At A Glance
AdTech can feel overwhelming with all its jargon, but we're breaking it down café-style. From first-party data and identity resolution to clean rooms and ID-free targeting, this guide breaks down the essential terms marketers need to know.In this article…
If you’ve ever sat in a meeting and heard an AdTech term you didn’t understand, you’re not alone. The industry evolves as quickly as a café turns over tables on a busy weekend. Even seasoned regulars can get tripped up by the jargon.
So instead of scratching your head over the “menu,” let’s walk through some of the most common terms: served café-style.
The ingredients: The many flavors of first-party data
Every meal starts with ingredients, and in AdTech, those ingredients are data. First-party data is not just one thing: it’s more like everything your favorite neighborhood café knows about you.
First-party data
The café knows your coffee preferences because you’ve told them directly; whether by ordering at the counter, calling in, or placing an order online. This is information you’ve willingly provided through your interactions, and it belongs only to that café.
First-party cookies
The barista writes down your preferences in a notebook behind the counter, so next time you walk in, they don’t have to ask. First-party cookies remember details to make your experience smoother, but only for that café.
Authenticated identity
A loyalty app that connects online orders to in-person visits. By logging in, you’re saying, “Yes, it’s really me.” Authenticated identity is proof that the customer isn’t just a face in line, but someone with a verified profile.
Persistent identity
Recognizing you whether you order through the app or in person. Persistent identity enables the ability to keep track of someone across different touchpoints, consistently, without confusing them with someone else.
Permissioned data
Agreeing to join the loyalty program and get emails. Permissioned data is a connection to the customer that the customer proactively shared with the café by signing up for their loyalty program or email newsletter.
Each piece comes from direct interactions, stored and used in different ways. That’s what makes first-party data nuanced. The saga of third-party cookie deprecation and changing privacy regulations makes it important to understand which types of data you can collect and use for marketing purposes.
And once you have those ingredients, the next step is making sure you recognize how they fit together, so you can see each customer clearly. That’s where identity resolution comes in.
The recipe: Bringing the ingredients together with identity resolution
At the café, identity resolution is what helps the staff recognize you as the same customer across every interaction. Without it, they might think you’re two different people; one who always orders breakfast and another who sometimes picks up pastries to go.
Matching
The café has a loyalty program, and the pet bakery next door has one too. When they match records across their two data sets, they realize “M. Jones” from the café is the same person as “Michelle Jones” from the bakery. That connection means they can activate a joint promotion, like free coffee with a dog treat, without either business handing over their full customer lists. In marketing, matching works the same way, linking records across data sets for activation so campaigns reach the right people.
Deduplication
Collapses duplicate profiles into a single, clean record, so you don’t get two birthday coupons, even though that would be nice to get.
That’s what Experian does at scale: we connect billions of IDs in a privacy-safe way, so you can get an accurate picture of your audience.
And once you can recognize your customers across touchpoints, the next challenge is collaborating across systems and partners for deeper insights. That’s where the behind-the-counter processes come in.
Behind the counter: Crosswalks and clean rooms
At a café, these terms are like the behind-the-counter processes that keep everything running smoothly. They may sound technical, but they all serve the same purpose: helping data collaborate across different sources, while keeping sensitive information safe. The goal is a better “meal” for the customer, deeper insights, better targeting, and more personalized campaigns. Here’s how they work.
Crosswalks
The café partners with the pet bakery next door. They both serve a lot of the same people, but they track them differently. With a crosswalk, they can use a shared key to recognize the same customer across both businesses, so you get a coffee refill, and your dog gets a treat, without either one handing over their full customer list. A crosswalk is the shared system that lets both know it is really you, without swapping personal details. It’s the bridge connecting two silos of data.
Clean rooms
The café and the pet bakery want to learn more about their shared customers, like whether dog owners are more likely to stop by for brunch on weekends. Instead of swapping their full records, they bring their data into another café’s private back room, a clean room, where they can compare trends safely and privately. Both get useful insights, while customer details stay protected. That’s a clean room: secure collaboration without exposing sensitive data.
Of course, sharing and protecting data is only part of the picture. The real test comes when you need to serve customers in new ways, especially as the industry moves beyond cookies.
Serving customers in new ways: Cookie-free to ID-free
Targeting has evolved beyond cookies, just like cafés no longer rely only on notebooks to remember regulars.
ID-free targeting
The café looks at ordering patterns, like cappuccinos selling on Mondays and croissants on Fridays, without tracking who’s ordering what. Instead of focusing on who the customer is, the café tailors choices based on the context of the situation, like time of day or day of the week. This is like contextual targeting, serving ads based on the environment or behavior in the moment, rather than on personal identity.
ID-agnostic targeting
The café realizes customers show up in all sorts of ways: walk in, online ordering, delivery. Each channel has its own “ID,” a name on the app, a credit card, or a loyalty profile. ID-agnostic targeting means no matter how you order, the café can still serve you without being locked into one system.
Just like cafés no longer rely only on notebooks to keep track of regulars, marketers no longer have to depend solely on cookies. Today, there are multiple paths, cookie-free, ID-free, and ID-agnostic, that can all help deliver better, more relevant experiences.
But even with new ways to reach people, one big question remains: how do you know if it’s actually working? That’s where measurement and outcomes come into play.
Counting tables vs. counting sales
At the café, measurement and outcomes aren’t the same.
Measurement
Tables filled, cups poured, specials ordered.
Outcomes
What it all means: higher revenue, more loyalty sign-ups, or increased sales from a new promotion.
Both matter. Measurement shows whether the café is running smoothly, but outcomes prove whether the promotions and strategies are truly paying off. Together, they help connect day-to-day activity to long-term success.
All of this brings us back to the bigger picture: understanding the menu well enough to enjoy the meal.
From menu to meal
In AdTech, there will always be new terms coming onto the menu. What matters most is understanding them well enough to know how they help you reach your business goals. Just like at the café, asking a question about the specials isn’t foolish. It’s how you make sure you get exactly what you want. The more we, as an industry, understand the “ingredients” of data and identity, the better we can cook up new solutions that serve both brands and consumers. After all, the goal isn’t just to talk about the menu, it’s to enjoy the meal.
At Experian, we help brands turn that menu into action. From identity resolution to privacy-safe data collaboration, our solutions make it easier to connect with audiences, activate campaigns, and measure real outcomes.
If you’re ready to move from decoding the jargon to delivering better customer experiences, we’re here to help
About the author
Brandon Alford
Group Product Manager, Experian
Brandon Alford is a seasoned professional in the AdTech ecosystem with a focus on identity, audience, measurement, and privacy-forward solutions. He has spent his career helping advertisers and publishers navigate the complexities of digital advertising and privacy, bringing a practical and forward-looking perspective to industry challenges and innovation.
AdTech jargon FAQs
First-party data is information a customer shares directly with a brand, like purchase history, preferences, or sign-ups. It’s the most valuable and privacy-safe data marketers can use to build personalized campaigns.
Identity resolution ensures a brand can recognize the same customer across different touchpoints. Matching links records across data sets (e.g., between partners) so campaigns reach the right people without exposing full customer lists.
A crosswalk bridges two data systems with a shared key to recognize the same customer, while a clean room allows partners to analyze data together securely without exposing sensitive details.
Cookie-free and ID-free targeting shift focus away from tracking individuals, instead tailoring ads based on context (like time of day or content being viewed) or allowing flexibility across multiple IDs.
Measurement tracks activity (like clicks or visits), while outcomes prove business impact (like sales, loyalty, or revenue). Both are essential, but outcomes show whether strategies are truly effective.
Experian provides tools for identity resolution, privacy-safe data collaboration, and campaign measurement, helping marketers move from understanding the “menu” of AdTech terms to achieving real results.
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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
Bridging disparate data in a fragmented world In today's world, consumers engage with brands across multiple platforms, including social media, online marketplaces, in-store experiences, and customer service touchpoints. However, the main challenge for marketers and advertisers is the fragmentation of customer data across these different channels. Each platform generates its own set of data, which is stored in different databases and formats. Integrating these various data sources to create a unified view of the customer is a complex task involving technology and understanding customer behavior across different digital and physical channels. Businesses must link these data fragments to avoid creating a disconnected customer experience. For example, a person may browse products on a mobile app, ask questions through a customer service chat, and eventually purchase in an online marketplace. 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With this strategic approach, businesses can achieve their objectives regulatory-compliant. The consumer perspective: Why consistency matters Data fragmentation can lead to inconsistent experiences for consumers, which can be frustrating and erode brand trust. For instance, imagine receiving a promotional email for a product you already purchased through an app or being targeted for a product you decided against. Consumers are increasingly tech-savvy and demand a seamless, integrated experience regardless of how they interact with a brand. They want to feel valued and recognized at every touchpoint and don't care about the complexities of data analytics. As a result, brands face significant pressure to get identity resolution right. Data security and privacy: A Fort Knox for your data AWS Clean Rooms empowers their customers to establish a secure data clean room within minutes, facilitating collaboration with any other entity within AWS. 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Start collaborating About the authors Kalyani Koppisetti, Principal Partner Solution Architect, AWS Kalyani Koppisetti is a technology leader with over 25 years of experience in the Financial Services Industry. In her current role at AWS, Kalyani advises financial services partners on best-practice cloud architecture. Kalyani works closely with internal and external stakeholders to identify industry technical trends, develop strategies, and execute them to help Financial Services Industry partners build innovative solutions and services on AWS. Technical and Solution interests include Cloud Computing, Software-as-a-Service, Artificial Intelligence, Big Data, Storage Virtualization and Data Protection. Matt Miller, Business Development Principal, AWS In his role as Business Development Principal at AWS, Matt drives customer and partner adoption for the AWS Clean Rooms service specializing in advertising and marketing industry use cases. Matt believes in the primacy of privacy-enhanced data collaboration and interoperability underpinning data-driven marketing imperatives from customer experience to addressable advertising. Prior to AWS, Matt led strategy and go-to-market efforts for ad technologies, large agencies, and consumer data products purpose-built to inform smarter marketing and deliver better customer experiences. Tyler Middleton, Sr. Partner Marketing Manager, Experian Marketing Services Tyler Middleton is the Partner Marketing Lead at Experian. With almost 20 years of strategic marketing experience, Tyler’s focus is on creating marketing strategies that effectively promote the unique value propositions of each of our partners’ brands. Tyler helps our strategic partners communicate their mutual value proposition and find opportunities to stand out in the AdTech industry. Tyler is an alumnus of the Seattle University MBA program and enjoys finding new marketing pathways for our growing partner portfolio. 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