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
Marketing without segmentation is a lot like shouting into a crowded room and hoping the right person hears you. Without a clear way to communicate in a noisy marketing environment, your message gets lost in the mix. With segmentation, you can identify your target audience, speak to their needs, and deliver the right message at the right moment. Companies that use segmentation are 130% more likely to understand customer motivations, resulting in more effective campaigns and deeper audience relationships. In this article, we’ll break down four of the most effective customer segmentation methods, when to use each, and how Experian’s audience solutions can help. What is segmentation in marketing? Segmentation is the process of splitting a large audience into smaller groups that share similar traits, like demographics, location, behavior, or firmographic characteristics. As a marketer, these segments enable you to choose channels, messaging, and offers that resonate with each group. Whether you’re targeting new homeowners in Texas, loyalty shoppers in retail, or small business decision-makers in finance, segmentation helps you stand out to them and get results. Why should marketers segment their audiences? Effective audience segmentation fuels accuracy, performance, and personalization at scale. Here\’s why you should invest your time and marketing budget in honing your audience segments. Maximize your marketing ROI Nobody wants to waste money talking to the wrong crowd. Using various methods of segmentation, you can focus on those who want to hear from you — and the payoff can be huge. For marketing channels like email, segmentation can drive up to 760% more revenue than non-segmented campaigns. The more targeted your message, the better the return. Create a unified omnichannel strategy Segmentation helps ensure that every channel, from email and social media to display, SMS, and direct mail, operates from the same playbook. Once you define your target audience segments, you also need a trusted identity partner to sync them across platforms and environments. This ensures you can deliver consistent, personalized experiences at every touchpoint and your audience receives the same message in the proper context, regardless of where they engage. Strengthen customer loyalty Roughly 75% of consumers are loyal to brands that “get” them. When you strive to understand your customers, they’re more likely to stay. Segmentation enables you to personalize communications based on your target segment’s values, behaviors, or preferences, encouraging repeat business. Expand into new markets With segmentation, you can analyze existing customers to identify common traits and use that data to pinpoint similar groups in new regions or markets. For example, if your top customers are middle-class parents in suburban areas, you can target lookalike segments in other cities with tailored messaging. This makes it easier to expand with confidence, knowing you\’re reaching people who are more likely to convert. Lower customer acquisition costs Rather than forcing you to cast a wide net, segmentation enables you to focus your budget on high-potential audiences across channels, reduce acquisition costs, and minimize wasted spend on low-intent audiences. Four segmentation methods and examples Let’s look at four different methods of market segmentation. We’ll define each, share when to use them, and give real-world examples to help you apply them. 1. Demographic segmentation Demographic segmentation breaks your audience into groups based on gender, income, age, education, marital status, occupation, and household size. It’s one of the most foundational segmentation methods because it’s easy to implement and often tied directly to buying behavior. Demographic data makes it easier to get the tone, offer, and channel right from the start. And when you combine demographic segmentation with other segmentation methods, such as behavior or location, the impact multiplies. When to use it Use demographic segmentation when your product or service is clearly more relevant to people in a specific life stage, income bracket, or household type. Among all methods of market segmentation, demographic data is often the easiest starting point. It’s especially effective for industries such as financial services, healthcare, education, retail, and others, where consumer needs change based on demographics. Examples As a real-world example, a health supplement company used Experian data to segment its ambassador program audience into four demographic groups based on lifestyle and household makeup. These included younger singles, value-seeking families, high-income spenders, and older empty nesters. Applying these insights at registration allowed the brand to deliver personalized, channel-specific communications that boosted acquisition and retention. The approach led to stronger engagement and more meaningful customer connections. 2. Geographic segmentation This method of market segmentation categorizes people by location, including country, region, state, city, zip code, or even climate. It’s a simple yet effective way to tailor your marketing, as location often influences everything from lifestyle and language to shopping habits and product needs. It’s most often used among brands with physical locations or region-specific campaigns. Whether you\’re promoting snow boots in Colorado or sunscreen in California, geographic segmentation helps you stay relevant to the local context. When to use it Geographic segmentation is ideal when your offer or message changes depending on climate, culture, availability, or local regulations. It’s also helpful for planning market expansion or testing the performance of different methods of market segmentation across regions. Examples One home furnishings retailer partnered with Experian to understand how customer needs varied across store locations. Using a mix of client data and Experian demographics, we segmented stores based on their surrounding customer base, like urban, white-collar shoppers in metro centers versus lower-income households in more remote cities. These insights enabled the retailer to tailor inventory, marketing strategies, and ad copy for each store type, resulting in more relevant customer experiences. 3. Behavioral segmentation Behavioral segmentation centers on how people live their lives — their interests, habits, and decision-making patterns. It includes factors like past purchases, engagement frequency, brand loyalty, product usage, browsing patterns, and responsiveness to offers or promotions. Among all of the segmentation methods, this one provides insight into intent, helping you go beyond who your audience is to understand what they do. You can use behavioral insights to re-engage former customers with relevant offers, reward loyal buyers with personalized perks, or guide high-intent shoppers toward conversion with timely nudges. When to use it Behavioral segmentation is best when you want to personalize based on intent, habits, or engagement stage. It\’s particularly useful for retention, reactivation, or cross-selling strategies. Examples In practice, a national big-box retailer partnered with Experian to better understand customer behavior during grocery store visits. The goal was to identify distinct “trip missions” that could drive category trial and increase basket size. We analyzed everything from basket contents to customer composition and segmented visits into 11 unique missions. For example, the “All Aisles Online” segment represented large households (often homeowners with families) stocking up on household staples through online orders. In contrast, the “Marketable Mission” segment captured smaller, likely renter households making quick trips for non-essentials. These behavioral insights empowered the retailer to adjust promotions based on the intent behind each visit, strengthen customer relationships, and drive growth. 4. Firmographic segmentation (B2B) Firmographic segmentation is like demographic segmentation for businesses. It groups B2B audiences based on attributes such as annual revenue, location, company size, industry, and organizational structure. You can also segment by job title or decision-maker role to better target key stakeholders. This method is great for aligning your messaging, sales strategy, or product offerings with the unique needs of various business types. A startup in the tech sector will likely respond to a very different pitch than an enterprise manufacturer, and firmographic data helps you speak to both with precision. When to use it Use firmographic segmentation when marketing to other businesses, especially when your product or service has different benefits depending on business size or sector. Examples Recently, a B2B client partnered with Experian to gain a deeper understanding of the revenue potential of their existing business customers. Using firmographic data, we segmented the client’s customers into distinct groups based on the characteristics most strongly tied to spending behavior. For each segment, we calculated potential spend, defined as the 80th percentile of annual spend within that segment. This allowed the client to identify high-value accounts with untapped growth potential. For example, one customer, ABC Construction, had spent $4,750. But based on their segment’s profile, their annual potential was $9,000. That insight revealed a $4,250 opportunity to deepen the relationship through more targeted marketing and sales efforts. Best practices for market segmentation Regardless of the segmentation method you use, the following best practices will help you maximize the benefits of your efforts. Start with clean, reliable data Segments are only as good as the data behind them. If your data is outdated, inaccurate, or incomplete, your segments will result in ineffective targeting and a wasted budget. Utilize accurate, compliant, up-to-date sources like Experian Marketing Data, ranked #1 in accuracy by Truthset, to ensure your targeting is on point. Test and refine segments continuously Business goals, market conditions, and behaviors are constantly changing. What worked last month or even last week might not work today. By adjusting your segments over time, you make sure your marketing stays relevant, focused, and effective. Use A/B testing, performance metrics, and audience analytics to iterate on your segments and improve results over time. Align segments with personalized messaging and offers Each segment has distinct needs, preferences, and motivations, which means generic messaging won’t resonate effectively. Once you’ve built your segments, personalize your creative, copy, and offers to appeal to each group and increase the likelihood of engagement and conversions. Integrate segmentation across all platforms If someone sees one message in an email and a completely different one in an ad or on your website, it creates confusion and weakens trust. From CRMs and email platforms to ad tech and analytics tools, make sure your segmentation method is applied consistently across every channel to improve performance and build a cohesive brand experience. Segment your audiences with Experian Effective audience segmentation is at the heart of every successful marketing strategy, but in this fragmented, privacy-conscious landscape, grouping your audience into meaningful, actionable subgroups is more challenging than ever. That’s where we come in. With coverage of the entire U.S. population, Experian helps marketers define and categorize broad audiences into precise segments using rich data on demographics, behaviors, financial profiles, and lifestyle traits. These insights make it easier to personalize messaging, optimize media spend, and drive better outcomes. From ready-to-use syndicated audiences to custom segments and even Contextually-Indexed Audiences that align targeting with content, Experian offers flexible segmentation solutions that perform across digital, TV, programmatic, and social channels. In our most recent release, we introduced over 750 new and updated audience segments across key categories, including a brand-new category for Experian, giving marketers more accurate, behavior-based targeting options than ever before. 135+ new CPG audiences, a brand-new category for Experian, built from opt-in loyalty card and receipt scan data 240+ new automotive audiences covering ownership and in-market shoppers 100+ new high-spending behavior audiences focused on specific merchant categories 24 new wealth and income segments with refined household net worth tiers 13 new lifestyle-based housing audiences for family- and household-focused targeting 250+ refreshed financial segments with improved naming conventions for better discoverability and clarity Together, these segments give marketers more accuracy to reach high-intent consumers based on real-world behaviors, spending patterns, and financial capacity. Audience solutions powered by consumer insights Experian Marketing Data, one of the most comprehensive and accurate consumer databases in the U.S., is the core of our segmentation capabilities. Backed by over 5,000 demographic and behavioral attributes, it helps you understand not just who your customers are but how they live, shop, spend, and engage, too. Each audience segment is built with privacy and precision in mind, using a blend of demographic data, financial behaviors, lifestyle signals, and media habits. With these consumer insights, we’ll help you uncover meaningful patterns that lead to smarter strategy. Experian’s pre-built audiences Our syndicated audiences are pre-built, ready-to-activate segments based on shared characteristics from age and income to purchase behavior and lifestyle indicators. When speed and scale are a priority, these segments offer a fast, effective way to reach your target audience. Experian’s 2,400+ syndicated audiences are available directly on over 30 leading television, social, and programmatic advertising platforms, as well as within Audigent for activation within private marketplaces (PMPs). Here’s what’s new from our August 2025 release: CPG shoppers by category (e.g., Frozen Food Shoppers, Multi-Vitamin Shoppers) Luxury EV owners and auto brand shoppers (e.g., Rivian, Polestar, Cadillac) High spenders in specific categories (e.g., men\’s grooming and women\’s accessories) Ultra high-net-worth households (e.g., Net Worth $50M+) and likely home sellers Young Family Homeowners and Growing Family Apartment Renters Custom audiences for specialized targeting Need a custom audience? Reach out to our audience team, and we can help you build and activate an Experian audience on your preferred platform. Additionally, work with Experian’s network of data providers to build audiences and send to an Audigent PMP for activation. Contextually-Indexed Audiences Experian’s Contextually-Indexed Audiences offer a privacy-safe way to reach relevant consumers in the moments that matter without relying on identity signals or third-party cookies. These segments combine Experian’s consumer insights with page-level content signals, enabling you to align targeting with intent and mindset, even in cookieless or ID-constrained environments. Want to take your segmentation strategy to the next level? Let’s talk. We’ll help you define your audience in ways that drive real results. Talk to our team about your segmentation methods today Latest posts
Healthcare and Life Sciences teams map the patient journey to spot care gaps and guide interventions. However, clinical records cover only what happens inside clinics, not the forces driving patient decisions. Enriching these records with lifestyle, socioeconomic, and consumer-behavior insights reveals the “why” behind health outcomes. That’s where non-clinical insights step in – revealing the real-world forces that shape patient results. To address these blind spots, Experian and Komodo Health have teamed to integrate de-identified insights from millions of patient journeys with Experian’s socioeconomic and lifestyle data. This enriched view lets enterprises see each journey in full, identify care disparities, and craft smarter strategies – while rigorously protecting privacy. Driving tangible outcomes and better patient care This collaboration focuses on turning insights into action. With Experian and Komodo\’s integrated clinical, socioeconomic, and lifestyle data, Healthcare and Life Sciences teams can move from insight to accuracy, building adherence programs, finding hard-to-reach patients, and demonstrating treatment success. They can: Layer Komodo’s de-identified patient-level medical and pharmacy insights and analytics with Experian lifestyle and socioeconomic attributes Segment patient populations by condition, treatment history, and socioeconomic status Prioritize outreach – reducing waste and focusing resources where care is needed most For instance: Neighborhood-level gaps Identify opportunities to capture untreated patients and improve clinical trial inclusion. Income-related support Flag populations most likely to benefit from cost-saving programs, ensuring communications highlight co-pay assistance or financial relief options. Inside the data stack At the core of Komodo Health\’s AI-enabled healthcare analytics platform is its Healthcare Map®. This innovative tool integrates de-identified patient-level medical and pharmacy claims data from the patient journeys of over 330 million unique individuals – providing insights on diagnoses, treatments, outcomes, and care patterns across the United States. Experian enhances this data by adding socioeconomic and lifestyle characteristics that influence up to 80% of health outcomes. Together, this combined data effectively addresses essential questions such as: Which neighborhoods face the highest diabetes risk? Where is therapy abandonment spiking? When should co-pay assistance messages drop? How can we accelerate HCP outreach or clinical-trial recruitment? Experian\’s socioeconomic and lifestyle insights: Fueling data-driven care decisions In this context, Experian provides valuable insights into socioeconomic factors and lifestyle patterns, covering everything from household composition and income ranges to psychographics and other attributes that help build a broader understanding of an individual\’s circumstances. Where deep patient understanding, health engagement, and real-world evidence converge As healthcare marketing, patient engagement, and real-world data converge, the Experian and Komodo collaboration is empowering Healthcare and Life Sciences teams with fast, actionable insights. Fusing de-identified patient-level clinical data with socioeconomic and lifestyle attributes helps teams engage the right patients, and fuels research from product launches to community programs. It elevates experiences while proving impact with real-world evidence. Ready to utilize these insights? Latest posts
Brand and tech leaders share insights to guide marketers forward Cannes Lions 2025 brought its usual charm, rosé, and lively discussions, but what stood out was a shift in tone: brand and tech leaders aren’t talking in theories anymore – they’re rebuilding how advertising works. From identity to outcomes, the consensus was clear: marketers need bold, structural changes to thrive. At Experian, we spoke with leaders from Ampersand, Butler/Till, Comcast Advertising, Fox, OpenX, Optable, Snowflake, VideoAmp, and Yieldmo. Their message? Foundational change, not incremental tweaks, is the way forward. Here are five moves marketers and CMOs should be making right now. 1. Make identity the foundation, not an add-on Identity must be the core of your marketing strategy, not an afterthought. Building a strong identity framework from the outset ensures that your data and tech stack work seamlessly across channels. This means investing in first-party data assets and identity resolution tools that inform every campaign and tactic. Identity isn’t just a feature; it’s the base layer of everything successful marketers do today. \”There’s no AI strategy without a data and identity strategy. Marketers who want to stretch every media dollar and personalize each touchpoint need a unified, deeper view of the consumer – insight they can carry straight into downstream ad platforms.”David Wells, Snowflake Next step: Treat identity resolution as a prerequisite to every campaign, not a task to address later. Align your data management platform (DMP), customer data platform (CDP), and collaboration partners around a unified identity spine (Experian’s or your own) to ensure data flows uninterrupted from planning to reporting. 2. Curate, don\’t automate. Programmatic is getting personal Programmatic advertising remains relevant, but its purpose is evolving from mere automation to intelligent, data-driven curation. This shift requires moving beyond static site lists to dynamic, page-level contextual engines that determine, in real-time, which impressions to display. Today, it’s about carefully selecting and curating inventory to ensure transparency, quality, and relevance for your audience. Marketers are increasingly turning to private marketplaces (PMPs) that offer curated, brand safe inventory and clear supply paths to deliver meaningful results. Expect continued growth in curated PMPs, AI-assisted forecasting, and supply-side innovations that combine premium connected TV (CTV) inventory with deterministic data. The goal is to reach the right viewer and understand exactly how and why they got there. “What we’re talking about right now is almost like curation 2.0, which is bringing more of the capabilities that historically sat with the demand-side platform (DSP) into the hands of the supply-side platform (SSP) – that is, supply-side targeting, or what we call data-driven curation.\”Matt Sattel, OpenX Next step: Audit your supply chain. If you can’t clearly explain every step from bid request to delivery, explore curated deals or direct SSP partnerships that align with your quality and transparency standards. 3. Connect teams like you connect data Fragmented results often stem from fragmented teams. Persistent silos (like TV buys on one floor, digital on another, and data science somewhere else) slow down budgets and create inconsistent messaging. Forward thinking organizations are restructuring teams around unified KPIs and shared data. When planners, buyers, and analysts work together (or at least share dashboards), campaigns move faster and creative stays consistent. “We restructured our teams to focus on all forms of video – linear, streaming, and online. This allowed us to embrace partners who cross over these verticals and technical approaches.”Gina Whelehan, Butler/Till Next step: Map your current workflow end-to-end. Where does a brief stall or data stop flowing? Restructure teams or create shared success metrics to eliminate bottlenecks. 4. Turn disconnected data into unified insights Marketers have spent years gathering massive amounts of data, but hoarding data isn’t a winning strategy. The future belongs to those who can collaborate with partners to connect and utilize data effectively, all while respecting privacy and security. Rather than chasing the next data source, leading marketers are finding ways to safely connect data already available in-house or via partners. This might involve data clean rooms, secure data sharing agreements, or joint analytics initiatives – but the common thread is working together on data, not operating in isolation. “We\’ve been encouraging marketers to tie in first-party data and to really utilize that data and to work with trusted sources and deterministic sources in order to overcome a lot of the challenges around signal loss with cookies, in particular. The other way is also clean rooms. Clean rooms really enable the opportunity to collaborate in a private, safe way, and connecting to those more deterministic sources in order to deliver the results that advertisers are looking for.”Carmela Fournier, Comcast Advertising Next step: Identify gaps in your first-party data. Then, collaborate with a provider like Experian to safely match data sets and unlock insights without exposing sensitive info. 5. Focus on outcomes, not clicks Impressions, clicks, and other output metrics have been the currency of marketing for decades. But the consensus at Cannes is that those proxies aren’t enough – business outcomes are what matter now. Marketers must shift their focus to measuring real results, such as sales lift, new customer acquisition, lifetime value, or brand impact, rather than getting bogged down in intermediate metrics. This move to outcome-based measurement changes how campaigns are planned and judged: success is defined by the value created, not just the volume delivered. Unified, identity-based analytics are finally making it possible to see who saw an ad and what they did next, across TV, CTV, and digital. That intel drives smarter budget shifts and tighter creative feedback loops. “Outcome-based measurement is table stakes in today’s media ecosystem, and Ampersand has woven it into almost everything we do. Thanks to Experian’s strength in identity, audience insights, and outcome measurement, we can give advertisers the attribution they need at every stage of the funnel.”Justin Rosen, Ampersand Next step: Identify metrics that matter to your bottom line, then find a partner who can measure them accurately. If measurement stacks don’t talk to each other, they’re holding you back. Preparing for the challenges ahead The common thread across these five moves is connection – connecting data, teams, and outcomes. Marketers who act on these imperatives will be ready for whatever new screen, format, or privacy rule comes next. Experian can help you: Establish an identity spine Enable secure data collaboration in or out of clean room environments Curate premium CTV inventory with deterministic audiences Measure business outcomes across every channel Ready to make your next bold move? Let\’s start a conversation Latest posts