
Our next segment in our Ask the Expert series dives into the importance of data enrichment and its benefits across connected TV (CTV) advertising. Ask the Expert features a series of conversations with product experts where we focus on topics that matter the most in AdTech. In our latest segment, Natalia Irmin, Director of Strategic Data & Media Partnerships at a4 Advertising, joins us to chat with Experian’s SVP of Sales & Partnerships, Chris Feo.
a4 is an advanced advertising and data company that offers audience-based, multiscreen advertising solutions for local and national advertising businesses.
In their conversation, Natalia and Chris review:
- The benefits of data enrichment
- First-party data enrichment across advertising
- Data enrichment in CTV advertising
- How Experian and a4 work together
What is data enrichment?
Data enrichment enhances first-party data sets using third-party data sources. This process involves merging first-party data from internal sources with data gathered from other internal sources or from external third-party sources.
Examples of data that can be part of the enrichment process include:
- Demographic information
- Contextual signals
- Behavioral patterns
- Interests
- Purchase-intent
The more you know about your customers, the better equipped you are to reach them where they are with the right message. By enriching your data, you can enhance your messaging, provide personalized offers, and establish a loyal customer base.
First-party data enrichment across advertising
Businesses are transitioning from cookie-based third-party targeting to first-party data enrichment solutions as a result of cookie deprecation. When data enrichment is paired with internal first-party data, you can generate a more holistic customer profile.
a4 has a rich set of first-party data, based on the subscriptions to their services. a4 uses first-party data enrichment across advertising in two ways:
- Measure performance using their viewership data
- Advise their customers on where they should focus their advertising efforts based on the customer’s viewing behavior
a4 supports the enrichment of their customers’ first-party data so they can get the most out of their insights.With Experian’s privacy-first approach, a4 can continue to rely on their first-party data while protecting personally identifiable information (PII).
Data enrichment in CTV advertising
CTV advertising refers to digital advertising that appears through a streaming service during a viewer’s video content, like a movie or TV show. CTV ad campaigns allow businesses to personalize their digital marketing messages while the viewer watches content on various platforms. CTV offers a highly measurable opportunity to increase brand awareness.
Benefits of data enrichment in CTV advertising
Data enrichment provides three key benefits that can enhance targeting, personalization, and campaign effectiveness in CTV advertising.
Understand your target audience
By using enriched data such as demographic information, viewing behavior, and interests, you can gain deeper insights into your target audience, refine your targeting strategies, and create highly personalized ad experiences. Data enrichment also enables better measurement and optimization of ad campaigns, maximizing ROI.
Integrate enriched data with other marketing channels
You can integrate enriched data into CTV with data from other marketing channels. This enables the creation of comprehensive and cohesive marketing strategies that provide consistent messaging and enhance cross-channel targeting.
Enhance the value of ad inventory
Data enrichment can also benefit content publishers and broadcasters by enhancing the value of ad inventory and providing more targeted and effective advertising opportunities.
Enabling your marketers to target specific audiences will result in improved campaign performance. Through data enrichment, you can increase return on your ad spend and boost the value of your publisher’s ad inventory. a4 and Experian can help your business attract additional demand with audience enrichment. a4 uses Experian’s vast offering of audiences and combines it with Experian’s Graph. This data can later be used to activate across a4’s parent company, Altice’s owned and operated properties, as well as beyond Altice’s own footprint via premium publisher partners.
How Experian and a4 work together
a4 and Experian have a long-standing partnership that enables a4 to enhance its data. Through our Consumer View and Consumer Sync products, a4 can add audience attributes to its subscriber and viewer data to precisely pinpoint the audience that its clients are targeting. Experian helps a4 in building a comprehensive customer profile, which helps expand the customer base for a4’s advertising clients.
We form partnerships, like we do with Experian, to enhance our data further, so that we can combine the power of the viewership and exposure data for those other attributes that clients might need.” – Natalia Irmin, Director, Data & Strategic Partnerships, a4 Advertising
Through Experian’s audience attributes and Graph, a4 can assist advertisers in targeting audiences beyond their usual reach, creating a better user experience. a4 can personalize experiences and promotions to prioritize customers with a higher likelihood of making a purchase. By tailoring messages and promotions to individual customer preferences, businesses can improve their advertising efforts and deliver them through their preferred channels.
Watch the full Q&A
Visit our Ask the Expert content hub to watch Natalia and Chris’s full conversation about data enrichment and its benefits across the advertising world. In the Q&A, Natalia and Chris also share their thoughts on the importance of first-party data enrichment, addressability, and measurability in CTV advertising.
About our experts

Natalia Irmin, Director, Strategic Data & Media Partnerships, a4 Advertising
Natalia Irmin is the Director of Strategic Data & Media Partnerships for a4 Advertising. With over 10 years of experience working with data in the Defense, Finance, and Advertising industries, Natalia currently leads the a4 Strategic Partnerships team in the development of advanced data and media products in support of the organization’s media planning, buying, and advanced analytics business. Natalia holds an MBA from the NYU Stern School of Business and a Bachelor of Arts from Tel Aviv University in Israel.

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!
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Why an identity framework matters more than any single identifier The challenge facing marketers today isn’t a single identifier on a deprecation timeline. It’s the increasing fragmentation of signals and identifiers across browsers, devices, apps, and platforms. This shift introduces complexity into how audiences are reached and measured, as signals behave differently in every environment, and it becomes more complex to piece together a complete view of the consumer. Each environment contributes to its own set of visibility gaps, making identity less predictable and more uneven. The result is a patchwork of inconsistent identity signals rather than a single, predictable decline. While you can’t control how platforms evolve, you can control how you respond to fragmentation. The future won’t be defined by the loss of any single identifier, but by your ability to unify, interpret, and activate the many signals that remain. Marketers who adopt a flexible, identity framework will be best positioned to create consistency in an otherwise fragmented landscape. At Experian, we believe flexibility starts with intelligence. For decades, we’ve used AI and machine learning to help marketers understand people’s behavior more clearly, respect their privacy, and deliver messages that drive business outcomes. Our technology brings identity, insight, and intelligence together, so even as the number of signals grows and becomes more varied across environments, marketers can reach the right people with relevance, respect, and simplicity. This intelligence acts as the connective tissue across fragmented ecosystems, ensuring marketers can recognize and reach audiences consistently wherever they appear. What forces are driving fragmentation in identity and signals? Changes to traditional IDs: Since Apple introduced ATT, access to IDFA has become inconsistent across apps and devices. Google’s evolving Android privacy roadmap adds another layer of variability, fragmenting mobile addressability. Safari and Firefox have long restricted third-party cookies, while Chrome continues to support them for now. This creates different signal availability across browsers, contributing to an uneven and increasingly fragmented identity landscape on the open web. Shifts in signals: IPv4 to IPv6 migration introduces mismatched identity structures that complicate continuity across environments. Platform-driven fragmentation: Closed ecosystems and uneven adoption of evolving RTB standards (like OpenRTB 2.6 updates designed to support new identifiers and consent signals) create differences in which identifiers and consent signals are shared in the bidstream. At the same time, the rise of alternative or “universal” IDs—often developed by individual platforms, publishers, or technology companies—means that multiple ID types can appear within the same auction, each with its own structure, rules, and level of support. These differences reduce interoperability across platforms and contribute to a more fragmented activation landscape. Each change creates an identity silo. Together, they form an ecosystem defined by fragmentation rather than absence. Without an identity framework, these environments operate as disconnected identity islands. A multi-ID world requires a unified identity framework Alternative IDs play an important role, but they also expand the number of signals marketers must reconcile. Without a consistent identity layer, more IDs often mean more complexity—not more clarity. Common alternative IDs in use today: UID2: The Trade Desk’s UID 2.0, an iteration of their original Unified ID 1.0, which was still reliant on third-party cookies, creates persistent IDs with user-provided email addresses and phone numbers. ID5: This independent identity provider builds an identity infrastructure that powers addressable advertising across channels. It can create an ID based on both deterministic and probabilistic data. Hadron ID: Hadron ID is a unique, interoperable identity system (including first-party, audience-based, contextual, deterministic, and probabilistic) developed by Audigent, now part of Experian, to drive revenue for publishers by making their audience data and inventory actionable for media buyers. Industry reports suggest roughly one-third to two-fifths of open-auction traffic carries alternative IDs, sometimes multiple per request. Among Experian clients, adoption of alternative IDs rose 50% year over year, with a 30% increase in IDs resolved to individuals via our Digital Graph. Identity isn’t disappearing; it’s multiplying. A modern identity framework resolves these identifiers into a single, privacy-safe consumer view.

Year after year, CES signals where marketing is headed next. In 2026, the message was clear. Progress comes from connecting data, intelligence, and outcomes with discipline, not spectacle. Across AI, programmatic media, and measurement, the same priorities surfaced again and again. Under the bright lights of Las Vegas, three themes cut through, and each one pointed to a future where data, intelligence, and outcomes move in lockstep. Here are the three themes that defined CES 2026. 1. Agentic AI proved that it’s only as good as its data inputs AI was once again the star of the show. At CES 2026, marketers focused less on demos and more on proof that AI improves decisions, reduces friction, and drives outcomes. Every credible use case traced back to accurate, privacy-first data. What changed at CES was how that intelligence is being applied. Agentic AI systems designed to act autonomously are moving beyond insights and into execution. From media buying to optimization, these agents are increasingly expected to make decisions at speed and scale. That shift raises the stakes for data quality. When AI is operating campaigns, not just informing them, accuracy and privacy are non-negotiable. Without accurate, privacy compliant data, AI agents struggle to reflect real behavior or support responsible personalization. A reliable, privacy-first data foundation is what turns AI from an interesting experiment into an operational advantage. That advantage gets even stronger when it’s anchored in an identity graph that understands people and households across channels. When identity and intelligence move together, AI becomes more accurate, accountable, and effective at driving outcomes. In an AI first world, the strongest signal isn't scale. It's data quality. 2. Curation goes mainstream Curation is no longer experimental. At CES, it showed up as an mandated capability for buyers and sellers navigating fragmented signals and complex supply paths. Marketers want intentional media buys they can explain, defend, and repeat. AI is accelerating this shift. As AI systems take on more responsibility for planning, packaging, and optimization, curation provides the guardrails. It defines what “good” looks like (premium supply, trusted data, and clear performance goals), and allows AI to operate within those constraints driving the optimal outcomes for marketers. Rather than maximizing inventory access, curation prioritizes control, transparency, and performance. Buyers want premium supply aligned to specific goals. Sellers want clearer paths to demand. They can play the odds or own the outcome. When data leads, they own it. When curation is powered by high-fidelity audiences and a connected identity framework, it becomes even stronger. That’s what allows curated deals to deliver clarity, confidence, and repeatable performance. This shift reflects a broader move away from probability-based buying toward outcome ownership, where AI-driven systems are measured not on activity, but on results. 3. Activation and measurement finally shared the same stage Activation and measurement are now coming together around shared data and identity. CES 2026 marked a turning point where closing the loop felt achievable, not aspirational. Both the buy- and sell-sides face pressure to show that media investment drives outcomes. Agentic AI was a quiet driver of this optimism. As AI agents increasingly manage activation decisions in real time, marketers need measurement systems that can keep up. That requires a shared data and identity foundation. One that allows AI-driven actions to be evaluated against outcomes consistently, across channels and partners. "The companies leading in alternative data aren't just optimizing for growth, they're setting a new standard for inclusion, precision and responsible lending." – Ashley Knight, SVP of Product Management, Experian Achieving that requires a consistent identity spine that connects planning, activation, and outcomes across channels. And that spine is strongest when it’s built on accurate, privacy-first data and audiences that understand people and households. That connection allows marketers to move beyond proxy metrics and evaluate performance based on tangible results. When campaigns and measurement rely on the same data foundation, AI driven platforms can optimize toward outcomes such as new customers, account growth, or in-store activity, not just delivery metrics. That’s the connective layer that turns disconnected touchpoints into a measurable, outcomes-based system. The takeaway CES made one thing clear: agentic AI is moving marketing from intention to execution. But only for teams with the right foundation. AI is maturing, but only for teams with accurate, connected, privacy-first data that AI agents can act on responsibly. Curation is scaling, giving both humans and AI systems clearer paths to quality, control, and differentiation. Activation and measurement are aligning, allowing AI-driven decisions to be judged on outcomes, not assumptions. We’re building for that world today. One where agentic AI operates on a trusted data and identity foundation, curation defines the rules, and outcomes determine success. With the right foundation and the deep data inputs, you can move faster, reduce risk, and let intelligence (human and artificial) work together to deliver results that last long after the neon lights fade.
