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
For the past several years ad-tech defined the value of identity at the individual level; made possible by the evolution of data, technology and machine-learning. But, earlier this year COVID-19 set in motion many shifts in consumer digital behavior. The more we’ve been working and learning from home, using devices that are shared amongst an entire household, the more apparent it is that marketers need to shift their strategies to align with these changes. Did you know the average household owns eleven or more connected devices? And the longer we’ve been at home, the more these devices are shared by multiple individuals. If you’re looking for a few simple ways to evolve from an individual focused strategy to a household strategy, here’s a good place to start: Audience segmentation Traditionally, audiences are built with a narrow focus on a single user, and what known attributes about that individual or their brand engagement can be leveraged for a targeting strategy. Now that screens are being shared between multiple users in a home, how can you be sure you’re identifying them correctly, and thus, segmenting them in the right buckets for targeting? The key lies in the ability to connect those points through identity resolution. Using ad exposure from household level devices, followed by a second engagement from an individual within that household can indicate a user is a better candidate for purchase or conversion than others. So before you build audiences for targeting, you can qualify them at the household level for segmentation with more confidence. Example: An auto advertiser uses audience segments from a third party provider such as ‘auto intenders’ to target individuals with new pricing offers. They would continue retargeting these users, unaware that some are connected in the same household, and thus are probably not all in the market to actually get a new car. By bucketing users that share a common household device within this third party segment, they can hone in on which individuals are actually in-market for a car and evolve their strategy to be more effective. Targeting Retargeting, frequency capping and sequential messaging have always been meant for an individual user — the more they’re exposed to your brand in a personalized way, the more likely they are to take the desired action. But, have you considered that multiple users could have a shared initial exposure to your brand? Today, you can target a household of potential consumers on a shared device like a CTV, and employ those retargeting strategies based on that common initial exposure. Starting at the household level, means you can compare movement through the funnel between different individuals in that household, and tailor your targeting accordingly. Perhaps you realize only one person in that household will convert and you tailor messaging to them more frequently, while confidently suppressing the other individuals. Example: a CPG brand uses OTT advertising, but doesn’t incorporate it within their sequential strategy, because they consider it just a ‘brand awareness’ opportunity. By using OTT more strategically as a household level engagement, it can reveal which individuals within a household are more favorable towards a brand further down the funnel. So, you can spend impressions targeting those users, rather than wasting impressions on multiple individuals within the household. Measurement Measurement and attribution are imperative to understanding the path to purchase and making strategies more efficient over time. Often that efficiency involves adding or removing devices and channels from a targeting strategy based on their contribution to an action or conversion by an individual. This year we’re seeing addressable TV devices explode in use, which are shared at the household level. Even desktop computers are being used by more people in the home due to COVID-19. So, assuming a linear path of attribution by an individual is missing the full picture. Identity resolution can help you understand where messaging was more effective for some users in the household than others, and leverage that insight to continue more effective strategies in the future. Example: Without a household view, a direct-to-consumer brand would assume all interactions from one device would be coming from a single individual, and that could create a higher cost-per analysis. By incorporating the household level devices into attribution models, they can find efficiencies between touch points of multiple users, and learn how those split off into individual paths to conversion. Not only can this DTC create a more effective model, but they can use that model to create cost efficiencies in the future. Contact us today
With the long-term effects to the economy unknown, many consumers are feeling the financial impact, while others are looking for opportunities, resulting in a transformational shift in spending. Some brands are experiencing decreased or paused marketing budgets, and you may be trepidatious about making the right decisions in your efforts to grow share of wallet. Recent events have been an impetus for change and we’re seeing brands make modifications to traditional marketing strategies. Some are developing innovative technologies and utilizing new sources of data and analytics. As we look at how these changes impact marketing results, we see the gap grow between those brands who are equipped to pivot and implement new strategies quickly, versus those who are not. So what steps can your organization implement now to make the smartest choices for both your customers and your business to secure more share of wallet? Here are four ideas to accelerate the success of your next financial marketing campaign: 1. Meet your customers wherever they are: Digital-first strategies have never been more relevant than they are right now. While consumers have fully embraced online engagement, marketers are even more focused on reaching high-value segments in the channels they utilize. By using an informed, data-driven strategy that includes preferred marketing communication channels and decision-making styles, engagement increases across those channels your target audience frequents the most. For example, are they heavy social media users? Do they prefer streaming TV? Or do they tend to rely on financial advice vs. performing their own research? To drive take rates, your audience must be exposed to a tailored message, in the right channel, and possibly multiple times. 2. Use messaging that resonates: As consumers refocus priorities, their expectations of brands with whom they do business are ever-increasing. Reflecting an understanding of the current needs and interests of your customers and prospects is an undertone that can only help strengthen their view of your brand. Consumer behavior has changed and is unlikely to revert to what was, so you want to be relevant, but you also do not want to be seen as ‘tone deaf’. As a result, consider revising your segmentation strategy to leverage predictive insights, such as household economic indicators, financial behaviors, lifestyle propensities and interests to help shape your message into one that truly makes an impact. 3. Prove the worth of your campaign: New consumer journeys are being formulated and showing ROI is imperative as your marketing budget is scrutinized. Having the right industry-relevant metrics and reports to analyze and share with leadership are key. Demonstrate that your campaigns are contributing to bottom-line success—and justify future campaigns—by using data-driven measurement insights collected across multiple reads and countless touchpoints. Marketing budgets are being scrutinized now more than ever, so showing ROI is critical. Having the right metrics and reports to analyze and share with leadership are key. 4. Follow government regulations—leverage Fair Lending-friendly audiences: Whether you’re cross-selling or prospecting, now is the time to identify the right audiences with rich data insights to not only execute impactful campaigns but adhere to government regulations that protect consumers and your organization. Trusting that the data you are activating follows Fair Lending Laws, including the Equal Credit Opportunity Act (“ECOA”) and the Fair Housing Act (“FHA”) is crucial. The Federal ECOA prohibits creditors from discriminating against credit applicants on the basis of several prohibited factors. Developing people-based segments that are not derived using these factors positions you to follow these regulations. Check out our previous blog post about Fair Lending-friendly audiences here. As you transition to new operating models, access to current and accurate consumer data can provide confidence in campaign potential, help you avoid business risk, enable you to respond to market changes and make better decisions. Experian can help you implement these strategies and put your brand unique position for growth. From start to finish, we provide the marketing solutions you need to plan, build and execute successful, Fair Lending-friendly campaigns to cross-sell to existing customers and acquire new customers. *Experian Fair Lending-friendly audiences do not constitute legal advice or otherwise assure compliance with the FHA, ECOA, or any other applicable laws. It’s recommended to seek legal advice with respect to the use of data in connection with lending decisions or application and compliance with applicable laws. Contact us today
Cross-device matching and pixel-based foot traffic attribution reporting empower digital marketers with greater control of location-based campaigns.RALEIGH, N.C. (PRWEB) AUGUST 04, 2020 Tapad, part of Experian a global leader in digital identity resolution, and Reveal Mobile, a leader in location-based marketing, today announced a collaboration that combines Tapad's digital cross-device matching technology and pixel-based attribution features with Reveal Mobile’s VISIT Local, the software that hundreds of digital agencies and brands use for location-based analytics. The partnership is designed to drive improved performance by optimizing ad targeting and messaging for location-based campaigns. Powered by Tapad’s privacy-safe cross device matching, marketers using VISIT Local to power location-based campaigns can enhance how they reach shoppers. When one member of a household shops for groceries, clothes, household goods or any other consumer item, a conversation between multiple members of the household typically takes place beforehand. With cross device matching, marketers can reach everyone who has influence over what to buy and where to buy it. VISIT Local users can expand location-based services with a single click to include devices that share the same household, including targeting across multiple devices owned by the same user, allowing advertisers to maximize messaging and increase their share of wallet among consumers. “VISIT Local has always given our customers access to high-intent location-based audiences. With the addition of cross device matching from Tapad, advertisers can boost audience sizes up to 300 percent while maintaining full confidence in quality and relevance,” says Brian Handly, CEO of Reveal Mobile. “VISIT Local users can now apply multiple criteria and attributes to a single location-based audience, giving them the advanced control and transparency they need.” As reliable attribution becomes increasingly complex for marketers and ad buyers who need to prove value, the addition of Tapad’s pixel-based foot traffic attribution to VISIT Local enables the measurement of actual campaign effectiveness by tying ad views to in-store foot traffic. This new feature, which will be available in VISIT Local this fall, lets Reveal Mobile customers understand who visited a retail location as a result of being served an ad, providing a more accurate view into return on ad spend during and after advertising campaigns. “Tapad’s goal is to empower marketers with digital advertising efficiencies at scale across devices,” says Mark Connon, COO of Tapad. “With cross device matching and pixel-based foot traffic attribution, marketers using VISIT Local can better address the consumer’s preferences and habits, and deliver them consistently actionable information on user behavior. These capabilities advance location-based advertising in ways marketers need and want.” In addition to these new features, VISIT Local’s location-based audience builder now enables marketers to create custom audiences made up of people who have visited different places on different dates. This gives VISIT Local users the ability to segment and create the most highly targeted audiences possible. For example, a marketer who wants to advertise for a chain of restaurants can easily target visitors of different competitors in different cities. Or a marketer who wants to advertise vacation destinations can target people who have been to various resorts at different times of year. Or a marketer who wants to advertise the release of new music can target people who have been to concert venues in different cities on different dates. “Many of our customers need to create highly custom audiences so they can run experiments, test messaging, and run increasingly competitive campaigns,” says Handly. “Everyone who uses VISIT Local can now apply multiple criteria and attributes to a single location-based audience, giving them the advanced control and transparency they need.”To learn more about Tapad’s digital identity resolution products, visit our identity solution page. To learn more about Reveal Mobile’s location-based marketing offerings, visit http://www.revealmobile.com. About TapadTapad, Inc. is a global leader in digital identity resolution. The Tapad Graph, and its related solutions, provide a transparent, privacy-safe approach connecting brands to consumers through their devices globally. Our one-of-a-kind Graph Select offering enables marketers the flexibility and freedom of choice to correlate devices to varied objectives, driving campaign effectiveness and business results. Tapad is recognized across the industry for its product innovation, workplace culture and talent, and has earned numerous awards including One World Identity's 2019 Top 100 Influencers in Identity Award. Headquartered in New York, Tapad also has offices in Chicago, London, Oslo, Singapore and Tokyo. About Reveal MobileReveal Mobile is a leader in location-based marketing, analytics, audiences, and attribution. Creator of VISIT Local, VISIT Match and VISIT Data, the company’s products help digital agencies, brands and retailers of any size leverage location data to understand and reach the right audiences. Reveal Mobile is CCPA compliant and a member of the Network Advertising Initiative, which conducts an annual privacy certification. The company is based in Raleigh, NC. For more information, visit https://revealmobile.com. Contact us today