Contextual ad targeting paves the way for new opportunities
Advertisers and marketers are always looking for ways to remain competitive in the current digital landscape. The challenge of signal loss continues to prompt marketers to rethink their current and future strategies. With many major browsers phasing out support for third-party cookies due to privacy and data security concerns, marketers will need to find new ways to identify and reach their target audience. Contextual ad targeting offers an innovative solution; a way to combine contextual signals with machine learning to engage with your consumers more deeply through highly targeted accuracy. Contextual advertising can help you reach your desired audiences amidst signal loss – but what exactly is contextual advertising, and how can it help optimize digital ad success?
In a Q&A with our experts, Jason Andersen, Senior Director of Strategic Initiatives and Partner Solutions with Experian, and Alex Johnston, Principal Product Manager with Yieldmo, they explore:
- The challenges causing marketers to rethink their current strategies
- How contextual advertising addresses signal loss
- Why addressability is more important than ever
- Why good creative is still integral in digital marketing
- Tips for digital ad success
By understanding what contextual advertising can offer, you’ll be on the path toward creating powerful, effective campaigns that will engage your target audiences.
Check out Jason and Alex’s full conversation from our webinar, “Making the Most of Your Digital Ad Budget With Contextual Advertising and Audience Insights” by reading below. Or watch the full webinar recording now!
Macro impacts affecting marketers
How important is it for digital marketers to stay informed about the changes coming to third-party cookies, and what challenges do you see signal loss creating?
Jason: Marketers must stay informed to succeed as the digital marketing landscape continuously evolves. Third-party cookies have already been eliminated from Firefox, Safari, and other browsers, while Chrome has held out. It’s just a matter of time before Chrome eliminates them too. Being proactive now by predicting potential impacts will be essential for maintaining growth when the third-party cookie finally disappears.
Alex: Jason, I think you nailed it. Third-party cookie loss is already a reality. As regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) take effect, more than 50% of exchange traffic lacks associated identifiers. This means that marketers have to think differently about how they reach their audiences in an environment with fewer data points available for targeting purposes. It’s no longer something to consider at some point down the line – it’s here now!
Also, as third-party cookies become more limited, reaching users online is becoming increasingly complex and competitive. Without access to as much data, the CPMs (cost per thousand impressions) that advertisers must pay are skyrocketing because everyone is trying to bid on those same valuable consumers. It’s essential for businesses desiring success in digital advertising now more than ever before.
Contextual ad targeting: A solution for signal loss
How does contextual ad targeting help digital marketers find new ways to reach and engage with consumers? What can you share about some new strategies that have modernized marketing, such as machine learning and Artificial Intelligence (AI)?
Jason: We’re taking contextual marketing to the next level with advanced machine learning. We are unlocking new insights from data beyond what a single page can tell us about users. As third-party cookies go away, alternative identifiers are coming to market, like RampID and UID2. These are going to be particularly important for marketers to be able to utilize.
As cookie syncing becomes outdated, marketers will have to look for alternative methods to reach their target audiences. It’s essential to look beyond cookie-reliant solutions and use other options available regarding advertising.
Alex: I think, as Jason alluded to, there’s a renaissance in contextual advertising over the last couple of years. If I were to break this down, there are three core drivers:
- The loss of identity signals. It’s forcing us to change, and we must look elsewhere and figure out how to reach our audiences differently.
- There have been considerable advances in our ability to store and operate across a set of contextual signals far more extensive than anything we’ve ever worked with in the past and in far more granular ways. That’s a huge deal because when it comes to machine learning, the power and the impact of those machine learning models are entirely based on how extensive and granular the data set is that you can collect. Machine learning can pull together critical contextual signals and figure out which constellations, or which combinations of those signals, are most predictive and valuable to a given advertiser.
- We can tailor machine learning models to individual advertisers using all those signals and find patterns across those in ways that were previously impractical or unfeasible. The transformation is occurring because of our ability to capture much more granular data, operate across it, and then build models that work for advertisers.
Addressability: Connect your campaigns to consumers
How does advanced contextual targeting help marketers reach non-addressable audiences?
Jason: Advanced contextual targeting allows us to take a set of known data (identity) and draw inferences from it with all the other signals we see across the bitstream. It’s taking that small seed set of either, customers that transacted with you before that you have an identity for, or customers that match whom you’re looking for. We can use that as a seed set to train these new contextual models. We can now look at making the unknown known or the unaddressable addressable. So, it’s not addressable in an identity sense, it is addressable in a contextual or an advanced contextual sense that’s made available to us, and we can derive great insight from it.
One of the terms I like to use is contextual indexing. This is where we take a set of users we know something about. So, I may know the identity of a particular group of households, and I can look at how those households index against any of the rich data sets available to us in any data marketplace, for example, the data Yieldmo has. We can look at how that data indexes to those known users to find patterns in that data and then extrapolate from that. Now we can go out and find users surfing on any of the other sites that traditionally don’t have that identifier for that user or don’t at that moment in time and start to be able to advertise to them based on the contextually indexed data.
Historically, we’ve done some contextual ad targeting based on geo-contextual, and this is when people wanted to do one to one marketing, and geo-contextual outperformed the one to one. But marketers weren’t ready for alternatives to one to one yet. We want marketers to start testing these solutions. Advertisers must start trying them, learning how they work, and learn how to optimize them because they are based on a feedback loop, and they’re only going to get better with feedback.
Alex: Jason, you described that perfectly. I think the exciting opportunity for many people in the industry is figuring out how to reach your known audience in a non-addressable space, that is based on environmental and non-identity based signals, that helps your campaign perform. Your known audience are people that are already converting – those who like your products and services and are engaged with your ads. Machine learning advancements allow you to take your small sample audience and uncover those patterns in the non-addressable space.
It’s also worth noting that in this world in which we are using seed audiences, or you are using your performing audiences to build non-addressable counterpart targeting campaigns, having high-quality, privacy-resilient data sets becomes incredibly important. In many cases, companies like Experian, who have high quality, deep rich training data, are well positioned to support advertisers in building those extension audiences. As we see the industry evolve, we’re going to see some significant changes in terms of the types of, and ways in which, companies offer data, and make that available to advertisers for training their models or supporting validation and measurement of those models.
Jason: Addressable users, the new identity-based users, are critical to marketers’ performance initiatives. They’re essential to training the models we’re building with contextual advertising. Together, addressable users and contextual advertising are a powerful combination. It’s not just one in isolation. It’s not just using advanced contextual, and it’s not just using the new identifiers. It’s using a combination to meet your performance needs.
It’s imperative to start thinking about how you can begin building your seed audiences. What can you start learning from, and how do you put contextual into play today? You are looking to build off a known set and build a more advanced model. These can be specialized models based on your data. You can hone in and create a customized model for your customer type, their profile, and how they transact. It’s a greenfield opportunity, and we’re super excited about the future of advanced contextual targeting.
Turn great creative into measurable data points
Why does good creative still play an integral part in digital advertising success?
Jason: Good creative has always been meaningful. It’s vital in getting people to click on your ad and transact. But it’s becoming increasingly important in this new world that we’re talking about, this advanced contextual world. The more signal that we can get coming into these models, the better. Good creative in the proper ad format that you can test and learn from is paramount. It comes back to that feedback loop. We can use that as another signal in this equation to develop and refine the right set of audiences for your targeting needs.
Alex: If you imagine within the broader context of identity and signal loss, creative and ad format becomes incredibly powerful signals in understanding how different audiences interact with and engage with different creative. In the case of the formats that serve on the Yieldmo exchange, we’re collecting data every 200 milliseconds around how individual users are engaging with those ads. Interaction data like the user scrolling back or the number of pixel seconds they stay on the screen, fills this critical gap between video completes and clicks. Clicks are sparse and down the funnel, and views and completes are up the funnel. All those attention and creative engagement type metrics occupy the sweet spot where they’re super prevalent, and you can collect them and understand how different audiences engage with your ads. That data lets you build powerful models because they predict all kinds of other downstream actions.
Throughout my career, I learned that designing or tailoring your creative to different audience groups is one of the best ways to improve performance. We ran many lift studies with analysis to understand how you can tailor creative customized for individual audiences. That capability and the ability to do that on an identity basis is starting to deteriorate. The ability to do that using a sample of data or using a smaller set of users, either where you’re inferring characteristics or you’re looking at the identity that does exist in a smaller group, becomes powerful for being able to customize your creative to tell the right story to the right audience. When you layer together all the interaction data collected at the creative level on top of all the contextual and environmental signals, you can build powerful models. Whether those are driving proxy metrics, or downstream outcomes, puts us in a powerful position to respond to the broader loss of identity that we’ve relied on for so many years.
Our recommendations for marketers for 2023 and beyond
Do you have recommendations for marketers building out their yearly strategies or a campaign strategy?
Jason: Be proactive and start testing and learning these new solutions. I mentioned addressability and being in the right place at the right time. That’s easier in today’s third-party cookie world. But as traditional identity is further constricted, you will have these first-party solutions that will not be at scale, so you’re less likely to find your user at the scale you want. It would be best if you thought about how to reach that user at the right place at the right time. They may not be seen from an identity basis. They might not be at the right place at the right time when you were delivering or trying to deliver an ad. But you increase your chance of reaching them by building these advanced contextual targeting audiences using this privacy-safe seed ‘opted-in’ user set; this is a way to cast that wider net and achieve targeted scale.
Alex: Build your seed lists, test your formats with different audiences, and understand what’s resonating with whom. Take advantage of some of the pretty remarkable advances in machine learning that are allowing us, really, for the first time to fully uncork the potential and the opportunity with contextual in a way that we’ve never done before.
Jason: At the end of the day, it’s making the unaddressable addressable. So, it’s a complementary strategy; having that addressable piece will feed the models. But also, that addressable piece still needs to be identity-based, addressable still needs to be part of your overall marketing strategy, and you need to complement it with other strategies like advanced contextual targeting. The two of them together are super complimentary. They learn from each other, and it’s a cyclical loop. Now is the time to take advantage and start testing and understanding how these solutions work.
We can help you get started with contextual ad targeting
Contextual advertising can help you stay ahead of the curve, identify your target audience, and continue to drive conversions despite signal loss. We’ve partnered with Yieldmo to help make sure that your marketing campaigns are reaching the right target audiences on the platforms that are most relevant. To get started with contextual ad targeting to reach the right audience at the right time and drive conversions, contact our marketing professionals. Let’s get to work, together.
Find the right marketing mix in 2023
Check out our webinar, “Find the right marketing mix with rising consumer expectations.” Guest speaker, Nikhil Lai, Senior Analyst from Forrester Research, joins Experian experts Erin Haselkorn, and Eden Wilbur. We discuss:
- New data on the complexity and uncertainty facing marketers
- Consumer trends for 2023
- Recommendations on finding the right channel mix and the right consumers
Get in touch
About our experts
Jason Andersen, Senior Director, Strategic Initiatives and Partner Solutions, Experian
Jason Andersen heads Strategic Initiatives and Partner Enablement for Experian Marketing Services. He focuses on addressability and activation in digital marketing and working with partners to solve signal loss. Jason has worked in digital advertising for 15+ years, spanning roles from operations and product to strategy and partnerships.
Alex Johnston, Principal Product Manager, Yieldmo
Alex Johnston is the Principal Product Manager at Yieldmo, overseeing the Machine Learning and Optimization products. Before joining Yieldmo, Alex spent 13 years at Google, where he led the Reach & Audience Planning and Measurement products, overseeing a 10X increase in revenue. During his time, he launched numerous ad products, including YouTube’s Google Preferred offering. To learn more about Yieldmo, visit www.Yieldmo.com.
Latest posts
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
Every marketer has seen it: a customer browses reviews on a laptop, adds items to a cart on mobile, then “disappears.” In reality, they just likely switched devices or logged in with a different email. Identity resolution connects these scattered signals into a single profile so you never lose sight of the customer journey. Identity resolution is what helps you keep track of customers who bounce around. Connecting scattered signals into a single customer profile can help you deliver seamless experiences, meet strengthening privacy standards, turn first-party data into measurable results, and fuel better customer analytics. See our identity resolution solution in action Learn about it here What is identity resolution? Identity resolution is the process of pulling together the different identifiers a customer uses and connecting them to a single profile. Without it, you’re left with an incomplete picture of the customer — like a cart tied to one email, an app login tied to another device, or a loyalty swipe that never links back to the same person. Common identifiers include: Cookies: Short-lived browser data Emails: Plain-text and hashed Device IDs: Mobile advertising IDs (MAIDs) or app-based identifiers Loyalty IDs: Program numbers that tie online and offline activity Hashed PII: Personally identifiable information (PII) encrypted for privacy Ultimately, identity resolution can help you recognize the same customer wherever they engage. Why does identity resolution matter now? Marketers face incomplete views, data silos, privacy regulations, and shrinking visibility: Rising consumer expectations: People want seamless, personalized journeys across touchpoints. Privacy-first environment: Consumer privacy legislation (like the GDPR, CCPA, GLBA, FCRA, and new state laws) makes compliance non-negotiable. Signal loss: The decline of cookies, MAIDs, and walled gardens are pushing brands toward first-party data. Experian utilizes AI and machine learning to fill these gaps, predict behaviors, and connect signals across devices — providing marketers with a clear, privacy-safe view of their customers, even when traditional identifiers are missing. In this environment, identity resolution matters because it gives marketers a way to deliver seamless, personalized customer experiences and engage audiences effectively while respecting their privacy. It’s the basis for turning consented first-party data into measurable marketing outcomes without sacrificing trust. Talk to an expert Why is identity resolution critical in a privacy-first world? Even as cookies linger, marketers have already shifted their strategies to rely on first-party data, where choice and transparency are the baseline expectation. At Experian, our long history as a regulated data steward makes us a uniquely capable and trusted partner for managing modern compliance expectations. Our identity resolution solutions maximize the value of permission-based data while meeting consumer demand for privacy, personalization, and control. Struggling with scattered customer data? Experian makes identity resolution seamless Learn more How does identity resolution help brands? Identity resolution turns fragmented signals into unified profiles that drive personalization, efficiency, and compliance. Here’s how it creates measurable business impact. Creates a unified customer view One of the biggest advantages of identity resolution is the ability to integrate data from loyalty programs, point-of-sale (POS) systems, customer relationship management (CRM) platforms, web analytics, and offline sources into a single, comprehensive profile. Experian strengthens identity resolution with AI-driven clustering models that resolve household and individual identities across billions of signals with greater accuracy. With a clearer picture of each customer, brands see higher match rates and larger addressable audiences, which translates to more substantial reach and better return on ad spend (ROAS). Enables better personalization Customers constantly switch devices, update their information, and change preferences. Experian makes it easier to keep pace with these changes through frequent data enrichment and near-real-time identity resolution via Activity Feed. Combined with our long-standing use of AI and machine learning, this approach ensures shifting behaviors are captured quickly, enabling timely personalization, and more responsive engagement. With less delay from data to action, the result is faster response times and higher conversion rates. Improves the customer experience Customers notice when brands deliver relevant ads and contextual content across every channel. Consistency matters! But consistency doesn’t just happen on its own; it comes from identity resolution, which keeps the customer journey connected. As brands maintain continuity, they build trust, strengthen engagement, and increase customer lifetime value. Drives better marketing ROI Not every profile is valuable. Identity resolution helps marketers identify the highest-value audiences and reduce wasted spend. That efficiency leads to lower CPA and a higher overall ROI across campaigns. The power of modeling from a stronger foundation When you have a unified customer view, your models are built on better data. That means you can find more people who look like your best customers, build more responsive audience segments, and target with greater accuracy. This foundation can lead to better spending, more relevant campaigns, and a higher ROI. Maintains privacy compliance With GLBA/FCRA-grade standards and consumer choice mechanisms like opt-outs and data correction, you can protect your brand while maintaining personalization — without compromising legal or ethical safeguards. What are some identity resolution use cases and examples? Every industry faces its own unique identity challenges, but identity resolution is the common thread that turns scattered data into connected experiences. Let’s break down how companies in different verticals are putting it to work (and the kinds of results they’re seeing). Retail and e-commerce Shoppers bounce between websites, carts, and checkout lines, leaving behind scattered signals in the process. In retail, identity resolution bridges the gap between online and in-store experiences by matching online carts with loyalty swipes or connecting connected TV (CTV) exposure to in-store sales. This means fewer silos, better targeting, and more personalized offers wherever people shop. Our 2025 Digital trends and predictions report calls out that omnichannel experiences aren’t optional anymore. With CTV and social dominating spend, brands need identity resolution to cut through silos and build a complete view of customer behavior. Read the full report Financial services In financial services, identity resolution makes it possible to deliver personalized, compliant offers like refinancing options for likely mortgage switchers or the right rewards card for frequent spenders. Our partnership with FMCG Direct to create Consumer Financial Insights® and Financial Personalities® segments helps banks, insurers, and lenders understand behaviors — such as credit card use, deposit balances, and investment habits — without exposing sensitive details. Read more below about how our financial audiences enable privacy-safe personalization. Explore privacy-safe financial audiences Travel and hospitality Travel decisions aren’t always planned out in advance. Many bookings happen spur-of-the-moment, which is why real-time identity resolution is so powerful; it keeps the journey seamless when travelers jump from phone to laptop to tablet and presents relevant offers right as decisions are being made. Windstar Cruises put this information into action with Experian’s identity graph to connect digital interactions with actual bookings, which drove 6,500+ reservations and $20 million in revenue. Get the $20 million Windstar Cruises playbook here Media and TV Viewers tend to hop around between linear TV, streaming apps, and social feeds. And without identity resolution, every screen looks like a different person. Marketers can accurately plan, activate, and measure campaigns by unifying viewing behaviors into one ID with Experian’s AI-powered identity graph. Optimum Media tackled its multiscreen challenge by partnering with Experian for identity solutions. Layering our audience insights and our AI-driven Digital Graph onto their subscriber data, they were able to connect the dots across channels, reach the right households, and measure results instead of just impressions. In the end, they finally got a clear view of what works across every screen. Learn how Optimum Media mastered multiscreen measurement Curious how identity resolution can power your customer analytics? We can walk you through it. Chat with an expert Healthcare and pharma Healthcare marketers can’t afford slip-ups with HIPAA regulations. Identity resolution makes it possible to engage the right patients and providers with de-identified audiences rather than third-party cookies. At Experian, AI and machine learning have always been part of how we power identity resolution. In healthcare, that means using AI-enhanced modeling to connect de-identified clinical and claims data with lifestyle insights. The result is a more comprehensive picture of the patient journey that helps close care gaps, reduce wasted spending, and improve outcomes. By working with partners like Komodo, PurpleLab, and Health Union, we make it possible to activate campaigns at scale that boost engagement and adherence while keeping patient privacy front and center: Komodo Health enriches our identity graph with insights from millions of de-identified patient journeys plus lifestyle data, giving brands a fuller view of where care gaps exist and how to close them. PurpleLab connects real-world clinical and claims data to Experian’s platform, letting advertisers activate HIPAA-compliant audiences across CTV, mobile, and social with the ability to measure real outcomes like prescription lift and provider engagement. Health Union contributes a data set built from 50 million+ patient IDs and 44 billion+ patient-reported data points. Combined with our identity and modeling capabilities, this expands match rates and unlocks up to 76% net-new reach, so campaigns reach patients and caregivers in critical health moments. As a result, healthcare brands can launch campaigns that are privacy-first, highly targeted, and proven to drive meaningful impact. Audio People use audio while commuting, working out, and even folding laundry. It can be one of the hardest channels to track because of how frequently listeners switch between apps, stations, and devices. Experian’s identity resolution partnerships with Audacy and DAX change the game: Audacy helps tie scattered listening into a single view, so advertisers can follow audiences across devices and keep ads relevant in the moment. DAX pairs Experian’s 2,400+ syndicated audiences with its audio network, enabling brands to target precisely and launch impactful campaigns at scale. These partnerships turn audio into an accurate channel where ads feel personal, privacy-safe, and measurable. Gaming Gamers don’t stick to one platform. Player data gets scattered across mobile, console, and PC, so it’s tough to keep track of individuals. Experian helps stitch those signals together so publishers can finally see the whole picture, personalize gameplay, and keep players coming back. With enriched profiles, publishers can deliver offers that resonate and unlock fresh revenue by packaging high-value gaming audiences for advertisers outside the industry. Unity, a leading gaming platform, is tapping into Experian’s syndicated audiences to gain player insights and help advertisers reach gamers across mobile, web, and CTV. For global publishers, unifying player data with Experian has driven higher engagement and stronger ad ROI. Discover how to unlock revenue with unified player data How should I evaluate identity resolution providers? When choosing an identity resolution partner, look for: Data scale and quality: The value of identity resolution depends on how complete and accurate the underlying data is. The right provider should bring together a wide range of identifiers from online and offline sources, maintaining high accuracy so your customer profiles are broad and reliable. Match accuracy and recency: The best partners also refresh their data regularly and can blend deterministic (exact, one-to-one matches) with probabilistic (pattern-based matches) methods. That way, you get the accuracy of “this email is definitely that customer” with the reach of “this device likely belongs to the same person.” Privacy and compliance readiness: Compliance can’t be an afterthought. Your identity partner should be ready for GLBA, FCRA, GDPR, CCPA, and the latest state-level rules with built-in tools for opt-outs, corrections, and deletions. Integration flexibility: A good provider fits into your world, not the other way around. Look for pre-built integrations with your customer data platform (CDP), demand-side platform (DSP), or marketing tech (MarTech) stack so you can get up and running without the heavy IT lift. Data analytics capabilities: You need proof that identity resolution drives ROI. Look for closed-loop measurement that ties unified IDs directly to campaign performance, so you can see what’s working and optimize with confidence. How Experian enables enterprise-grade identity resolution Experian delivers identity resolution at the scale, accuracy, and compliance required by the world’s largest enterprises. Our solutions are: Built on trust: Backed by 40+ years as a regulated data steward and rated #1 in data accuracy by Truthset, so you can act with confidence. Powered by our proprietary AI-enhanced identity graph: Combining breadth, accuracy, and recency across four billion identifiers, continuously refined by machine learning for maximum accuracy. Seamlessly connected: Pre-built data integration with leading CDPs, DSPs, and MarTech platforms for faster time to value. Always up to date: Frequent enrichment and near-real-time identity resolution through Activity Feed for timely personalization and more responsive customer engagement. Privacy-first by design: Compliance with GLBA, FCRA, and emerging state regulations baked in at every step, supported by rigorous partner vetting. The bottom line Identity resolution turns fragmented signals into connected, measurable, and compliant experiences. From retail to gaming, brands using it see stronger personalization, engagement, and ROI. With Experian, you get the data, trust, and responsible AI innovation to make identity resolution work across every channel. Our approach uses AI to connect identities, predict behaviors, and deliver personalization that balances privacy with performance. If you’re ready to turn fragmented data into growth, now’s the time to start. The world’s leading brands trust us to power identity resolution at scale. See how we can do the same for you. Identity resolution FAQs What’s the difference between deterministic and probabilistic matching? Deterministic uses exact identifiers (like an email) for accuracy, while probabilistic uses signals and algorithms to expand reach. Best-in-class providers usually combine both. How does identity resolution improve ROI? Identity resolution helps with personalization by unifying scattered signals into one profile. It reduces wasted spend and increases match rates, which means bigger addressable audiences and higher ROAS. Can identity resolution work without third-party cookies? Yes. With first-party data and hashed PII, brands can still maintain addressability and personalization. What industries benefit most from identity resolution? Retail, finance, travel, media, gaming, and audio all use identity resolution to personalize, attribute sales, and improve efficiency. How is Experian different from a CDP? A customer data platform unifies the data you already own. Meanwhile, we add depth, scale, and higher match rates by layering in our identity graph and data enrichment. Is Experian identity resolution privacy-compliant? Yes. Experian is GLBA/FCRA compliant, GDPR/CCPA ready, and supports consumer opt-outs and corrections to ensure responsible personalization. Latest posts
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 Allison Dewey (Director, Data & Curation) at 33Across. Navigating complexity in digital advertising Digital advertising is more fragmented and privacy-constrained than ever. How is 33Across helping marketers cut through that complexity to drive real outcomes, and what makes your approach distinct? Reaching audiences without compromising scale or performance is one of the toughest challenges for marketers. Users consume content across multiple devices and channels, making it difficult for marketers to identify and accurately target them with the right message. 33Across segments leverage AI-powered contextual and behavioral signals across privacy-safe environments to help marketers accurately identify audiences, whether they’re streaming content on their connected TV or researching products on their mobile device. What sets us apart is that we don’t just identify valuable audiences; we help marketers also target cookieless inventory and power it with real-time signals. Marketplace integration milestones What excites you most about bringing 33Across audiences into Experian’s data marketplace? We’re excited to bring 33Across audiences into Experian’s data marketplace because it connects our unique segments with a powerful data ecosystem that marketers already trust. Buyers looking to activate audiences that are both privacy-safe and performant continue to tap into the Experian data marketplace for high-quality, high-performing data. We offer a wide range of audience verticals, including B2B, demographic, retail purchase data, interest and intent, and political data. In addition, we offer the ability to create custom segments across verticals. Our intent-based audiences, built from contextual and engagement signals, help buyers reach consumers on CTV, desktop, or mobile devices with scale. Being part of Experian’s data marketplace accelerates access to these audiences, drives better ROI, and helps brands future-proof their strategies today. Retail demand signals Retail brands are racing toward privacy-safe, first-party data. Which 33Across retail datasets or segments are experiencing the highest demand, and what makes them a must-have? Retail marketers are leaning into contextual and behavioral intent signals to complement their first-party data strategies. At 33Across, we’re seeing high demand for segments tied to shopping intent, including in-market consumers browsing for categories like fashion, home goods, electronics, and health & wellness. What makes these segments essential is their real-time nature – they can capture consumer interest as it happens. For retail brands looking to expand their reach while respecting privacy, our segments offer scalable, actionable intent that drives results. B2B without cookies Reaching real B2B decision-makers at scale is tough with or without signals. How does 33Across deliver both precision and reach in this environment? B2B marketing often struggles with balancing scale and specificity. 33Across addresses this by combining contextual precision with AI-modeled behavioral signals; this segment approach reaches professionals actively engaging with relevant content and topics, even in environments where IDs are unavailable. Marketers gain access to more signals and, in turn, better reach from 33Across’ unique publisher integrations and audience curation built from machine learning and AI. We surface intent through content consumption patterns and contextual engagement, unlocking valuable, privacy-safe signals at scale. Allowing B2B marketers to reach real decision-makers in a signal-sparse world. Use cases With retail, B2B, and beyond, can you share an example of how brands in these verticals are utilizing your audiences? Top brands that have a user-focused approach use 33Across audiences to drive scale; performance. These brands enable our segments to precisely reach the right users across devices and increase conversion rates; brand awareness. By reaching the right users, brands have higher conversion rates and increase campaign efficiency. Supply path innovation As identifiers disappear, advertisers are looking for scalable, privacy-safe ways to reach real people. How is 33Across helping unlock more addressable inventory and drive performance? By combining contextual, semantic, and engagement-based signals, we deliver intent-based targeting that performs across CTV, display and video. Higher addressability helps marketers not only extend their reach but also deliver personalized messaging across digital channels in a privacy-compliant way. Contact us FAQs How can advertisers reach audiences without traditional identifiers? By using contextual and engagement-based signals, advertisers can target consumers across CTV, mobile, and desktop in a privacy compliant way, even as identifiers become less available. What audience segments are most in demand for retail marketers? Segments tied to shopping intent, such as consumers browsing fashion, electronics, or health products, are highly sought after because they capture real time interest and drive results. How can B2B marketers find decision-makers without cookies? Combining content engagement patterns with machine learning allows marketers to reach professionals actively engaging with relevant topics, even in environments where IDs are unavailable. What makes privacy safe audience targeting effective? Privacy safe targeting uses real time contextual and behavioral signals to deliver relevant messaging across devices and channels without compromising consumer trust. How can real-time intent signals drive demand? Real time intent signals allow advertisers to capture consumer interest as it happens, helping demand side platforms and brands deliver timely, relevant ads that increase engagement and drive conversions across devices like CTV, mobile, and desktop. About our expert Allison Dewey, Director of Data and Curation, 33Across Allison Dewey is the Director of Data & Curation at 33Across, where she oversees data partnerships, integrations, and supply-side curation. With a deep expertise in audience targeting and signal optimization, Allison plays a key role in connecting data into the programmatic world. Allison holds a Bachelor\’s degree in Psychology from Bates College. About 33Across Rooted in over 15 years of data expertise, 33Across harnesses signals to enrich and expand marketers’ audiences and reach them wherever they consume content. Built from over 300 billion proprietary data signals, we apply machine learning and AI to create over 1,500 B2C and B2B segments using privacy-first principles to reach audiences. Latest posts