allows brands to build loyalty with consumers by speaking to their interests and intent behind purchases.
Third-party data opens up new targeting tactics for advertisers, such as:
In addition to targeting, third-party data also remains critical to AI models, which must train on both structured and unstructured data. At Experian, our AI-powered technology interprets live bidstream data, device activity, content, and timing to optimize in the moment, ensuring campaigns deliver meaningful relevance, not just broader reach.
How are contextual and geographic approaches reshaping audience targeting?
Contextual and geographic approaches to targeting focus on environment and behavior rather than identifiers. Regulatory scrutiny, stricter and more fragmented compliance standards, and rising consumer expectations are transforming how marketers approach third-party data targeting. Evolving privacy laws and inconsistent identifiers across environments require new approaches that balance performance and privacy.
Contextual and geographic targeting help marketers reach relevant audiences while maintaining privacy.
What is data-informed contextual targeting?
Contextual targeting connects audience attributes to the content environments people choose. It helps determine the setting of your story—where your characters spend their time.
Solutions like Experian’s Contextually-Indexed Audiences harness advanced machine learning technology to combine contextual signals (a tried–and-true targeting tactic) with third-party targeting to ensure marketers reach their target audiences on the content they tend to consume, regardless of environment or location. What’s excellent about data-informed contextual targeting is that it moves beyond traditional keyword-based strategies to reach consumers on websites that over-index for visitors with the demographics, behaviors, or interests they are looking to target.
What is data-informed geotargeting?
Geotargeting uses shared location patterns to support relevance at scale. Geotargeting is another possibility for further developing the scene of your story.
People with similar behaviors and interests tend to live in similar areas, which is why so much effort goes into location planning for brick-and-mortar stores. Data-informed geotargeting combines geos with third-party data to make more informed media buys based on common behaviors within a geographic location.
We launched our Geo-Indexed audiences, which use advanced indexing technology to identify and reach consumers based on their geographic attributes. These audiences help marketers discover, segment, and craft messaging for consumers without relying on sensitive personal information, enabling them to reach target audiences while maintaining data privacy confidently.
What role does AI play in third-party data targeting?
AI acts like an automated editor of your book, refining and finding new ways to put valuable third-party audiences and data to work without relying on segments linked to known or disparate identifiers.
We’ve used AI and machine learning at Experian for decades to bring identity, insight, and generative intelligence together so brands and agencies can reach the right people, with relevance, respect, and simplicity.
Why does a balanced, integrated approach that combines first-party, third-party, contextual, and geo-targeting data matter?
The combined effects of integrating third-party, contextual, and geotargeting data (and the marketing tactics it underpins) with first-party data will drive your success.
Think of how any good author crafts a story. Regardless of whether it’s fiction or non-fiction, they draw on both first-person experience and external research and sources to develop their plot. No single data source tells the full story. Integration allows marketers to understand audiences more completely and act with confidence.
Pooling these inputs together moves you closer to your goal of understanding the whole story about your target customers. In fact, an almost even number of marketers plan to use contextual targeting (41%) and first-party data (40%) as their main targeting strategies, amid privacy laws and the loss of persistent advertisers.
| Primary data strategy | Percent of marketers that plan to use this data strategy |
| Contextual targeting | 41% |
| First-party data | 40% |
A brand with strong first-party insights can extend reach by layering in additional signals. For example, a nutrition brand that knows who purchases protein supplements can expand prospecting by combining:
By connecting these inputs, the brand can identify new health-conscious audiences with similar interests and behaviors. This approach supports privacy-safe targeting while improving engagement and performance.
How can marketers build an integrated data strategy in 2026?
An integrated data strategy reduces friction and supports scale. The right data partner offers a unified solution that helps unify data, activate audiences, and adapt as the ecosystem evolves. Here’s how:
Marketers who want to create and activate campaigns more efficiently and effectively in 2026 need an integrated approach that combines first-party, third-party, contextual, and geotargeting data. Streamlining data integration and activation positions brands and agencies for sustainable growth and stronger consumer relationships in a privacy-conscious marketplace.
Build your next chapter on a connected data foundation
As audience strategies evolve, connection and interoperability matter more than ever. Connect with our team to learn how Experian helps marketers unify data, identity, and activation across channels.
About the author
Scott Kozub
VP, Product Management, Experian
Scott Kozub is the Vice President of the Product Management team at Experian Marketing Services working across the entire product portfolio. He has over 20 years of product experience in the marketing and advertising space. He’s been with a few startups and spent many years at FICO and Oracle Data Cloud heavily focused on loyalty marketing and advertising technology.
FAQs
In 2026, CMOs should prioritize and invest in data and targeting strategies that combine first-party, third-party, contextual, and geographic data to drive growth, improve efficiency, and strengthen customer relationships.
First-party data is not sufficient on its own because first-party data defines known customers but limits reach and frequency. Growth depends on expanding beyond existing relationships. The ability to unify different data sources with accuracy, scale, and privacy at the forefront sits at the core of Experian’s business. We unify household, individual, device, demographic, behavioral, and first-party signals, along with contextual and geographic data points, to build a reliable view of consumers, even when specific signals are missing. This clarity helps you personalize, target, activate, and measure with confidence.
Third-party data expands understanding beyond known customers. Third-party data opens up new targeting tactics for advertisers, such as:
– Location: Where people live, work, or spend large amounts of time
– Health: A combination of demographics, behaviors, and health needs
– Purchases: Using previous purchase behavior to identify the right audiences
– Behavioral: How people engage with brands or how they use social media
– Interest: Delivering ads based on interests, hobbies, or online activities
– Psychographics: Shared characteristics like attitudes, lifestyles, and interests
– Demographic: Age, gender, education, income, and religion
In addition to targeting, third-party data also remains critical to AI models, which must train on both structured and unstructured data. At Experian, our AI-powered technology interprets live bidstream data, device activity, content, and timing to optimize in the moment, ensuring campaigns deliver meaningful relevance, not just broader reach.
Data-informed contextual targeting connects audience attributes to the content environments people choose. It helps determine the setting of your story—where your characters spend their time. Experian’s Contextually-Indexed Audiences harness advanced machine learning technology to combine contextual signals (a tried–and-true targeting tactic) with third-party targeting to ensure marketers reach their target audiences on the content they tend to consume, regardless of environment or location.
Data-informed geotargeting uses shared location patterns to support relevance at scale. Experian launched our Geo-Indexed audiences, which use advanced indexing technology to identify and reach consumers based on their geographic attributes. These audiences help marketers discover, segment, and craft messaging for consumers without relying on sensitive personal information, enabling them to reach target audiences while maintaining data privacy confidently.
In third-party data targeting, AI refines and finds new ways to put valuable third-party audiences and data to work without relying on segments linked to known or disparate identifiers. We’ve used AI and machine learning at Experian for decades to bring identity, insight, and generative intelligence together so brands and agencies can reach the right people, with relevance, respect, and simplicity.
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In this article…How data collaboration is evolving from 2023 to 2024How to create efficient data collaboration strategies We live in a data-driven world, and businesses need effective data collaboration strategies to remain successful. Before you determine your 2023 and 2024 data collaboration options, it’s essential to understand what data collaboration is. In short, it involves sharing and combining data from multiple sources to better understand a customer base and make informed marketing decisions. Read on to learn more about our three-step plan to create new data collaboration strategies, how it’s evolving, and what we do to ensure our solutions help maintain your company’s data privacy. How data collaboration is evolving from 2023 to 2024 Data collaboration strategies continually evolve thanks to changing industry dynamics and new technologies. As we move from 2023 to 2024, we’ll likely see collaboration extending outside businesses, meaning data can be shared with external partnerships in the form of a data ecosystem. A data ecosystem is a platform that combines numerous information points, including packages, algorithms, and cloud-computing services, to allow businesses to store, analyze, and use the data they’ve collected. To ensure you’re ready for 2024 data collaboration, you’ll need to take a forward-thinking approach toward new data strategies. How to create efficient data collaboration strategies Here are our three steps for efficient collaboration to make the most of 2023 data collaboration and prepare for 2024. Identify your collaboration goal What are you hoping to gain from data collaboration? Do you understand the audience you’re trying to target and what you want regarding outcomes? To measure your success, you should set short- and long-term goals surrounding data collaboration in 2023 and 2024. Maximize the value of your data One of the most important reasons to gather data is to discover in-depth insights into your audience and the effectiveness of your marketing efforts. You’ll be able to identify hidden patterns and pinpoint trends you may not have noticed before. With this information, you can make more strategic marketing decisions to stay competitive in your industry. Resolve digital identities Collaborating on data with trusted partners can help you gain a more complete view of your customers by building comprehensive digital profiles. Resolving digital identities can provide greater insight into online and offline behavior of individual consumers, allowing you to better connect with your target audience and boost brand loyalty. Find an alternative to third-party cookies Digital privacy regulations are getting more strict, which is why it’s so important to find more secure alternatives to third-party cookies. By collaborating on data, you can gather essential insights without relying on cookies. This means you’ll still get the information you want while complying with privacy regulations. Choose the right collaboration partner Before you choose a data collaboration partner, it’s essential to ensure their privacy standards align with yours. How do they collect data and use it ethically and responsibly? At Experian, we are dedicated to protecting consumers and delivering responsible and transparent data practices. We focus on five Global Data Principles — security, accuracy, fairness, transparency, and inclusion — to ensure we treat data carefully and respectfully while boosting economic growth and resilience in the marketing environment. When you partner with us for data collaboration, you can trust that your data is protected in a system built for 2023 data collaboration needs — both known and unknown — while still evolving for 2024 and beyond. Choose a secure environment for collaboration Data collaboration security is vital to safeguard your business and consumers’ information. You can make sure your new data collaboration options are protected in several ways. We’ve outlined three options below. Collaboration in clean rooms Clean rooms are secure, private environments where data is shared and analyzed without exposing the underlying raw data. This ensures that sensitive information remains protected and insights are discovered securely. Experian has vetted clean room partners if this is an option you prefer while still getting industry-leading identity resolution. Collaboration directly Collaborating directly with your partner can be a good option if you have robust security measures. Encryption, access controls, and regular audits are essential to maintain data security in direct collaborations. Collaboration with Experian We excel at meeting our clients where they are and accommodating their technical capabilities and how they manage their data. We offer a secure and compliant environment for data collaboration. Our data collaboration solutions are designed to protect your data while enabling deeper insights. At Experian, we understand the importance of data privacy, and our platform reflects our commitment to safeguarding your information. Enable deeper insights and activation with Experian’s data collaboration solution Data collaboration is crucial in today’s business world, and Experian’s solutions are designed to help you bring together your 2023 and 2024 data collaboration strategies securely and efficiently. With Experian, you can unlock deeper insights, resolve digital identities, and confidently navigate the evolving data privacy landscape. If you’re looking for the right partner to enhance data collaboration to drive growth and innovation in your business, you’ll find a secure environment and the right partner with Experian. Contact us today to get started. Contact us Latest posts
We are excited to announce that we’ve updated our CAPE data with 2020 Census data. This release updates estimates and projections from 2010 and replaces all previous CAPE data attributes. U.S. Census data offers a great opportunity for data enrichment The U.S. Census is conducted every 10 years to determine the number of people living in the U.S. in addition to collecting data on dozens of topics across 130+ surveys and programs. U.S. Census data is already broken out into regional groups and covers 100k+ different geographies: States, counties, places, tribal areas, zip codes, and congressional districts. Block groups are the smallest geographic area for which the Bureau of the Census collects and tabulates data. They are formed by streets, roads, railroads, streams, other bodies of water, and other visible physical and cultural features. What is CAPE? Census Area Projections & Estimates data (CAPE) data from Experian utilizes a proprietary methodology to make the data easy to action on for marketing use cases. Made from U.S Census and Experian consumer data, CAPE data sets are developed at the block group and zip code level and targetable at the household level. CAPE 2020 updates CAPE 2020 uses the 2020 Census data blended with other Experian data to update CAPE’s unique attributes for data enrichment and licensing. Multiple sources are used and data is delivered at a block group level or zip code. Experian provides unique CAPE attributes not available through other sources that provide Census data. These include our Ratio and Percentages attributes, Score Factors/Segments, and Mosaic. CAPE 2020 use cases Our CAPE 2020 data sets enable strategic marketing analysis and decision-making. You can use CAPE 2020 data to understand the differences in the markets you serve as they relate to core demographics, housing attributes, education, income, employment, spending, and more. You can do this to: Find populations that are not typically captured in standard demographics. Cross-reference Census demographics data with other behavioral and shopper data. Understand supply and demand for products sold. Get started with our CAPE 2020 data today If you are using Experian’s CAPE 2010 data, please work with your Experian representative to migrate to CAPE 2020. If you are interested in learning more about our CAPE data, get in touch with us today. Latest posts
Centralized data access is emerging as a key strategy for advertisers. In our next Ask the Expert segment, we explore this topic further and discuss the importance of data ownership and the concept of audience as an asset. We're joined by industry leaders, Andy Fisher, Head of Merkury Advanced TV at Merkle, and Chris Feo, Experian’s SVP of Sales & Partnerships who spotlight Merkle's commitment to centralized data access and how advertisers can use our combined solutions to navigate industry shifts while ensuring consumer privacy. Watch our Q&A to learn more about these topics and gain insights on how to stay ahead of industry changes. The concept of audience as an asset In order to gain actionable marketing insights about your audience, you need to identify consumers who are actively engaged with your brand and compare them against non-engaged consumers, or consumers engaged with rival brands. Audience ownership Audience ownership is a fundamental marketing concept where marketers build, define, create, and own their audience. This approach allows you to use your audiences as an asset and deliver a customized journey to the most promising prospects across multiple channels. With this strategy, you enhance marketing effectiveness and ensure ownership over your audience, no matter the platform or channel used. Merkle enables marketers to own and deploy said asset (audience) so that marketers can have direct control over their audience. With audience strategy, you can tie all elements together – amplify your marketing reach, while maintaining control of your audience. Merkle connects customer experiences with business results. Data ownership Data ownership refers to the control organizations have over data they generate, including marketing, sales, product, and customer data. This data is often scattered across multiple platforms, making it difficult to evaluate their effectiveness. Alternatively, owning this data, which is typically housed in a data warehouse, allows the creation of historical overviews, forecasting of customer trends, and cross-channel comparisons. With advertisers and publishers both claiming ownership over their respective data and wanting to control its access, there has been a growing interest in data clean rooms. Data clean rooms The growing interest in data clean rooms is largely due to marketers increasing preference to maintain ownership over their audience data. They provide a secure environment for controlled collaboration between advertisers and publishers while preserving the privacy of valuable data. Data clean rooms allow all parties to define their usage terms – who can access it, how it is used, and when it is used. The rise in the use of data clean rooms strengthens data privacy and creates opportunities for deeper customer insights, which leads to enhanced customer targeting. Data clean rooms unlock new data sets, aiding brands, publishers, and data providers in adapting to rapidly changing privacy requirements. Why is centralized data access important? Centralized data access is crucial for the effective organization and optimization of your advertising campaigns. It involves consolidating your data in one place, allowing for the identification of inconsistencies. Merkle’s Merkury platform The concept of centralized data is a key component of Merkle’s Merkury platform, an enterprise identity platform that empowers brands to own and control first-party identity at an individual level. A common use case involves marketers combining their first-party data with Merkury's data assets and marketplace data assets to build prospecting audiences. These are later published to various endpoints for activation. The Merkury platform covers three classes of data: Proprietary data set – Permissioned data set covering the entire United States, compiled from about 40 different vendors Marketplace data – Includes contributions from various vendors like Experian First-party data from marketers – Allows marketers to bring in their own data Merkury's identity platform empowers brands to own and control first-party identity at an individual level, unifying known and unknown customer and prospect records, site and app visits, and consumer data to a single, person ID. This makes Merkury the only enterprise identity platform that combines the accuracy and sustainability of client first-party data, quality personally identifiable information (PII) data, third-party data, cookie-less media, and technology platform connections in the market. End-to-end management of data Data ownership and management enables you to enhance the quality of your data, facilitate the exchange of information, and ensure privacy compliance. The Merkury platform provides a comprehensive, end-to-end solution for managing first-party data, all rooted in identity. Unlike data management platforms (DMPs) that are primarily built on cookies, the Merkury platform is constructed on a person ID, allowing it to operate effectively in a cookie-free environment. A broader perspective with people-based views The Merkury platform is unique because it contains data from almost every individual in the United States, providing a broader perspective compared to customer data platforms (CDPs) which only contain consumer data. The platform provides a view of the world in a people-based manner, but also offers the flexibility to toggle between person and household views. This enables you to turn data into actionable insights and makes it possible to target specific individuals within a household or consider the household as a whole. How Experian and Merkle work together Experian and Merkle have established a strong partnership that magnifies the capabilities of Merkle's Merkury platform. With Experian’s robust integration capabilities and extensive connectivity opportunities, customers can use this technology for seamless direct integrations, resulting in more effective onboarding to various channels, like digital and TV. "Experian's role in Merkury's data marketplace is essential as they are considered the gold standard for data. It significantly contributes to our connectivity through direct integrations and partnerships. Experian's presence in various platforms and technologies ensures easy connections and high match rates. Our partnership is very important to us."andy fisher, head of merkury advanced tv Through this partnership, Merkle can deliver unique, personalized digital customer experiences across multiple platforms and devices, highlighting their commitment to data-driven performance marketing. Watch the full Q&A Visit our Ask the Expert content hub to watch Andy and Chris's full conversation about data ownership, innovative strategies to empower you to overcome identity challenges, and navigating industry shifts while protecting consumer privacy. Tune into the full recording to gain insights into the captivating topics of artificial intelligence (AI), understanding how retail networks can amplify the value of media, and the growing influence of connected TV (CTV). Dive into the Q&A to gain rich insights that could greatly influence your strategies. Contact us today About our experts Andy Fisher, Head of Merkury Advanced TV As the Head of Merkury Advanced TV, Andy's primary responsibility is driving person-based marketing and big data adoption in all areas of Television including Linear, Addressable, Connected, Programmatic, and X-channel planning and Measurement. Andy has held several positions at Merkle including Chief Analytics Officer and he ran the Merkle data business. Prior to joining Merkle, Andy was the EVP, Global Data & Analytics Director at Starcom MediaVest Group where he led the SMG global analytics practice. In this role, he built and managed a team of 150 analytics professionals across 17 countries servicing many of the world’s largest advertisers. Prior to that role, Andy was Vice President and National Lead, Analytics at Razorfish, where he led the digital analytics practice and managed a team of modeling, survey, media data, and business intelligence experts. He and his team were responsible for some of the first innovations in multi-touchpoint attribution and joining online/offline data for many of the Fortune 100. Andy has also held leadership positions at Personify and IRI. Andy holds a BA in mathematics from UC Berkeley and an MA in statistics from Stanford. Chris Feo, SVP, Sales & Partnerships, 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! Latest posts