
In this article…
Artificial intelligence (AI) and connected TV (CTV) have a perfect synergy that’s revolutionizing how advertisers connect with their audiences. CTV serves as a medium for streaming content, while AI acts as a sophisticated technology that improves the performance of CTV advertising campaigns. The integration of these two technologies has paved the way for advertisers to reach their target audience more effectively, making CTV advertising a powerful and efficient tool.
In this blog post, we’ll dive into how these technologies work together —and why you should jump on board with AI for CTV advertising if you haven’t already.
Why AI and CTV are a great match
CTV and AI are transforming how advertisers connect with their audiences and improving the performance of their advertising campaigns in the CTV space. They work together to make advertising smarter and more enjoyable for everyone involved. AI uses sophisticated computer programs to analyze and understand data, while CTV refers to the streaming services that consumers use at home. But what makes them a great match in advertising?
AI uses data to determine which TV ads are most exciting and relevant to certain people, and it can even adjust ads in real time to ensure viewers are always getting the most personalized experience. AI can provide suggestions to viewers based on previously watched content to help them find what they’d enjoy watching next. To sum it up, AI allows for:
- Precise targeting: AI uses data to determine which TV ads are most exciting and relevant to certain people.
- Personalization: AI can adjust ads in real time to ensure viewers are always getting the most personalized experience.
- Effective ad insertion: AI can provide suggestions to viewers based on previously watched content to help them find what they’d enjoy watching next.
CTV facilitates these AI-driven strategies for enhanced user engagement and satisfaction.
The rising popularity of CTV
CTV has become increasingly popular as people change the way they watch TV. Instead of the traditional approach, more viewers are now choosing CTV platforms for their entertainment. One of the main reasons for this shift is that CTV offers greater flexibility and lets viewers watch content at their convenience. The ability to skip ads on many CTV platforms also improves the experience.
CTV offers a great opportunity to interact with your target audience in a more engaging way. CTV allows for highly targeted advertising capabilities so you can reach specific demographics and households with tailored messages. Additionally, CTV provides valuable data insights that enable you to measure campaign effectiveness accurately.
If you haven’t embraced this advertising channel yet, you may be missing out on a growing and engaged audience. Here are three reasons you should add CTV to your advertising strategy.
Global video ad impressions
As a global platform, CTV has the unique ability to reach audiences worldwide. Unlike traditional TV, CTV transcends geographical boundaries and brings marketers a global audience, which makes it an ideal channel for global ad campaigns. No matter your target audience, they’re consuming content on CTV. In fact, a recent study showed that 51% of global video ad impressions came from CTV in 2022.
This abundance of global video ad impressions generates vast amounts of data, which AI can process in real time to help you make data-driven decisions and optimize your campaigns for diverse international audiences. AI can analyze viewer data from various regions, identify audience preferences and behaviors across borders, and tailor ad content accordingly. These data analysis capabilities ensure your ads get in front of the right viewers.
Viewers prefer ad-supported CTV
In 2020, the viewing time of ad-supported CTV surged by 55% while subscription video on demand decreased by 30%, according to TVision Insights. Viewers have a well-established preference for ad-supported CTV due, in part, to cost-effective access to premium content. Viewers are more engaged and less resistant to ads, as AI tailors ad content to viewer preferences and behavior to enhance ad relevance.
AI-powered insights can also aid in viewer retention and help you optimize your CTV campaigns. By accommodating viewers’ preference for ad-supported CTV and harnessing AI to improve the ad experience, you’re more likely to be successful in your marketing efforts.
CTV outpaces mobile and desktop for digital video viewing
eMarketer recently reported that U.S. adults spend 7.5+ hours each day on CTV —more than half of their digital video viewing time. Comparatively, they only spend 37.5% of their viewing time on mobile and 10% on desktops and laptops. These statistics demonstrate that CTV has become the preferred platform for digital video consumption, as viewers enjoy larger screens with superior quality for an immersive experience.
It’s important to note that AI is an essential CTV marketing tool, as it allows for precise targeting and content optimization. By utilizing AI on CTV, you can take advantage of this trend and deliver more engaging and effective campaigns to a growing and engaged audience.
How is AI already being used in CTV?
CTV has been integrated with AI across various facets and has revolutionized the television landscape. Here’s a look at how AI is already shaping the CTV experience:
Generative AI ads
Generative AI ads are taking CTV personalization to a whole new level. These innovative ads are customized versions of the same CTV ad to suit individual viewers. Some AI tools can generate several versions of the same CTV ad — swapping the actor’s clothing and voiceover elements like store locations, local deals, promo codes, and more — and can create up to thousands of personalized iterations in just a few seconds. Such capabilities are a game-changing approach to connecting with your audience.
Next, we dive into the advantages and impact of generative AI ads, and explore their transformative role in CTV advertising.
Contextual ads vs personal data
Generative AI ads use personal data, such as viewing history and demographics, to create highly personalized ad experiences. This sets them apart from contextual ads, which rely solely on the content being viewed. Using AI to harness this data, you can move beyond traditional contextual targeting and ensure your ads connect with viewers on a more individualized level.
Generative AI ads can be used to A/B test
Generative AI ads are not just about personalization; they also open the door to A/B testing. Being able to create several versions of one ad quickly allows you to experiment with various ad elements, such as messaging, visuals, and calls to action, to identify what works best for different segments of your audience and drives the best performance. This flexibility is especially valuable for refining ad campaigns and maximizing their impact.
What’s next for AI-generated ads like this?
The potential of AI-generated ads is exciting. As AI technologies constantly advance, we can expect even more personalized and automated CTV advertising. It’s a good idea to keep up with the latest AI-driven innovations to create more effective ad campaigns in the fast-evolving CTV space. The possibilities are endless, and you’ll likely find the most success when you embrace AI in CTV advertising.
Optimize streaming quality
AI helps viewers enjoy more seamless CTV experiences. By assessing network speed and user preferences, AI optimizes video quality in real time to reduce buffering interruptions. For instance, streaming platforms use AI to adjust video settings based on a user’s connection speed. This guarantees an uninterrupted and enjoyable viewing experience.
Review content for compliance
AI also has a part to play in quality assurance and compliance management. It assesses content alignment with technical parameters and moderates compliance with local age restrictions and privacy regulations. This means AI can identify and filter out unsuitable content to provide a safer and more enjoyable viewing environment for audiences while safeguarding brands from association with undesirable material.
Voice command
AI-powered voice command technology is increasingly used to control CTV viewing. This technology is embedded in streaming devices and smart TVs and allows viewers to interact with their CTV content through voice-activated commands. This personalizes the viewing experience and improves convenience, as it eliminates the need for remote controls.
CTV-integrated voice assistants like Google Assistant, Amazon Alexa, Apple Siri, and Samsung Bixby offer a more human-like interaction with the television, allowing users to give commands and receive tailored responses.
Content recommendations
AI can offer content recommendations that provide viewers a more personalized and engaging experience. Major over-the-top (OTT) services like Netflix, Hulu, and Amazon Prime use AI-driven data analysis to deliver tailored content suggestions to their audiences. By analyzing user habits in detail, AI can recommend content based on factors such as actors, genres, reviews, and countries of origin. This personalized approach helps viewers discover content that matches their preferences and enhances their viewing experience.
Advertising
Programmatic ad buying, driven by AI, automatically matches ad placements to specific audience segments based on behavioral patterns. It improves ad delivery by moving away from gross rating points (GRP) to more intelligent and targeted placements. This benefits marketers by ensuring ads are seen by the right people at the right time. It’s also cost-effective for publishers, as it maximizes the sale of ad spots to suitable buyers.
Automatic content recognition (ACR) technology, which AI powers, is integrated into smart TVs and streaming devices to improve ad relevance. It provides contextual targeting and extends the reach of ads across multiple devices. For example, platforms like Roku use ACR data to display ads to viewers who haven’t seen them on traditional TV. Similarly, Samba TV retargets mobile users based on IP address and aligns their viewing habits with their smart TVs.
Demand-side platforms
CTV advertising relies heavily on demand-side platforms (DSPs) to efficiently manage and optimize ad campaigns. These platforms use machine learning and AI in several important ways:
Using machine learning and AI to address data fragmentation
Data is abundant but fragmented when it comes to CTV advertising. DSPs are flooded with a massive amount of data, including information about households, viewer behavior, and viewing patterns. This data is far too much for manual analysis to handle effectively, which is where AI comes in.
By integrating machine learning algorithms into DSPs, AI can harmonize this fragmented data and provide valuable insights and a holistic view of your audience. AI can process zettabytes of data in real time, which streamlines the decision-making process and empowers you to compete quickly for limited CTV impression opportunities.
Predicting advertising outcomes with AI
AI is quickly changing the way we predict and optimize advertising outcomes. TV buying and optimization platforms are now using AI to improve ad performance. With machine learning, these platforms can anticipate which ad creatives will produce the best results based on various non-creative factors. These include the context of the ad, the audience’s profiles, the time of day it is displayed, and the frequency of the ad display.
By relying on AI to make these predictions, you can make sure your campaigns are highly optimized for success and deliver more relevant, compelling ads to viewers.
Optimizing generative ads
AI is also driving optimization in generative ads. These personalized versions of the same CTV ad can be tailored to suit individual viewers. By utilizing AI-driven analytics, DSPs can process extensive amounts of data in real time and optimize generative ads to ensure they align with viewers’ preferences and behaviors. This level of personalization is a game-changer in CTV advertising that boosts engagement and delivers content that truly resonates with the audience.
Add AI to your CTV strategy today
Integrating AI into your CTV strategy can help you stay competitive and ensure your ad campaigns are effective and engaging.
At Experian, we’re ready to help you elevate your CTV advertising and implement AI as part of your strategy. Our solutions, such as Consumer View and Consumer Sync, provide valuable audience insights, enhance targeting capabilities, and optimize engagement on TV. Plus, our partnerships with leading media marketing solutions can help you achieve greater success through effective advanced television advertising.
As you incorporate AI into your CTV strategy, you’ll be able to make more data-driven decisions, deliver more relevant content, and reach the right audience at the right time. Explore Experian’s TV solutions and empower your CTV advertising with AI today.
Start exploring
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

RampUp 2025 brought together some of the smartest minds in AdTech to talk about the future of our industry. I had the opportunity to ask attendees key questions about AI, data collaboration, and the challenges they wish they could solve instantly. Here’s what they had to say. Watch my interviews here AI is everywhere in ads—How is it changing things? AI’s influence on advertising is undeniable, and industry leaders at RampUp 2025 emphasized how it is transforming the way data is used across marketing workflows. The increasing presence of Generative AI like ChatGPT is making it easier to stitch together data from various sources and act on insights, helping marketers execute campaigns with more efficiency. AI is no longer just about automation; it is now deeply embedded in audience building, personalization, and measurement, enabling marketers to optimize every step of the customer journey. What’s the one AdTech headache you’d fix forever? AdTech leaders agreed that some industry challenges have lingered for too long. Many expressed frustrations with the ongoing conversation about unifying cross-screen targeting and measurement. While the technology exists, aligning business priorities remains a roadblock. Others highlighted issues like the complexity of billing and reporting, which still needs to be faster and more reliable. There was also a strong push to educate brand marketers on the continued impact of offline media, such as billboards, and how data-driven strategies can enhance the effectiveness of out-of-home advertising. Beyond these operational challenges, another recurring theme was the increasing importance of identity as the backbone of effective advertising. While brands are focused on collecting first-party data, the true challenge lies in activating that data at scale. Without a strong identity resolution strategy, first-party data alone is not enough to create meaningful audience connections across multiple platforms and devices. What's one AdTech tool or strategy you can’t live without? When it comes to must-have tools and strategies, data collaboration and clean rooms emerged as essential. These solutions help companies, agencies, and publishers work together seamlessly while maintaining security and efficiency. Another key strategy discussed was traffic shaping, which allows advertisers to push activation closer to publishers, reducing data leakage and improving overall performance. Both of these approaches are critical for advertisers aiming to scale. However, as brands continue to seek more flexibility and efficiency, the conversation at RampUp expanded beyond individual tools toward a broader industry transformation. Interoperability has become a top priority, with brands, platforms, and data providers focused on ensuring seamless connectivity across clean rooms, customer data platforms (CDPs), and activation partners. The days of being locked into a single walled garden are over—the future is about data portability. "RampUp made it clear that the industry is shifting toward curated, interoperable, and always-on identity solutions—and Experian is perfectly positioned to lead this next phase of growth."Suzanna Stevens, Sr. Enterprise Partnerships Manager This shift is also driving changes in how brands manage identity. Rather than relying on one-off data onboarding, companies are increasingly adopting subscription-based identity solutions that provide an always-on, continuously refreshed identity graph. This model ensures that brands have up-to-date customer profiles while reducing inefficiencies associated with batch processing. What privacy regulations should marketers be watching? Privacy remains one of the most pressing concerns in AdTech, and industry experts highlighted the need for a better approach to regulation. Consent management was identified as a major priority since it is fluid and directly impacts how marketers engage with consumers. There was also a strong sentiment that the current state-by-state approach to privacy regulation in the U.S. is unsustainable. Instead, the industry would benefit from a national framework that simplifies compliance and ensures more consistent data governance across all states. Final thoughts from RampUp 2025 RampUp 2025 showcased the rapid shifts happening in AdTech, from AI-driven efficiencies to the growing importance of data collaboration and privacy-first strategies. As the industry works to solve long-standing challenges, such as unification and regulatory fragmentation, innovation continues to drive new opportunities. Experian remains committed to helping advertisers and marketers navigate these changes by enabling smarter, more connected, and privacy-conscious advertising solutions. We’re excited to see how these themes evolve throughout the year and look forward to collaborating with our partners to shape the future of digital advertising. Follow us on LinkedIn or sign up for our email newsletter for more insights on the latest industry trends and data-driven marketing strategies. Contact us Latest posts