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 Brian Mandelbaum, CEO and Co-Founder at Attain. About Attain Built for privacy — with visibility across all retailers, verticals and purchases — Attain provides solutions for the modern marketer. Its real-time measurement and optimization solutions coupled with high-fidelity audiences and proprietary insights enable marketers to drive valuable business outcomes. The power of transaction-based audiences Attain’s real-time transaction data provides a 360-degree view of consumer behavior. What makes this approach more effective than traditional demographic or behavioral targeting? Attain is the industry’s most trusted source of live purchase data, powered by a robust panel of 8 million fully permissioned consumers. Our platform delivers unmatched, real-time visibility into consumer purchase behavior across retailers, industries, and payment methods. Marketers gain deep insights — such as in-store vs. online purchases, payment methods, purchase frequency, cart contents, and average transaction value — enabling more precise audience targeting and media strategies. With Attain’s rich, transaction-based data, marketers can optimize campaigns with direct, actionable sales signals. Ensuring data accuracy and relevance Attain curates audiences using real-time transaction data, but advertisers often ask whether this data is deterministic or probabilistic. Can you clarify your methodology, and if probabilistic, how do you ensure accuracy and representation across the entire US population? Our transaction data comes directly from the largest live purchase data panel in the U.S. Covering over 10,000+ merchants and $600B in cumulative spend, our dataset offers a complete and dynamic view of real-world purchase behavior. Using advanced machine learning, we scale this data to represent the entire U.S. population with unmatched accuracy, ensuring a balanced and unbiased reflection of consumer spending patterns. Our rigorous methodology eliminates outliers, continuously optimizing for precision and stability, so marketers can trust our insights for better targeting, measurement, and optimization. Privacy-first data practices Attain is built on a privacy-first, consumer-permissioned model. There are many ways to capture purchase data—why did Attain choose a panel-based approach, and how does this method compare to other collection strategies in terms of accuracy, scale, and compliance? Attain’s panel-based approach is the foundation of our privacy-first, consumer-permissioned model. By capturing real-time transaction data directly from our opted-in consumer panel, we ensure unmatched accuracy and ethical data sourcing — paramount in today’s privacy-conscious world. In exchange for sharing their data, consumers receive valuable benefits like early wages, savings tools, and shopping rewards, with no hidden fees. Unlike legacy third party data providers, our directly sourced transaction data provides deeper, more precise insights, enabling highly granular and actionable audience segments. Our continuously growing panel reflects a broad cross-section of U.S. consumers while maintaining strict privacy and compliance standards. We fully adhere to regulations like CCPA and GDPR, giving both consumers and advertisers confidence in the responsible use of data. Attain’s approach delivers the ideal balance of accuracy, scale, and compliance—while prioritizing consumer trust. Cross-channel addressability With brands activating audiences across display, mobile, and CTV, how does Attain’s purchase data help advertisers refine their cross-channel strategies? Attain’s purchase data empowers advertisers to refine cross-channel strategies with smarter, data-driven insights. Our real-time transaction-based audiences enable scalable activation across display, social, online video, and addressable TV — ensuring campaigns reach high-intent buyers more likely to convert. By applying purchase-based audiences across all channels, marketers are utilizing the strongest signals possible, which enables a more effective holistic strategy to drive to that ultimate sales outcome. Whether through social media, TV/CTV, mobile, or programmatic platforms, Attain helps brands connect with consumers at key moments in their buying journey, maximizing media impact with real behavioral insights instead of proxies. With an expansive and growing network of media partners, Attain ensures brands reach their audiences wherever they are, delivering consistent, high-impact messaging. Whether optimizing for brand awareness or performance, our data helps marketers make smarter decisions to drive superior results. Proven performance with live purchase feedback Attain moves beyond traditional proxy metrics by providing live purchase data. How does this help advertisers optimize campaigns while they’re still running? What sets Attain’s audiences apart isn’t just the data fidelity and holistic coverage of consumer behavior, it's that they’re built and validated using live, privacy-safe purchase signals. Advertisers can execute campaigns confidently, knowing that they’re reaching real consumers based on recent, real-world transactions, not outdated models or inferred, probabilistic behaviors. Attain’s ability to measure sales lift across a wide range of inputs means that marketers can easily understand which audiences are driving actual sales outcomes during flight. This unlocks smarter mid-campaign optimizations, discovering new audiences, and fine-tuning targeting — to ensure audience performance continually improves against real revenue goals. Attain’s closed-loop approach gives advertisers a faster path from targeting to transaction, helping brands maximize the value of every impression. Industry-specific use cases Beyond CPG, Attain supports industries like QSR, retail, and financial services. Can you share a compelling example of how brands in these verticals are utilizing your audiences? Attain’s audiences provide a comprehensive view of the consumer, capturing all aspects of their purchase behaviors — from travel and dining to TV content consumption and shopping habits. This broad perspective offers brands a far richer set of buying signals than ever before, enabling them to make more informed decisions across the entire consumer journey. Quick service restaurants (QSR): With a comprehensive view across all transaction types (cash, credit, debit) – Attain enables QSRs to capture a full picture of customer spend at their nationwide locations. Ensuring these brands have holistic coverage across all sales channels, powered by a direct relationship with the consumer, Attain captures transactions both in-store, online, and through 3P delivery apps like UberEats and Grubhub. This powers Attain’s deep insights, which QSRs can use for intelligent, precise targeting- including frequent visitors, competitive share, products purchased, and more. QSRs can use this data to solve a variety of business objectives, like retention/growth, competitive conquesting, and more. Retail: In retail, Attain provides a wide range of audience segments, including loyalty shoppers, in-market buyers, competitive shoppers, and even adjacent buyers who may be interested in similar products. By combining these segments, retailers can optimize their campaigns to target real-time shoppers with the highest intent, rather than relying on outdated or generalized profiles that other providers might offer. Additionally, with our industry-leading refresh rate, brands benefit from the most up-to-date data, ensuring their campaigns are always aligned with the latest consumer behaviors. Financial services: In the financial services sector, Attain’s purchase data helps identify consumers who are actively considering financial products such as credit cards or loans. By understanding their purchasing behaviors, marketers can deliver highly personalized and relevant offers to those already displaying intent, leading to better conversion rates and more effective acquisition strategies. Integration with Experian's marketplace Attain is now available through the Experian marketplace. How does this integration make it easier for advertisers to activate and scale your audiences? Attain’s integration with Experian marketplace makes it easier than ever for advertisers to activate our purchase-based audiences across TV, social, and programmatic. This partnership makes Attain’s data even more accessible, supporting our mission to build the most comprehensive and trusted consumer data ecosystem. With direct access to our real-time audiences within Experian’s marketplace, advertisers can more efficiently launch campaigns at scale and make more precise, data-driven decisions. As one of Experian’s inaugural partners, we’ve already seen strong adoption and demand, reinforcing the value of this partnership. The future of transaction-based targeting As the use of transaction data in advertising continues to grow, what changes do you anticipate in how brands will apply it for targeting and measurement? And how is Attain evolving its approach to support those shifts? As transaction data reshapes advertising, brands can shift from targeting probabilistic audiences to reaching high-intent consumers for greater ad relevance and conversions. Purchase data also unlocks highly accurate incrementality measurement, closing the loop and revealing which tactics and channels drive true incremental sales. Attain’s platform is built for outcomes-driven advertising, capturing data across the entire media cycle to continuously optimize performance. As we continue to make investments in AI and machine learning into our platform, our insights will become even more actionable and efficient — helping brands maximize impact, drive incrementality, and fuel long-term growth. Thanks for the interview. Any recommendations for our readers if they want to learn more? To explore our audience segments, visit the Attain website or contact your Experian account representative to schedule your free match test. Contact us today About our expert Brian Mandelbaum, CEO and Co-Founder, Attain Brian Mandelbaum, a veteran entrepreneur and investor, is the co-founder and CEO of Attain, North America’s largest opt-in purchase platform. Prior to Attain, Brian founded Clearstream TV, a data-enabled video distribution platform acquired by Engine Group in 2015. He brings over 20 years of experience in data-driven digital media, collaborating with top agencies and major brands. Latest posts
Retail media networks (RMNs) are on track to capture over $128 billion in ad spend by 2028, growing nearly 25% year over year. But behind this rapid expansion, RMNs face a challenge that could slow their momentum: they lack the complete picture of their customers. Retailers sit on a goldmine of first-party data—loyalty programs, online purchases, and in-store transactions—but their customer view is often fragmented, incomplete, or entirely anonymous. Without a strong identity foundation, RMNs struggle to: Scale advertiser reach beyond logged-in users Seamlessly match audiences across channels (CTV, programmatic, social) Deliver the precise targeting and measurement that advertisers demand The reality? Data is only valuable if it’s usable. And right now, too many RMNs are leaving value on the table. The identity challenge: If you can’t see it, you can’t monetize it Retailers have two types of customers: Known customers: Logged-in or self-identified users with purchase history and identifiable attributes. Unknown customers: Shoppers who browse, purchase in-store, or check out as guests—leaving behind only partial or anonymous data. Although many retailers have a loyalty program, it’s unlikely they are capturing a full view of all of their customers, especially outside of their four walls. When retailers don’t know their customers, they can’t effectively: Understand what messages will resonate with what audiences Extend their audiences beyond their owned platforms Provide advertisers with the reach and addressability they demand Accurately measure media performance and prove ROI But this challenge isn’t unsolvable—it’s an identity problem, and Experian is built to fix it. The missing link: Clean, enriched, and connected data Assuming your data is ready to activate is a costly mistake. Too often, RMN data is messy, siloed, and incomplete, making it difficult to deliver the precision and performance advertisers expect. Experian flips the script—helping RMNs transform fragmented signals into a complete, connected picture of their audience. Here’s how Experian helps RMNs go from fragmented to first-class Clean and optimize We organize messy customer data, removing duplicates and filling in gaps. Enrich and enhance Our insights add depth to profiles with demographics, behavior, and purchase intent signals. For example, an RMN may know a shopper recently bought a car seat—but not that they lease a luxury SUV. That auto data is critical to securing auto ad dollars, and it’s exactly the kind of insight Experian provides. Expand and connect Using digital identifiers like hashed emails (HEMs), mobile ad IDs (MAIDs), and connected TV (CTV) IDs, we help extend audience reach across every channel advertisers care about. The result? A complete and addressable audience picture that RMNs can activate confidently—on-site and off. We partnered with one of the largest RMNs in the world to overhaul its first-party shopper data ahead of industry changes. By anchoring its data to stable digital IDs, addressability skyrocketed by nearly 300%. That’s the Experian difference—turning guesswork into confidence. Retailers who master identity will win the RMN race In an increasingly competitive RMN landscape, identity isn’t optional—it’s everything. Advertisers demand scale, accuracy, and measurable impact. Only RMNs with a robust identity foundation will rise above the competition. RMNs that prioritize identity resolution and data enrichment will: Drive more revenue by increasing the size of their addressable audience Keep advertisers engaged with better targeting and measurement Capture RMN market share by offering scale and accuracy Don’t just compete—lead. Ready to transform? Experian will show you how Fixing data inside the RMN ecosystem is just the beginning. In part two, we’ll cover: Why RMNs should be activating their enriched first-party data across CTV, programmatic, and social. Why off-site expansion is the future of maximizing revenue. How Experian’s data and identity solutions power off-site activation. Experian isn’t just part of the RMN conversation. We’re driving it. Let’s talk. Connect with our team Latest posts
As privacy regulations, signal loss, and consumer expectations change, marketers face growing challenges in creating meaningful connections. In our latest Ask the Expert segment, Tom Wolfe, SVP at Viant, and Ali Mack, VP of AdTech Sales at Experian explore how first- and third-party data strategies, advancements in connected TV (CTV), and AI tools empower marketers to build smarter campaigns tailored to modern demands. Identity-driven advertising built on first-party data With the decline of traditional third-party signals and the rise of privacy-first advertising, first-party data is more important than ever. By collecting data directly from customers, marketers ensure they have accurate, user-consented data to fuel personalized advertising. Viant’s identity graph takes these first-party signals—such as email addresses, household locations, and phone numbers—and connects them with additional attributes in a privacy-safe way. This approach empowers marketers to build precise audience segments without relying on cookies, which Viant phased out over a decade ago. Combining first-party data and privacy-first solutions to build trust By combining first-party data strategies with privacy-first solutions, marketers can build long-term success while earning consumer trust. The Viant Household ID eliminates reliance on cookies while enabling secure, compliant campaign management. Additionally, Viant's partnerships with cleanrooms further protect their clients' data integrity and ensure smooth collaboration between trusted parties. Beyond safeguarding consumer information, the Viant ecosystem allows their clients to integrate data seamlessly from audience segmentation to campaign activation and reporting. How first and third-party data work together While first-party data is crucial for precise, personalized advertising, it isn’t always sufficient—especially for smaller or emerging brands that haven’t yet amassed audience data. Third-party data plays a pivotal role in these scenarios by supplementing first-party insights, offering a broader view of consumer behavior, leading to new growth opportunities. Viant collaborates with partners like Experian to help marketers seamlessly merge their customer information with additional consumer insights. Viant and their clients benefit from Experian's identity data to match various identifiers such as hashed emails, device IDs, or other platform-specific tags and map them back to a single consumer profile. With a unified view of the consumer, marketers can refine targeting, expand their reach, and maintain consistency across channels. By utilizing first- and third-party data solutions, marketers can build well-rounded, effective campaigns that resonate with diverse audiences. “Our clients have embraced the Viant Household ID because it powers a comprehensive, seamless flow from segment creation to targeting, activation, and measurement.” Tom Wolfe, SVP Business Development, Viant CTV as a core marketing channel CTV is emerging as the core platform for immersive and effective advertising by merging the visual storytelling power of traditional TV with the precision of digital tools. Viant helps marketers optimize CTV capabilities by building connections between premium publishers and data, allowing marketers to personalize experiences. Whether it’s tailored ads for families watching a live sports event or pinpointing niche interests, CTV enables marketers to reach diverse audiences with meaningful ads. Beyond awareness, Viant drives results for their clients and monitors that performance across each stage of the funnel. Marketers can use the key insights to optimize their media buys on CTV and achieve even higher ROI. Viant takes CTV performance a step further with its direct access programs. Stronger data matching via publisher partnerships improves accuracy, helping marketers connect with their ideal audience. Viant’s recent data shows that campaigns incorporating CTV achieve a conversion rate of 12.89%, outperforming campaigns lacking it by a wide margin. This dramatic improvement highlights the power of precise targeting combined with Viant’s advanced CTV tools. For marketers, this translates to impactful storytelling supported by tangible results. “CTV drives high-level brand awareness via sight, sound, motion, and emotion, but it also powers activity through the funnel.” Tom Wolfe, SVP Business Development, Viant AI is streamlining marketing from start to finish AI is transforming advertising by automating tasks like performance tracking and audience segmentation, allowing marketers to focus on strategy and creativity. At Viant, AI is part of the company’s DNA, helping marketers drive more efficient and effective campaigns. With real-time data insights and streamlined processes, teams can quickly refine messaging and optimize budgets. This efficiency not only saves time but also empowers marketers to channel their energy into creating impactful strategies that resonate with their audiences. The integration of AI into Viant’s ecosystem also simplifies overall workflows, optimizing campaign execution from start to finish. With performance tracking made easier and segmentation automated, marketers can rely on data accuracy and actionable insights to make confident decisions. How Experian and Viant work together Experian's syndicated audiences—demographic, auto, TV, FLA (Financial Fair Lending Act), and more—are available within Viant's platform. Experian's partnership with Viant enables the deployment of custom audiences specifically designed to meet distinct campaign objectives. Together, Experian and Viant provide solutions that support first-party data strategies, third-party data integration, CTV optimization, AI-driven insights, and identity resolution, creating a cohesive and privacy-forward marketing ecosystem. “At Viant, we focus on the sensible, scalable, impactful opportunities.” Tom Wolfe, SVP Business Development, Viant Watch the full Q&A Visit our Ask the Expert content hub to watch the full conversation with Tom and Ali and learn more about Viant’s scalable identity solutions. Contact us About our expert Tom Wolfe, SVP Business Development, Viant As SVP of Business Development at Viant, Tom and his team forge strategic business partnerships that fuel the company's growth and business strategy. He is a seasoned industry veteran with more than 25 years of expertise in content distribution, advertising, and technology, particularly in CTV. Throughout his career, Tom has played a pivotal role in establishing and managing multiple businesses at major companies such as Roku, TiVo, YuMe, and Comcast. Additionally, he has provided valuable advisory services to organizations including VIZIO, Vice Media, and many others across the ecosystem. Tom holds a B.A. in Political Science from Lehigh University and has shared his knowledge as a guest lecturer at both New York University and Drexel University. Latest posts