At A Glance
As CTV viewership grows, marketers face challenges in targeting and measurement across fragmented platforms. Identity resolution and audience strategies, supported by Experian’s syndicated audiences and privacy-safe solutions, help DSPs and advertisers reach high-value audiences, improve campaign accuracy, and drive measurable outcomes.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!
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FAQs
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.
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.
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.
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.
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With U.S. brands expected to invest over $28 billion in connected TV (CTV) in 2024, balancing linear TV and CTV is now a top priority. Advertisers need to integrate these platforms as the TV landscape evolves to reach audiences with various viewing habits. A successful strategy requires both linear and CTV approaches to effectively reach audiences at scale. We interviewed experts from Comcast Advertising, Disney, Fox, Samsung Ads, Snowflake, and others to gain insights on the evolving landscape of linear and CTV. In our video, they discuss audience fragmentation, data-driven targeting, measurement challenges, and more. Watch now to hear their perspectives. Five considerations for connecting with linear TV and CTV audiences 1. Adapt to audience fragmentation With consumers' rapid shift toward streaming, it's easy to overlook the enduring significance of linear TV, which still commands a large portion of viewership. According to Jamie Power of the Walt Disney Company, roughly half of the current ad supply remains linear, highlighting the need for brands to adapt their strategies to target traditional TV viewers and cord-cutters. As streaming continues to rise, ensuring your strategy integrates both CTV and linear TV is crucial for reaching the full spectrum of audiences. "I don't think that we thought the world would shift so quickly to streaming, but it's not always just all about streaming; there's still such a massive audience in linear."Jamie Power, Disney 2. Combine linear TV’s reach with CTV’s precision Blending the reach of linear TV with the granular targeting capabilities of CTV allows advertisers to engage both broad and niche audiences. Data is critical in understanding audience behavior across these platforms, enabling brands to create highly relevant campaigns tailored to specific audience segments. This strategic use of data enhances engagement and ensures that the right viewers see advertising campaigns. "The future of TV is really around managing the fragmentation of audiences and making sure that you can reach those audiences addressably wherever they're watching TV."Carmela Fournier, Comcast Advertising 3. Manage frequency across platforms Cross-platform campaigns require managing ad frequency to avoid oversaturation while ensuring adequate exposure. With a variety of offline and digital IDs resolved to consumers, our Digital and Offline Graphs can help maintain consistent messaging across linear TV and CTV. This approach allows advertisers to strike the right balance, preventing ad fatigue and delivering the right audience reach for campaign impact. "You've got to make sure that you're not reaching the same homes too many times, that you're reaching everybody the right amount of times."Justin Rosen, Ampersand 4. Focus on consistent measurement Linear TV and CTV offer different data granularities, necessitating tailored approaches for accurate cross-platform campaign measurement. Bridging these data gaps requires advanced tools that streamline reporting for both mediums. As the industry moves toward consistent measurement standards, advertisers must adopt solutions that provide a comprehensive view of campaign performance, enabling them to optimize their cross-platform efforts. "Where I think there are pitfalls are with the measurement piece, it's highly fragmented, there's more work to be done, we're not necessarily unified in terms of a consistent approach to measurement."April Weeks, Basis 5. Align with shifts in audience behavior The success of cross-platform campaigns hinges on staying agile and responsive to shifting audience preferences. As CTV adoption grows, advertisers must proactively adjust their strategies to align with how viewers engage across linear and streaming platforms. Ideas include: Regularly updating creative Adjusting the media mix Utilizing real-time data insights to ensure campaigns remain relevant "At Fox we were a traditional linear company, and essentially what we're trying to do is merge the reach and the scale of TV as well as the reach and the scale of all the cord-cutters and cord-nevers that Tubi possesses." Darren Sherriff – FoxDarren Sherriff, Fox As streaming TV rapidly changes, brands must stay ahead of trends and shifts in consumer behavior to tap into CTV's growing potential. By focusing on these opportunities, advertisers can blend linear TV and CTV, ensuring their campaigns reach audiences wherever they watch. Connect with Experian's TV experts As a trusted leader in data and identity services, Experian offers the expertise to help you succeed in television marketing. With our strong partnerships with key players in the TV industry, we provide access to unique marketing opportunities. Learn how Experian’s data and identity solutions can deliver outstanding results in advanced TV advertising. Partner with us today to enhance your marketing strategies using our Consumer View and Consumer Sync solutions. Connect with our TV experts Contact us Latest posts
In this article…Understanding the AI revolution in commerceFour benefits of the AI revolution coming to commerceFuture trends and predictionsChart the future of commerce with Experian Technology is pushing the boundaries of commerce like never before. Artificial intelligence (AI) is one of the primary driving technologies at the forefront of the commerce evolution, using advanced algorithms to revolutionize marketing and personalize customer experiences. As of 2024, AI adoption in e-commerce is skyrocketing, with 84% of brands already using it or gearing up to do so. This article explores the AI revolution coming to commerce, focusing on what makes AI a driving force for e-commerce in particular, and the ways it's reshaping how businesses engage with consumers. Understanding the AI revolution in commerce AI is quickly reshaping commerce as we know it by democratizing access to sophisticated tools once reserved for large corporations, breaking down functional silos within organizations, and integrating data from multiple sources to achieve deeper customer understanding. It’s paving the way for a future where every brand interaction is uniquely crafted for the individual, powered by AI systems that anticipate preferences proactively. AI is a broad term that encompasses: Data mining: The gathering of current and historical data on which to base predictions Natural language processing (NLP): The interpretation of human language by computers Machine learning: The use of algorithms to learn from past experiences or examples to enhance data understanding The capabilities of AI have significantly matured into powerful tools that can improve operational efficiency and boost sales, even for smaller businesses. They have also fundamentally changed how businesses interact with customers and handle operations. As AI continues to develop, it has the potential to provide even more seamless, personalized, and ethically informed commerce experiences and establish new benchmarks for engagement and efficiency in the marketplace. Four benefits of the AI revolution coming to commerce Major commerce players like Amazon have benefited from AI and related technologies for a while. Through machine learning, they’ve optimized logistics, curated their product selection, and improved the user experience. As this technology quickly expands, businesses have unlimited opportunities to see the same efficiency, growth, and customer satisfaction as Amazon. Here are four primary benefits of AI adoption in commerce. 1. Data-driven decision making AI gives businesses powerful tools to analyze large amounts of data more quickly and accurately than a person. Through advanced algorithms and machine learning, AI can sift through historical sales data, customer behavior patterns, and market trends to uncover insights and suggest actions that might not be immediately obvious to human analysts. By transforming raw data into actionable insights, AI empowers businesses to make more informed decisions, reduce risks, and capitalize on opportunities. As a real-world example, Foxconn, the largest electronics contract manufacturer worldwide, worked with Amazon Machine Learning Solutions Lab to implement AI-enhanced business analytics for more accurate forecasting. This move improved forecasting accuracy by 8%, saved $533,000 annually, reduced labor waste, and improved customer satisfaction through data-driven decisions. 2. A better customer experience AI is set to make customer interactions smoother, faster, and more personalized by recommending products based on preferences and behaviors, making it easier for customers to find what they need. When consumers visit an online store, AI also provides instantaneous help via a chatbot that knows their order history and preferences. These AI-powered assistants offer real-time help like a knowledgeable store clerk. They give the appearance of higher-touch support and can answer basic questions at any hour, provide personalized product recommendations, and even troubleshoot issues. Chatbots free up human customer service agents for more complicated matters, and these agents can then use AI to obtain relevant information and suggestions for the customer during an interaction. 3. Personalized marketing Data-driven personalization of the customer journey has been shown to generate up to eight times the ROI, as data shows 71% of consumers now expect personalized brand interactions. Until AI came around, personalization at scale was complex to achieve. Now, gathering and processing data about a customer’s shopping experience is easier than ever based on lookalike customers and past behavior. Many businesses have adopted AI to glean deeper insights into purchase history, web browsing, and social media interactions to drive better segmentation and targeting. With AI, advertisers can analyze behavioral and demographic data to suggest products someone is likely to love. Consumers can now browse many of their favorite online stores and see product recommendations that perfectly match their tastes and needs. AI can also offer special discounts based on purchasing habits, and send personalized emails with products and content that interest customers to make their shopping experience more engaging and relevant. This personalization helps businesses forge stronger customer relationships. Personalization across digital storefronts Retail media involves placing advertisements within a retailer's website, app, or other digital platform to help brands target consumers based on their behavior and preferences within that environment. Retail media networks (RMNs) expand this capability across multiple retail platforms to create seamless advertising opportunities throughout the customer journey. Integrating AI into RMNs can improve personalization across digital storefronts with personalized, relevant ads and custom offers in real time that improve the customer experience. 4. Operational efficiency AI can also be beneficial on the back end, enabling more efficient resource allocation, pricing optimization, efficiency, and productivity. Customers can be frustrated when they visit a store for a specific product only to find it out of stock or unavailable in a particular size. With AI, these situations can be prevented through algorithms that forecast demand for certain items. Retailers like Amazon and Walmart both use AI to predict demand, with Walmart even tracking inventory in real time so managers can restock items as soon as they run out. AI can automate and streamline operational tasks to help businesses run smoother, faster, and more cost-effective operations. It can: Offload tedious data entry, scheduling, and order processing tasks for greater fulfillment accuracy. Analyze historical data and market trends, predicting demand to help businesses optimize inventory, reduce waste, track online and in-store sales, and prevent shortages. Forecast demand levels, transit times, and shipment delays to make better predictions about logistics and supply chains. Improve data quality using machine learning algorithms that find and correct product information errors, duplicates, and inconsistencies. Adjust prices based on competitor pricing, seasonal fluctuations, and market conditions to maximize profits. Pinpoint bottlenecks, identify issues before they escalate, and provide improvements for suggestions. Future trends and predictions If you want to stay ahead in e-commerce, it’s just as important to know what’s coming as it is to understand where things are today. Here are some of the trends expected to shape the rest of 2024 and beyond. Conversational commerce Conversational commerce allows real-time, two-way communication through AI-based text and voice assistants, social messaging apps, and chatbots. Generative AI advancements may soon enable more seamless, personalized interactions between customers and online retailers. This technology can improve customer engagement and satisfaction while providing helpful insights into preferences and behaviors for better personalization and targeting. Delivery optimization AI-driven delivery optimization uses AI to predict ideal routes for each individual delivery, boosting efficiency, reducing costs, promoting sustainability, and improving customer satisfaction throughout the delivery process. Visual search AI-driven visual search is quickly improving in accuracy, speed, and contextual understanding. Future developments may integrate seamlessly with augmented reality (AR) so shoppers can search for products by pointing their devices at physical objects. Social media and e-commerce platforms may soon incorporate visual search more prominently, allowing users to find products directly from images. AI content creation AI is already automating and optimizing aspects of content production: Algorithms can generate product descriptions, blog posts, and social media captions personalized to specific customer segments. AI tools also enable the creation of high-quality visuals and videos. NLP advancements ensure content is compelling and grammatically correct. AI-driven content strategies analyze consumer behavior and refine messaging to meet changing preferences and trends. This automation speeds up content creation while freeing resources for strategic planning and customer interaction. IoT integration Integrating AI with Internet of Things (IoT) devices could help make the ecosystem more interconnected in the future. AI algorithms can use data from IoT devices like smart appliances, wearables, and sensors to gather real-time insights into consumer behavior, preferences, and product usage patterns. This data enables personalized marketing strategies, predictive maintenance for products, and optimized inventory management. AI-driven IoT data analytics can also streamline supply chain operations to reduce costs and inefficiencies. Fraud detection and security There will likely be an increased focus on the ethical use of AI and data privacy regulations to strengthen consumer trust and transparency. AI-powered systems will get better at detecting and preventing fraud in e-commerce transactions, which will heighten security measures for both businesses and consumers. Chart the future of commerce with Experian AI has changed how marketers approach e-commerce in 2024. With AI-driven analytics and predictive capabilities, marketers can extract deeper insights from extensive data sets to gain a clearer understanding of consumer behavior. This enables refined segmentation, precise targeting, and real-time customization of messages and content to fit individual preferences. Beyond insights, AI automates routine tasks like ad placement, content creation, and customer service responses, freeing marketers to concentrate on strategic planning and creativity. Through machine learning, marketers can predict trends, optimize budgets, and fine-tune strategies faster and more accurately than ever. The time to embrace AI is now. At Experian, we’re here to help you make more data-driven decisions, deliver more relevant content, and reach the right audience at the right time. Using AI in your commerce marketing strategy with our Consumer View and Consumer Sync solutions can help you stay competitive with effective, engaging campaigns. Contact us to learn how we can empower your commerce advertising strategy today. Contact us 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 Rachel Herbstman, VP of Data Innovation, and Anastasia Dukes-Asuen, Senior Director of Advanced TV Data & Insights at Ampersand. Could you introduce us to Ampersand and discuss your approach to TV advertising? Ampersand, a joint venture between Comcast, Charter, and Cox, is a media sales organization that offers a unified footprint, unlocking unparalleled scale and unique data/insights for local and national advertisers. Ampersand gives advertisers true audience first planning, scale in execution, and advanced measurement of their TV investments, representing 117 million multiscreen households and over 75% of addressable households in the U.S. (64 million households). We help clients reach their unique target audience and deliver their stories – anytime, anywhere, and on whatever device. How does adding streaming to a linear campaign, or vice versa, enhance overall campaign performance for marketers? Herbstman: Marketers have recognized that multiscreen media strategies are the strongest as viewership continues to fragment. Unique audiences exist in traditional TV and streaming, and failure to include either media channel will reduce the total reach opportunity. These channels have proven to validate unduplicated audiences. In our local business, adding streaming to a historically traditional linear-only media strategy increased campaign reach by 33%. Conversely, adding linear TV to a historically streaming-only media strategy increased reach by 209%. These metrics are validated by matching media exposures to an authenticated households subscriber ID and represent mass opportunities to reach new audiences with a multiscreen media strategy. When considering reallocating media investments, how does Ampersand help clients determine the most effective channels for specific campaigns? Herbstman: For a brand that historically invested in traditional TV, either national or local broadcast, we can provide insights to analyze the performance of any media campaign. The insights can include high-level metrics like reach and frequency and more granular metrics like unique reach per network. By seeing both the high-level results and more detailed granularity, we can provide optimization recommendations for funding other activation opportunities. Our database of past campaigns consistently demonstrates that gaining new eyeballs with a national TV campaign usually plateaus after a few weeks. In other words, if most of your intended audience is reached after about three or four weeks of national television, reaching any new viewers can be exponentially more expensive. We’ve built an Addressable Simulator tool for national advertisers that shows the potential impact of shifting a portion of the national media weight, specifically from the latter part of a flight, into addressable TV. Using our licensed Experian data set, we can measure any standard age/gender target or any advanced target to understand the complementary impact that addressable audience has on national media. This tool has dynamic inputs of CPMs and incidence rates, flight lengths, and budgets to simulate different scenarios and give marketers some intelligence on what holistic reach against that Experian segment they could expect with one given budget using brand-safe, traditional, and streaming inventory with an addressable activation. Additionally, we've developed an interactive eCPM calculator that helps national advertisers assess the cost efficiency of adding addressable TV to their traditional campaigns. By dynamically inputting CPMs, marketers can evaluate tradeoffs between media types for upcoming campaigns. Are there audience demographics that benefit from these combined media strategies, and what indicators or data points guide your recommendations to add cable to a local broadcast campaign versus other reallocations? Herbstman: By including cable or streaming in a local effort, a client can use a data-driven approach to find more intended viewers in other premium content. Utilizing the vast library of Experian audience segments paired with our robust sample of 64 million data-enabled homes enables Ampersand to provide insights into the most valuable networks and dayparts that the intended viewer will likely watch on either platform. With identity and viewing insights at scale, we can understand how consumers watch TV, even for inventory we have yet to sell. Our goal is to help marketers understand what’s happening as a result of their investments at a holistic level. We can analyze a campaign running across hundreds of designated market areas to quickly and simply understand the holistic delivery of their broadcast and cable weight by pulling back set-top-box exposures on broadcast and Ampersand-purchased cable on our measurable footprint. Then, we can determine the share of measurable reach that each portion’s media weight contributes to. We recommend optimizing towards a more balanced approach, where the reach levels for broadcast and cable mirror each other, creating a more effective market media mix. Once we confirm cable's potential in a market, we analyze network and daypart metrics to adjust key areas to optimize the campaign. We invite marketers to use these insights to measure their local or national TV campaign performance and garner unique perspectives to re-balance investments to drive reach and optimal frequencies. Are there common missteps to avoid? Dukes-Asuen: Ampersand's decades of experience with media and data insights have allowed us to create an extensive database complete with targeting and measurement benchmarks. We use this database to curate best practices for brands and help set them up for success, keeping their goals and objectives for reach and frequency in mind. Some clients spread their investment levels too thin, whether through short flight windows, low weekly frequencies, or targeting overly niche audiences that don't fully support KPI goals. One way to avoid these missteps is to set up a test-and-learn plan to validate a hypothesis and refine media strategies, ensuring campaigns are structured to garner meaningful insights. Ampersand can help ensure the test itself is constructed and supported to yield statistically relevant results, and the learnings can then be applied to the next campaign. How does Experian’s data enhance your campaigns at Ampersand? Dukes-Asuen: Within our Experian license, we can map the Experian Consumer View databases against our multichannel video programming distributors subscriber base in a privacy-compliant way to plan and activate them seamlessly. Experian has a rich set of audience targets and segmentation that we utilize to identify households that can be used for audience-based media execution with Ampersand. By defining the right audience—whether consumers are likely to purchase a product, exhibit certain behaviors, or demonstrate specific values—we enhance campaign performance and improve media spending efficiency for our advertisers. Additionally, how do you believe AI and other new technologies will impact your media buying approaches in the future, and how might these innovations improve campaign effectiveness and provide value to your clients? Herbstman: We have a strong use case on the measurement and analytics end. Using AI, we can aggregate a massive amount of historical data—viewership and exposure data. AI helps us understand overarching market trends and media performance to analyze campaign results and inform future campaign optimizations. The value of AI is in its role as an additional technology layer, enriching our insights portfolio and providing faster intelligence that enhances campaign effectiveness and delivers greater value to our clients. Can you share an example of how precise audience targeting and segmentation, powered by Experian, have led to significantly better media spend reallocations and campaign performance for marketers? One great example is how a national cruise brand dramatically improved its media spend and campaign performance by utilizing precise audience targeting and segmentation through Experian. By combining Ampersand’s addressable TV with Experian’s data-driven insights, they achieved a 14% incremental reach, a 3.1x higher frequency, and a 24% lower effective CPM. This strategic approach allowed them to reallocate their media spending more effectively, ensuring every impression reached their custom target audience. Thanks for the interview. For those interested in learning more about Ampersand, reach out for a personalized consultation. Contact us Latest posts