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.
Latest posts
Over the last few months, Experian has released new syndicated audiences to most major platforms supporting retail and travel. In this blog post, we’ll highlight some of these new audiences and how they can be used with other data from Experian to build the perfect audience to reach your customers and prospects. What separates Experian's syndicated audiences Experian’s 2,400+ syndicated audiences are available directly on over 30 leading television, social, programmatic advertising platforms, and directly within Audigent for activation within private marketplaces (PMPs). Reach consumers based on who they are, where they live, and their household makeup. Experian ranked #1 in accuracy by Truthset for key demographic attributes. Access to unique audiences through Experian’s Partner Audiences available on Experian’s data marketplace, within Audigent for activation in PMPs and directly on platforms like DirectTV, Dish, Magnite, OpenAP, and The Trade Desk. Household Expenditure audiences We’ve created new predictive audiences to help retailers reach consumers across 35 categories likely to spend within that category. A few categories include Apparel, DIY, Health, and more. With the launch of these new audiences, we will retire our existing Household Consumer Expenditure, Online and Retail category audiences in the November Digital Master update. Who these audiences are for Our Household Expenditure audiences use data from multiple sources, providing brands with highly accurate purchase predictions and data that scales for digital execution. Household Expenditure audiences are an excellent solution for brands with new product lines or where targeting based on historical purchases lack signal brands seek. Building data from multiple data sources helps ensure high performance and accuracy and can illuminate trends in consumer shopping patterns. These trends can be used to help predict future shopping behaviors. How to refine our Household Expenditure audiences To refine your audience, you can combine this data with Experian’s demographic and household expenditure audiences to ensure you are reaching consumers. For example, suppose you’re an apparel brand launching a new line aimed toward women over the age of 40. In that case, you can use Experian’s demographic data to reach those women and layer in our household expenditure purchase predictor segment for women's apparel to reach their new target audience. Mobile Location audiences We’ve expanded our location database to include more locations and points of interest. With this new data, we could strengthen our existing mobile location audiences to broaden the reach, improve accuracy, and increase performance. We’ve created 11 new mobile location audiences with our new dataset that supports the retail and travel verticals. These new audiences include new shopping behaviors, including high-income and high-end shoppers and travel and entertainment behaviors, including visiting sporting arenas like MLB, NBA, NFL, and university stadiums. Who these audiences are for These audiences are for brands that want to reach consumers based on their location behaviors. Often valid for retail, travel, and entertainment brands, Mobile Location audiences provide brands with highly accurate data that shows previous intent and interest in critical locations. How to refine our Mobile Location audiences To refine your audience, you can combine your Mobile Location audience with Lifestyle and Interest data. For example, if you are creating an advertising campaign for a hotel near a university stadium for the largest game in the season, you could combine university stadium visitors with sports enthusiasts and in-market for travel to find consumers most likely to be interested in your campaign and staying at the hotel. Purchase-Based Transaction audiences For use cases where predictive audiences aren’t the best fit to reach the right consumer, such as targeting consumer’s historical purchases, we’ve created new purchase-based transaction audiences that utilize opt-in consumer transaction data across 29 retail categories, including apparel, home, lifestyle, health, food and beverage, and more. Who these audiences are for These audiences are a perfect fit for brands trying to reach consumers based on previous purchases. These audiences can be broken out by their spending patterns – frequency of purchase and high spenders – and their response to advertising, including direct mail, email, inserts, and digital. How to refine our Purchase-Based Transaction audiences Combine these new audiences with Mosaic to fine-tune your audience based on their purchasing and lifestyle patterns. Suppose you are a brand with a new line of home décor products launching and will utilize influencers to endorse your product line. In that case, you can use Experian’s purchase-based transaction audiences for high spenders in home décor and layer our Mosaic audience Influenced by Influencers to find consumers who are most likely to purchase and trust an influencer. We can help you discover and activate your perfect audience Our audiences are available in most major data and execution platforms. Visit our partner page for more information. Don’t see our audiences on your platform of choice? We can help you build and activate an Experian audience on the platform of your choice. Contact us Latest posts
The AdTech industry is buzzing with discussions about cookie deprecation and effective strategies to tackle it. One of the commonly suggested solutions is the utilization of clean rooms alongside responsibly sourced first-party data. Above all else, the industry recognizes the importance of respecting consumer data and complying with all privacy laws. Additionally, the industry acknowledges the need for a change in our historical practices. This shift benefits everyone involved, as consumer data is more secure than ever. Tremendous investments have been made to ensure the utmost security of consumer information. Clean rooms are one of the tools that enable companies to use data securely, ensuring the content that you see is as relevant as possible. Two ways the AdTech industry is addressing cookie deprecation The days of sending data directly to partners for usage or for using only third-party data for marketing efforts are gone. Now, the emphasis is on responsibly collecting first-party data and using clean rooms to enrich first-party data to enhance marketing efforts. First-party data The industry is starting to lean into first-party data gained through transparent means. This valuable information provides organizations with deeper insights into their customers, allowing for more personalized and effective interactions. By embracing the power of first-party data, either on its own or enriched via partner collaboration, you can cultivate stronger relationships, build trust, and deliver tailored experiences that resonate with your customers on a deeper level. Clean rooms Many data lakes and warehouses offer this service, ensuring their clients can not only store their data with them but can connect it with other partners in a secure environment and extract more information through the combined data sets versus their data on its own. Brands and their partners recognize that they need to work together, and a clean room provides a secure environment to share their first-party data without exposing their sensitive data to their partner. So, while we're losing third-party cookies, brands and partners can still get value from first-party data by using a clean room to generate audience insights, segmentation strategies, personalized experiences and offers, media plans, and measurement and attribution. Three ways data clean rooms can improve Data clean rooms are a great way to facilitate data collaboration while ensuring sensitive data is not exposed. Data clean rooms are not yet easy to use nor are they inexpensive. They require investment, both financially and resource allocation-wise, and you are not guaranteed to yield great match results. Let’s dive into three areas for data clean room improvement. High cost According to the IAB's State of Data 2023, nearly two-thirds of data clean room users spent at least $200K on the technology in 2022. In addition, one-third of data clean room users expect the price of data clean rooms to rise in 2023. The high cost of this solution can make it inaccessible to smaller companies in the advertising space. Resource intensive Nearly half of the companies using data clean rooms have a team of six or more dedicated to the technology, according to the IAB’s State of Data 2023, while nearly a third of companies using data clean rooms have 11 or more employees focused on the technology. Data clean rooms are not turnkey solutions. Inefficient matching Even if companies are using clean rooms does not mean that they are automatically going to achieve great success. Identity fragmentation, data hygiene, and differing identifiers can suppress client match rates in clean rooms, leading to significant investment and a lackluster output. How to get the most return on your clean room investment The finish line for data collaboration in clean rooms is not just having a relationship with a clean room. Instead, you should incorporate an identity resolution solution in your clean room. By adding an identity solution to your clean room, you can: Resolve and match all your identity data, regardless of the identity data that you or your partner have, giving you a larger data foundation to analyze. Generate more valuable insights and information, leading to a better experience for your customers. Join data sets to create smarter activation and targeting strategies and produce more holistic measurement. Experian can help you get started with identity resolution and data clean rooms If you are investing in data clean rooms, that means you are committed to the best in data practices. Experian recommends going the extra step and that you also invest in finding an identity resolution solution. By doing this, you can see better match rates. Experian offers this capability and has existing relationships with three clean room partners, Amazon Web Services, InfoSum, and Snowflake. In addition to collaborating in clean rooms, we offer collaboration in two other secure environments. Contact us today to discuss how we enable identity resolution in clean rooms or to chat about our other collaboration capabilities. Get in touch Latest posts
Ongoing signal loss is driving marketers, agencies, and platforms to turn to supply-side advertising. By using first-party data from publishers and platforms, supply-side advertising has the potential to deliver high-quality audience and context for more effective ad targeting. The supply-side refers to the publishers and platforms that sell advertising inventory. These companies have access to first-party data about their users, which can be used to target ads more effectively. By tapping into supply-side advertising, you can overcome the challenges of signal loss and target ads more effectively. To shed light on this topic, we hosted a panel discussion at Cannes, featuring industry leaders from Audigent, Captify, Newsweek, Pubmatic, Truthset, and Experian. In this blog post, we'll explore how partnerships between supply-side channels and publishers are working to enhance advertising opportunities while balancing the need for transparency and control in programmatic ad buying. Shift toward supply-side advertising Traditionally, the demand-side dominated the programmatic media buying chain due to an abundance of supply. However, with the emergence of finite data and its interpretation, collaboration between supply-side technology companies and publishers is required to redefine these economics. It's no longer sufficient for the demand-side to blindly negotiate prices based on limited knowledge. Marketers can still define their target audience, but effective communication is key. This presents an opportunity for premium journalistic outlets to guide the industry's understanding of how data from the supply-side impacts media buying economics in the future. "Supply-side technology partnerships with publishers are now in a position to shape the economics of programmatic media buying as there is a finite amount of data. It’s crucial for supply-side technology companies to collaborate with publishers to shape these new economics. This presents an opportunity for premium journalistic outlets to provide guidance on how data from the supply-side can affect the future of media buying." matthew papa, svp, business & corporate development, captify Democratizing data from the supply-side Cookies haven't brought significant benefits to premium publishers. They mainly serve to retarget users from sites like The Wall Street Journal to advertising sites. This approach primarily serves the purpose of generating revenue. The elimination of third-party cookies presents an opportunity for premium publishers to shift this dynamic. By using their knowledge of first-party audiences, and using identifiers like Experian's LUID, publishers can own and understand their audience data, which can then be modeled. Here’s how publishers can win Establishing a connection with consumers and emphasizing the value exchange is essential to building trust. Determining what incentives and benefits consumers find meaningful will be crucial in gaining their opt-in. With consumers The Apple tracking transparency initiative, specifically the deprecation of IDFA signals, had significant implications for mobile app developers. Overnight, opt-in rates plummeted, causing a drastic decline in iOS ad monetization. To combat this, developers focused on demonstrating the value exchange to consumers—better ad experiences and personalized content. By articulating the benefits over a couple of years, opt-in rates increased from 10-15% to 30-40%. The key takeaway is the need to effectively communicate the value exchange to consumers. With partners Trust plays a crucial role in planning your first-party data strategy. Publishers, advertisers, and data partners highly value their proprietary data. However, there are concerns about how it's used, mishandled, or leaked in the ecosystem. Building trust between partners is essential. It's important to work with trustworthy partners who are agnostic, committed to innovative solutions, and globally oriented. These partners can help navigate the complexities of laws and regulations. Choosing the right partners is crucial in a world where first-party data is a key asset. "Power is shifting toward brands that have strong relationships with customers and possess first-party data. As the ownership of customer data becomes more important, it is crucial to establish a first-party data strategy to better serve customers and adapt to changing market dynamics."chip russo, president, truthset Balance probabilistic and deterministic data Focus on building trust with consumers and collaborating with reliable companies to share data. However, it's important to remember that achieving a 100% opt-in rate is unlikely. The cookie, which has become omnipresent, requires us to shift our strategic thinking. We need to consider both deterministic and probabilistic approaches instead of viewing them as mutually exclusive. The landscape will be fragmented, with some consumers opting in and others not. "Probabilistic and predictive audience data holds immense potential. With the power of AI, we can expect enhanced performance and efficacy in media campaigns. At Audigent, we firmly believe that this data will outperform deterministic data, making it an integral part of our strategy." drew stein, ceo, audigent Premium content Trust plays a crucial role in leading to premium content. By placing trust in the best media brands, data, and technology partners, we can expect to see improvements in media, journalism, and advertising. This shift may have a direct impact on the long tail of free natural resources, making it more challenging for them to thrive. However, this change is ultimately beneficial since it promotes higher-quality media experiences overall. "The homepage surface is making a comeback in the publishing industry, proving its value in establishing a direct connection with readers. While we acknowledge the importance of technology partnerships for addressability and identity, our core competency as a publisher remains outstanding journalism that captures and engages great audiences." kevin gentzel, cco, newsweek Watch our Cannes panel for more on supply-side advertising We hosted a panel in Cannes that covered supply-side advertising. Check out the full recording below to hear what leaders from Audigent, Captify, Newsweek, Pubmatic, Truthset, and Experian had to say. Watch now Check out more Cannes content: Our key takeaways from Cannes Lions 2023 Insights from a first-time attendee Four new marketing strategies for 2023 Exploring the opportunities in streaming TV advertising The future of identity in cookieless advertising Follow us on LinkedIn or sign up for our email newsletter for more informative content on the latest industry insights and data-driven marketing. Contact us today Latest posts