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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In our Ask the Expert Series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with George Castrissiades, General Manager of Connected TV at AdRoll. Premium reach and fragmentation As viewer attention fragments across platforms, how should marketers redefine “premium reach” in CTV to prioritize engagement and audience quality over scale alone? A few years ago, ad supported streaming over-indexed on younger adults, those without much financial history and much more budget conscious. It would have been fair for B2B brands to assume that maybe they weren’t going to find their C-Suite audiences on those channels, and so connected TV(CTV) was positioned as a top of funnel tactic aimed at retail. But that’s all changed – ad-free prices are going up, and ad supported tiers are the norm across the majority of channels. 66% of adults have at least one ad supported streaming channel, and adults today spend nearly as much time streaming movies and TV as they spend on their mobile phones. Now that ad viewing audiences on CTV really span the full spectrum of demo, techno, and firmographic segments, savvy marketers should partner with platforms that offer breadth and depth of targeting and measurement to find the highest value audiences wherever they’re watching CTV and serve them highly relevant ads that draw their attention towards the screen. I know I’m jumping out of my seat whenever I see an AdTech or MarTech ad. Identity and relevance What does a strong identity framework unlock for delivering household- and person-level relevance across screens, and how does it reshape audience planning? In privacy-safe ecosystems, people want to share less data and log in to websites and browsers less frequently. If you can’t resolve a household ID to a CTV device through Safari and other sources of obfuscated identity, you’re going to end up losing a lot of signal along the way. On top of that, targeting smaller, higher-value audiences means this attrition can have a profound impact on your ability to build meaningful reach and use audience forecasts to predict scale. A strong identity framework is the key to maintaining as much of your planned audience as possible and staying true to initial forecasts. AI and outcome planning How is AI evolving CTV from tactical bidding to strategic outcome planning, and what mechanisms are in place to validate true performance lift? Tomorrow isn’t guaranteed, especially not in advertising. Audiences change where and when they consume media, and so shifting budget to a placement that did well yesterday is like buying a stock when it’s outperforming – the gains might be gone by then! Predictive AI is bridging the gap to find the highest value and most engaged audiences in real time, versus being purely reactive. This helps drive outcomes which we see in the form of pipeline influence, ROAS, and site traffic lift – without exponentially increasing costs. The same is true for account-based marketing(ABM) outcomes – there’s a blend of signals, account “fit” and intent data that needs to be evaluated in a deeper, more intelligent way. AI is helping to find those highest value accounts, even before they’re in market, which means smart marketers aren’t showing up late to the party. Measurement and incrementality What privacy-safe, closed-loop measurement frameworks should become standard to prove incremental visits and sales from CTV campaigns? Working with a dedicated multichannel, full-funnel ad and marketing platform like AdRoll can easily let you know when a user arrives at your site and makes a purchase, but understanding how that customer arrived there and which tactics deserve the credit requires a deeper, more sophisticated workflow. Our partnership with Experian allows all devices in a household to ladder back up to a household ID, so we can ensure accuracy without pivoting on anything personally identifiable. This works perfectly in CTV, an environment that follows an app workflow of user resettable device IDs rather than IP address or email but always connects seamlessly to web tokens including cookies. Accuracy, scale, and privacy are maintained in a proven way – you see this tech underpinning the infrastructure of streaming across all the biggest players, so marketers can rest easy. Creative and commerce How can creative sequencing and shoppable TV experiences convert living-room attention into commerce without compromising user experience or feeling intrusive? I like to say that CTV trades attention for action. Users lean back and focus on the messaging and visuals of the big screen rather than scrambling for the mouse or tapping to close some intrusive pop-up. This focus means that the messaging is absorbed more quickly, but creatives can wear out their welcome just as fast. Sequential messaging really helps to move the messaging along without subjecting the viewer to longer ads where attention wanes, but also increases brand recall and specific product information because the story evolves with each impression. This is a great tactic to use when you want a viewer to take a specific action later – but shoppable ads can help motivate a user to act now, and new formats can really simplify things. Shoppable can feel out of range for most – the top players in this space own major e-comm storefronts and then tie them back into their own demand-side platforms (DSPs), content, and streaming devices. For the rest of us, dipping our toes in slowly through simple and cheap solutions like QR codes can connect audiences right to a web experience from their TVs, or intermediate solutions like interactive video ads. Users love to play around with fun on-screen experiences, and there’s a whole spectrum of crawl/walk/run options available. Trust and governance Which shared guardrails—brand safety, fraud control, and frequency management- are essential to unlocking sustainable, scaled investment in CTV? I’ve always thought of CTV inventory analogously to high-end watches – if you buy from the source or a well-known, reputable dealer, you’re probably buying the real thing. But that fancy timepiece the guy was selling outside the bar, that you swore looked real? Probably not. Untrusted resellers and too-good-to-be-true pricing might mean you’re running ads on a screen at a lonely gas station at 3 am to an audience of no one, and that's not even the worst case scenario. Good relationships and deep pockets can solve brand safety and fraud issues, but not every advertiser is going to have those resources. Brand safety and fraud prevention can reduce workload and help distinguish the good stuff from the growing pool of gray area, arguably, CTV inventory that isn’t what was promised to a customer. Outsourcing this trust also goes a long way, with buyers knowing you’re not grading your own homework. Frequency management is equally as important. Once you have your audience and your good supply, it’s important not to abuse a single household just because they meet your targeting criteria. Reach is your best friend with CTV. Data and audience strategy How do Experian’s syndicated audiences provide a consistent, scalable foundation for planning, activation, and measurement across CTV and digital, and what outcomes are clients seeing? We love to talk about how Experian’s data is such an integral part of so much of streaming’s architecture, and the fact that it’s built on deterministic datasets means you’re getting scaled audiences built on knowledge rather than best guesses. That means a lot when working across multiple channels, privacy-safe environments, and households with an ever-growing number of connected devices. Our customers are always delighted at how precise targeting can be, especially in the B2B/B2C space – and knowing the size of those audiences helps them to understand how budget transforms into reach in a more predictable way. It’s confidence-inspiring to point to a new audience and tell your client that these are their future customers. The best part is showing them the outcomes reporting – we consistently see a massive spike in site traffic and engagement on days when a new Experian syndicated audience is launched! Contact us FAQs Why is identity resolution important in CTV? Identity resolution ensures marketers can connect devices and maintain audience accuracy. Experian's identity solutions help reduce data loss and improve audience forecasts, making campaigns more effective. How can marketers find the right audiences on CTV? With viewer attention spread across platforms, marketers need tools that offer both broad and detailed targeting. Experian's syndicated audiences provide reliable, scalable data to help identify and reach high-value audiences across channels. How can creative strategies improve CTV campaigns? Techniques like sequential messaging and shoppable ads keep viewers engaged and encourage action. Simple tools like QR codes or interactive video ads can connect audiences to web experiences directly from their TVs. How do DSPs benefit from strong identity frameworks in CTV? Strong identity frameworks help DSPs maintain accurate targeting and audience reach, even in privacy-focused environments. By connecting devices to household IDs, solutions like Experian’s Digital Graph ensure DSPs can deliver relevant ads and measure performance effectively across channels. About our expert George Castrissiades General Manager of Connected TV, AdRoll George leads the CTV go-to-market strategy at NextRoll, driving rapid growth and adoption of the channel for both B2B and B2C customers. With a track record of building and scaling CTV solutions, he is focused on developing a strategic playbook that accelerates success in the evolving digital advertising landscape. Before joining NextRoll, George spearheaded CTV product innovation at iSpot.tv and held leadership roles in product and operations at YouTube, VICE Media, Crackle, Roku, and Innovid. His expertise spans product development, monetization, and market expansion. About AdRoll AdRoll is a connected advertising platform built for growth-minded marketers. With powerful AI, flexible campaign tools, and seamless integrations, AdRoll helps mid-sized businesses turn complexity into clarity and clicks into customers. The AdRoll platform delivers full-funnel performance through multi-channel advertising, audience insights, and cross-channel attribution, supporting marketers across industries including ecommerce, technology, financial services, education, and more. For B2B teams, AdRoll ABM extends these capabilities with account-based precision, multi-touch campaigns, and real-time buyer intelligence. Backed by nearly 20 years of data and award-winning support, AdRoll enables marketing teams to advertise smarter, move faster, and achieve more, all from one place. Latest posts