At A Glance
Reaching the right audience is becoming more challenging as digital advertising grows increasingly fragmented, and privacy regulations change. 33Across addresses this by providing real-time intent signals and contextual insights, helping marketers connect with consumers across devices like CTV, mobile, and desktop. Integration into Experian's marketplace makes these solutions more accessible, helping advertisers achieve measurable results.In our Ask the Expert Series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with Allison Dewey (Director, Data & Curation) at 33Across.
Navigating complexity in digital advertising
Digital advertising is more fragmented and privacy-constrained than ever. How is 33Across helping marketers cut through that complexity to drive real outcomes, and what makes your approach distinct?
Reaching audiences without compromising scale or performance is one of the toughest challenges for marketers. Users consume content across multiple devices and channels, making it difficult for marketers to identify and accurately target them with the right message. 33Across segments leverage AI-powered contextual and behavioral signals across privacy-safe environments to help marketers accurately identify audiences, whether they’re streaming content on their connected TV or researching products on their mobile device. What sets us apart is that we don’t just identify valuable audiences; we help marketers also target cookieless inventory and power it with real-time signals.

Marketplace integration milestones
What excites you most about bringing 33Across audiences into Experian’s data marketplace?
We’re excited to bring 33Across audiences into Experian’s data marketplace because it connects our unique segments with a powerful data ecosystem that marketers already trust. Buyers looking to activate audiences that are both privacy-safe and performant continue to tap into the Experian data marketplace for high-quality, high-performing data. We offer a wide range of audience verticals, including B2B, demographic, retail purchase data, interest and intent, and political data. In addition, we offer the ability to create custom segments across verticals.

Our intent-based audiences, built from contextual and engagement signals, help buyers reach consumers on CTV, desktop, or mobile devices with scale. Being part of Experian’s data marketplace accelerates access to these audiences, drives better ROI, and helps brands future-proof their strategies today.

Retail demand signals
Retail brands are racing toward privacy-safe, first-party data. Which 33Across retail datasets or segments are experiencing the highest demand, and what makes them a must-have?
Retail marketers are leaning into contextual and behavioral intent signals to complement their first-party data strategies. At 33Across, we’re seeing high demand for segments tied to shopping intent, including in-market consumers browsing for categories like fashion, home goods, electronics, and health & wellness.
What makes these segments essential is their real-time nature – they can capture consumer interest as it happens. For retail brands looking to expand their reach while respecting privacy, our segments offer scalable, actionable intent that drives results.

B2B without cookies
Reaching real B2B decision-makers at scale is tough with or without signals. How does 33Across deliver both precision and reach in this environment?
B2B marketing often struggles with balancing scale and specificity. 33Across addresses this by combining contextual precision with AI-modeled behavioral signals; this segment approach reaches professionals actively engaging with relevant content and topics, even in environments where IDs are unavailable. Marketers gain access to more signals and, in turn, better reach from 33Across’ unique publisher integrations and audience curation built from machine learning and AI.
We surface intent through content consumption patterns and contextual engagement, unlocking valuable, privacy-safe signals at scale. Allowing B2B marketers to reach real decision-makers in a signal-sparse world.

Use cases
With retail, B2B, and beyond, can you share an example of how brands in these verticals are utilizing your audiences?
Top brands that have a user-focused approach use 33Across audiences to drive scale; performance. These brands enable our segments to precisely reach the right users across devices and increase conversion rates; brand awareness. By reaching the right users, brands have higher conversion rates and increase campaign efficiency.

Supply path innovation
As identifiers disappear, advertisers are looking for scalable, privacy-safe ways to reach real people. How is 33Across helping unlock more addressable inventory and drive performance?
By combining contextual, semantic, and engagement-based signals, we deliver intent-based targeting that performs across CTV, display and video. Higher addressability helps marketers not only extend their reach but also deliver personalized messaging across digital channels in a privacy-compliant way.
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About our expert

Allison Dewey
Director of Data and Curation, 33Across
Allison Dewey is the Director of Data & Curation at 33Across, where she oversees data partnerships, integrations, and supply-side curation. With a deep expertise in audience targeting and signal optimization, Allison plays a key role in connecting data into the programmatic world. Allison holds a Bachelor’s degree in Psychology from Bates College.

About 33Across
Rooted in over 15 years of data expertise, 33Across harnesses signals to enrich and expand marketers’ audiences and reach them wherever they consume content. Built from over 300 billion proprietary data signals, we apply machine learning and AI to create over 1,500 B2C and B2B segments using privacy-first principles to reach audiences.
Cookieless targeting FAQs
By using contextual and engagement-based signals, advertisers can target consumers across CTV, mobile, and desktop in a privacy compliant way, even as identifiers become less available.
Segments tied to shopping intent, such as consumers browsing fashion, electronics, or health products, are highly sought after because they capture real time interest and drive results.
Combining content engagement patterns with machine learning allows marketers to reach professionals actively engaging with relevant topics, even in environments where IDs are unavailable.
Privacy safe targeting uses real time contextual and behavioral signals to deliver relevant messaging across devices and channels without compromising consumer trust.
Real time intent signals allow advertisers to capture consumer interest as it happens, helping demand side platforms and brands deliver timely, relevant ads that increase engagement and drive conversions across devices like CTV, mobile, and desktop.
Latest posts

In a perfect world, we’d all have a single, go-to grocery store that carried everything on our shopping list – fresh produce, gourmet coffee beans, rare spices, and maybe even that special-grade olive oil, right alongside our wholesale bulk purchases at unbeatable prices. It would be convenient and efficient, and it’d save a lot of driving around town. The changing data marketplace: From one-stop shop to specialized selection For a long time, data buyers enjoyed something similar in their world: a small set of large-scale data marketplaces that offered a wide array of audiences, making it easy to load up on whatever you needed in one place. Not only are there fewer places to pick everything up, but new factors like privacy and signal deprecation are placing a spotlight on quality and addressability. Just as our dinner plans are growing more ambitious insofar as we want health, flavor, value, and convenience all in one place – so are our data strategies. Instead of a single steak-and-potatoes meal, today’s data marketplace operators might be cooking up a complex menu of campaigns. As a result, data buyers are beginning to shop around. Some still rely on large-scale marketplaces for familiar staples, but now they have reasons to explore other options. Some are turning to providers known for offering top-tier, transparently sourced segments. Others are focusing on specialty providers that excel in one area. A more selective approach to data buying In this environment, choosing where to “shop” for data is becoming more deliberate and selective. Data buyers aren’t just thinking about broad scale; they’re looking to prioritize quality, durability, data privacy, and differentiation. They need to place higher value on data marketplaces that can maintain audience addressability over time, despite signal loss. Sometimes, that means accepting a smaller assortment in exchange for tighter vetting and more reliable targeting. Other times it means mixing and matching – stopping by one marketplace for premium segments and another for cost-friendly, wide-reaching data sets. Either way, they can benefit from having more choices. Experian’s marketplace: A trusted source for high-quality data Experian’s vetted and curated blend of data partners and vertically-aligned audiences offers a trusted specialty store for data buyers. Experian’s marketplace, powered by identity graphs that include 126 million households, 250 million individuals, and 4 billion active digital IDs, enables partner audiences to be easily activated and maintain high addressability across display, mobile, and connected TV (CTV) channels. In particular, Experian’s marketplace provides: Enhanced addressability and match rates All audiences delivered from the marketplace benefit from our best-in-class offline and digital identity graphs, which ensure addressability across all channels like display, mobile, and CTV. Unlike other data marketplaces, Experian ensures all identifiers associated with an audience have been active and are targetable, improving the accuracy of audience planning. Audience diversity and scale Access a broad range of audiences across top verticals from our partner audiences, which can be combined with one another and with 2,400+ Experian Audiences. The ability to join audiences across data providers ensures that buyers can build the perfect audience for the campaign. Trusted compliance and oversight With decades of experience, Experian is a trusted expert in data compliance. Our rigorous data partner review ensures available audiences comply with all federal, state, and local consumer privacy regulations. The future of data marketplaces: Precision and flexibility matter The evolution of data marketplaces reflects the industry's shifting priorities. Data buyers seek specificity, reliability, and adaptability to align with their diverse campaign needs. The best data strategy, much like the best grocery run, isn’t about grabbing everything in one place – it’s about carefully selecting the right ingredients to create the perfect recipe for success. This shift underscores the importance of flexibility and precision as data buyers navigate a landscape shaped by privacy regulations, signal loss, and evolving consumer expectations. As data marketplaces adapt to meet these demands, they are redefining what it means to deliver value. Experian’s marketplace enables buyers to strike the perfect balance between reach and quality by offering enhanced match rates, precise audience planning, and seamless distribution. In this new era, data buyers have the tools and options to craft campaigns that are impactful and aligned with the increasingly selective and privacy-conscious digital landscape. The key is recognizing that today’s data strategy is about utilizing the strengths of many to create a cohesive and effective whole. If you're interested in learning more about Experian's marketplace or becoming an active buyer or seller in our marketplace, please contact us. Contact us Latest posts

Conventional TV advertising campaigns have historically relied on general audience metrics like impressions and ratings to measure outcomes. These metrics can help marketers understand how many people have seen an ad, but they don’t reveal its real-world impact, which leaves a gap between ad exposure and results. Outcome-based TV measurement bridges this gap and helps marketers tie ad spending directly to their business goals. Instead of counting eyeballs alone, TV measurement zeroes in on what viewers do after seeing an ad — whether signing up for a service, visiting your website, or purchasing a product. TV ad measurement helps marketers adjust campaigns based on clear, trackable outcomes rather than guesswork. Let’s talk about how marketers can get started with outcome-based TV measurement and start experiencing tangible results. Why outcome-based TV measurement matters Outcome-based measurement indicates a massive shift in how marketers evaluate TV advertising success. As a principal analyst at Forrester explained, the industry is about to “move into a whole different world" where multiple metrics are tailored to advertisers’ unique goals, such as sales, store traffic, or web engagement. This shift is driven by improved tools for tracking TV outcomes, which help justify spending and clarify ROI. With TV measurement, you can see how your campaigns impact aspects of your marketing like sales and engagement. Aligning TV ad spend with business goals Every business has distinct objectives. Outcome-based measurement ties your marketing efforts to business goals and enables smarter decisions, campaign optimization, and ROI improvements. Whether you're a B2C brand wanting immediate sales or a B2B organization looking to drive website traffic, this method provides the insights needed for strategic decision-making. Marketers can deliver the most value by adjusting TV ad spending to maximize desired results: Sales goals: Identify which ads and platforms directly influence purchases to ensure TV ad spend contributes to revenue growth. Customer engagement: Link actions like website visits or app downloads to TV campaigns and refine messaging to deepen audience connections. Desired outcomes: Align ad spend with goals like consumer awareness or repeat purchases to allocate resources effectively for measurable success. Reducing wasted spend on ineffective channels Outcome-based TV measurement allows you to pinpoint which networks, times, or programs drive the most engagement and conversion. When you know your underperforming channels, you can reallocate budgets to those with a higher ROI and avoid waste. Core metrics in outcome-based TV measurement The effective implementation of outcome-based measurement requires advanced TV advertising analytics and tracking metrics that shed light on TV ad performance. Incremental lift This metric measures the increase in desired actions and business results — like purchases or site visits — that can be attributed directly to a TV campaign. Incremental lift quantifies your campaign’s impact and separates organic activity from the results your ads have driven. Let’s say a meal kit service experiences a 20% lift in subscriptions within a single week of running TV ads compared to a week without ads. They’d want to be able to isolate the impact of their ad from their organic growth so they can determine if the growth is actually a result of the TV ads or another effort. Attribution and conversions Attribution links TV ad exposure to specific customer actions, such as newsletter sign-ups and product purchases. Conversion data helps marketers understand the whole customer journey to optimize messaging, targeting, and channel mix to improve conversion rates. A retailer that knows 50% of TV ad viewers visit its e-commerce site within 36 hours of exposure could use that information to adjust the timing of its retargeting and align with site visit spikes. Audience segmentation for targeted measurement Outcome-based measurement breaks down performance across target demographics and allows for granular audience segmentation so TV ads resonate with the right audiences. For example, if a luxury brand saw better TV ad performance with high-earning Millennials, they’d want to refine their campaign messaging based on this group’s habits and preferences. Customer journey tracking Knowing how viewers move from awareness to conversion is critical. Outcome-based TV measurement helps you track the customer journey by pinpointing touchpoints where engagement happens and tying these to your TV campaigns. If a fitness brand found that TV campaigns drive app downloads, it could combine app analytics and TV exposure data to find out when most of their conversions happen after ad exposure and create follow-up messaging for that window of time. Integrating these insights with other marketing channels allows you to fine-tune your messaging, channel mix, and audience targeting to drive better outcomes and deliver more personalized customer experiences. Lifetime value (LTV) Beyond immediate conversions, outcome-based TV ad measurement helps brands identify which TV campaigns attract high-value customers with long-term revenue potential. If a financial institution ran a TV ad campaign centered on its new credit card, for instance, it could use LTV to track new cardholders and determine whether ads occurring during financial news airtime produced customers with higher average annual spend compared to other segments. How outcome-based TV measurement works Outcome-based measurement is a data-driven process that involves collecting, analyzing, and applying insights to improve TV ad performance. 1. Collect data When someone sees your TV ad, they might take action, like downloading your app or buying something. Outcome-based TV measurement begins by tracking these actions and gathering data from various sources, such as: TV viewership CRM Digital engagement Purchase behavior Cross-platform interactions And more Data integration with digital platforms Combining TV data with insights from platforms like social media or website analytics creates a more unified view of campaign performance. This integration powers easier retargeting and better alignment between digital and TV advertising strategies. Some marketers enhance this integration further using artificial intelligence (AI) to streamline data coordination and ensure campaigns are optimized for effectiveness and ROI. 2. Connect the dots Next, marketers need to find out which actions were influenced by TV ads. It’s important to ask questions like these as you work to connect the dots: Did website traffic spike right after the ad aired? Did the ad viewers match the people who signed up for the service or made a purchase? You can link TV exposure to real-world behaviors with tools and identifiers like hashed emails, device IDs, surveys, and privacy-safe data-matching techniques. 3. Analyze the data Then, the data needs to be analyzed for patterns like these: Which TV ads or time slots drove the most engagement? Did certain customer groups respond better than others? Was there a noticeable lift in sales or signups after the ad campaign? This step can help you uncover what’s working and what’s not. Role of advanced analytics and machine learning The data analysis required in this process can be overwhelming, time-consuming, and risky without the right tools. Fortunately, advanced analytics and fast, effective artificial intelligence tools can process large amounts of data from digital platforms, TV viewership, and customer interactions in less time to reveal accurate, actionable insights and patterns. They can also predict which audiences, messages, and channels will be most profitable so campaigns can adapt in real time, whether by reallocating spend to higher-performing channels or refining audience targeting. 4. Turn insights into action Once you have your data-derived insights, you can tweak your campaign in a number of ways, whether you decide to: Adjust your ads: If one message works better than another, lean into it. Refine your targeting: Focus on the audience segments most likely to act. Optimize your spend: Invest in channels or times that deliver the best return. For example, if you see that ads during prime time lead to more purchases than morning slots, you can shift your budget accordingly. This type of knowledge can be used to continuously improve your campaigns. Each time you run a new ad, you measure again, building on past insights to make your outcome-based TV advertising even smarter. Applications of outcome-based TV measurement Outcome-based TV measurement has wide-ranging applications across industries. Here’s how it’s helping businesses link TV ad exposure to real-world actions and optimize campaigns for better results. E-commerce and retail: Retailers can track how TV ads influence purchases and use those insights to refine their assets and target specific customer groups. A clothing retailer may track how well a TV ad boosts online traffic and in-store purchases. For instance, if a seasonal sale commercial correlates with a spike in website visits or mobile app downloads, the brand can refine its ad placement to focus on the most responsive demographics. Automotive: Automakers use outcome-based TV measurement insights to determine how ads drive dealership visits, test drives, or inquiries. A car manufacturer could analyze whether TV spots featuring a new vehicle increase traffic to its dealership locator or car configuration tool online. Healthcare: Pharmaceutical companies could assess whether TV spots lead to increased prescription fills, or a health provider could test how ads promoting flu shots result in appointment bookings through its website or app. If any messages resonate more with families, the provider can create similar campaigns for the future. How Experian enhances outcome-based TV measurement Experian has recently partnered with EDO, an outcomes-based measurement provider, to offer more granular TV measurement across platforms. Our identity resolution and matching capabilities enhance EDO’s IdentitySpine™ solution with rich consumer data, including age, gender, and household income, all in a privacy-centric way. Integrating these demographic attributes is helping advertisers achieve more precise audience insights and connect their first-party data to actionable outcomes. As a result of this collaboration, brands, agencies, and networks can optimize their TV campaigns by identifying which ads drive the most decisive engagement among specific audience segments. We’re improving accuracy, targeting, and more so advertisers can maximize the performance of their CTV strategies. Get in touch with Experian’s TV experts If you’re ready to take your data-driven TV advertising strategies to the next level, connect with our team. We combine advanced data and identity solutions as well as strong industry collaborations to help brands optimize their TV campaigns. Whether you're navigating traditional or advanced TV formats, our expertise ensures your efforts deliver maximum impact. Connect with us today to drive engagement, connect with audiences, and achieve better ROI. Let’s transform the way you measure success on TV. Reach out to our TV experts Contact us Latest posts

Advertising today is more complex than ever. Consumers demand personalized, relevant experiences from brands, making it increasingly challenging to meet expectations without external support. Businesses must work with publishers, retailers, and platforms to thrive, using these partnerships for data insights that refine their strategies and fuel growth. We spoke with industry leaders from Ampersand, AppsFlyer, Audigent, Comcast Advertising, Fox, ID5, and Snowflake to gather insights on how strategic collaboration can expand audience reach, improve targeting precision, and drive measurable advertising success. 1. Expand your reach with strategic collaborations Gone are the days when brands relied solely on third-party data. By linking their first-party insights with equally valuable data from partners, brands develop a far more comprehensive understanding of their audiences. This collaborative approach creates richer audience profiles, improves targeting, and enhances campaign performance. Partnerships also create opportunities for operational efficiencies. For instance, brands that share data and expertise with collaborators can expand their audience reach without overhauling existing systems. These collaborations allow marketers to work smarter, turning shared knowledge into strategic wins. "Partnerships are everything. We can't fulfill our goals on the sale side, marketers can't fulfill their goals of finding their audience where they need to reach them and with the right level of outcomes without partnering together. Why? Because each of them has their own line of sight to the data that they have access to and the data that they know best."Justin Rosen, Ampersand 2. Identify the right partnership model Choosing the right partnership model is key to achieving your business objectives. For some, pairing first-party data with publishers' insights creates better targeting. For others, aligning with complementary brands allows them to engage shared audiences. For large-scale efforts, agencies can unify collaboration frameworks, making onboarding and activation seamless. Meanwhile, emerging categories like FinTech, hospitality, and commerce media provide brands new avenues for impactful partnerships. Evaluating these options thoroughly will ensure your collaboration aligns with long-term marketing goals. "With first-party data being really the central point of signal today, we see more and more of our advertisers identifying partnerships with maybe potentially historical competitors or partners they would've never considered."Tami Harrigan, AppsFlyer 3. Utilize the power of pooled insights Combining various data sources, like CRM records, browsing behavior, and shopping receipts, creates an in-depth view of your customers. By understanding what motivates consumers at every stage of their journey, brands can better tailor messaging and funnel marketing spend to where it matters most. This approach also enables data-driven agility. Real-time insights help brands make informed adjustments, whether it’s shifting strategies mid-campaign or identifying new growth opportunities. When brands share data responsibly, the results are campaigns that resonate and deliver measurable improvements. "A lot of advertisers have gotten smarter about their data than they were just two, three years ago. They’re now doing that segmentation on their side with their data and bringing that to Fox and saying, ‘Look, match this segment against your entire user base.’ In order to do that, we can work with providers like Experian, or with data clean rooms to really bring that data and do a direct match without going through a third party."Darren Sherriff, Fox 4. Adopt the right tools and technology The right tools empower a collaborative data ecosystem. Solutions like data clean rooms ensure privacy-first data matching and measurement. Identity frameworks, such as Unified ID 2.0 (UID2) or ID5, enable secure data alignment across platforms, simplifying audience targeting while safeguarding sensitive information. Shared dashboards are another crucial tool, providing all collaborators with clear, co-owned performance metrics. Yet, while technology is an enabler, success ultimately depends on how well tools align with each partner’s goals and build trust within the collaboration. “You have to make it accessible to non-technical personas and you have to have the ability to have it stood up and pay dividends in a short amount of time. The other thing is interoperability. We very much think as an industry we need to have interoperability with clean rooms, ones that operate on different frameworks.” David Wells, Snowflake 5. Overcome barriers to collaboration Collaboration often faces obstacles, like differing goals, fragmented data, or resource gaps. Brands can tackle these issues by aligning stakeholders on clear KPIs, standardizing data-sharing practices, and selecting tools that integrate smoothly with existing systems. Breaking down barriers early fosters fluid cooperation and improves outcomes for everyone involved. When goals, tools, and resources are in sync, these partnerships deliver lasting value and stronger results. “The key is to bring together data assets and work collaboratively to address fragmentation. The way to solve that is with more interoperability and connect the data in very privacy-safe ways, offering more opportunity to reach high fidelity audiences and incorporate better measurement methodologies.”Carmela Fournier, Comcast Advertising The path to growth through partnership Those who prioritize collaboration will outrun the competition and drive sustainable growth through smarter, more connected advertising. By choosing the right models, using powerful technology, and addressing potential obstacles, brands can co-create campaigns that resonate deeply with their audiences. Connect with our experts Latest posts