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Contextual, redefined: Why AI makes it a performance play, not a privacy fallback

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Contextual, redefined: Why AI makes it a performance play, not a privacy fallback For years, contextual advertising was treated as a secondary signal. In mobile, it usually meant broad associations – targeting by app categories or genres – and while it served a role in brand safety and compliance, it was never considered precise enough to drive performance on its own when device IDs and behavioral profiles were available. That perception is changing, as app marketers now need to prove ROAS in an environment where traditional user identifiers – once the backbone of attribution and targeting – are either restricted or set to face increasing limitations. Apple’s ATT has already redrawn the rules of user-level targeting, while Google continues to iterate on learnings from Privacy Sandbox for Android, and privacy frameworks like GDPR continue to limit how personal data can be shared. These aren’t just privacy changes; they’re redefining what performance itself is built on. The limits of behavioral targeting Behavioral targeting grows on the back of large-scale data collection, often tracking people across apps and websites without clear visibility or consent. Profiles are stitched together and sold into the market, creating an ecosystem that feels intrusive and opaque. Regulators have stepped in to curb practices that put personal data at risk, and platforms are following suit to align with both legal requirements and shifting consumer expectations. Identifiers may be slowly fading, but the deeper issue is that the models rely on tracking and data sharing at a scale regulators and consumers are increasingly unwilling to accept. GDPR fines have already exceeded €5.6 billion since 2018, while Apple’s ATT has pushed opt-in rates down to around 15%. At the same time, surveys consistently show that vast majority of consumers want greater transparency into how their personal data is used (97% in this survey of 4,000), yet their sense of control over it is slipping (65% in 2025, down from 68% a year prior). But the real shift goes beyond privacy. Behavioral is losing the very rationale that made it indispensable: performance no longer requires building profiles at scale. Advances in AI now allow contextual to deliver similar precision and outcomes, with the added benefit of aligning with the privacy standards regulators and consumers expect. Recent Dataseat (part of Verve) campaigns’ outcomes show that contextual-first approaches have achieved better ROAS vs. targets on iOS and Android, with significant CPI/CPA reductions – across verticals such as retail, fintech, and gaming – proving that efficiency and scale no longer rely on identity-based targeting. AI and the evolution of contextual As with many other areas of advertising, contextual targeting is being reshaped by AI. At the bidding stage, models can evaluate impressions across multiple contextual signals – session information, placement type, device model, creative match – rather than relying solely on static labels or broad categories. This allows bids to reflect the environments most likely to convert and continuously learn which contexts drive outcomes. The same logic now feeds into campaign setup. Deep-learning recommendation systems analyse historical performance to build refined whitelists and targeting strategies. By fusing semantic, visual, and structural signals, these models infer relevance across multiple layers and construct a richer understanding of each environment. Within DSPs like Dataseat, this contextual intelligence blends internal auction data with external app-classification datasets to surface high-performing inventory and uncover expansion opportunities with similar attributes. The heaviest computation happens offline, where classical machine learning (ML) models run alongside generative and agent-based systems. These ensembles merge fragmented datasets – SKAN postbacks, publisher reports, auction logs – and combine contextual signals to predict outcomes with greater accuracy. They also run scenario simulations that expose inefficiencies, such as supply paths that inflate CPMs without lifting performance, and surface optimization patterns that guide more efficient spend. Some of this intelligence is already moving on-device. Lightweight neural networks now process interaction signals locally – session depth, placement engagement, sensor inputs – turning them into privacy-safe features in real time. Modeling on the handset allows auctions to use these scores directly, letting contextual systems assess inventory through live indicators of receptivity rather than static metadata – a step toward moment-based prediction within ATT/SKAN limits. Together, these layers make contextual a system that doesn’t just describe environments but drives outcomes. For UA teams, the benefit is clear: campaigns reach efficiency faster, more inventory becomes viable, and budgets scale within CPI goals – all without relying on user IDs. Takeaways for UA teams This shift matters now because it defines what UA teams can still count on. Profiles built on IDs are eroding – not gone, but shrinking, fragmented, and increasingly unreliable as a foundation for scale. Contextual, once dismissed as too blunt, is now the system where AI can make the biggest difference: converting noisy, privacy-constrained signals into predictive intelligence that actually drives spend decisions. The result is practical, not theoretical. Campaigns that used to take weeks of testing now reach efficiency faster. Inventory once written off as “untargetable” becomes usable supply. And marketers can hit their CPI or ROAS goals without building on sand. That’s the real change: contextual has moved from a privacy fallback to the performance layer UA teams can build growth on with confidence.
Free Ad-Supported Streaming TV: The best bet in CTV advertising

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Free Ad-Supported Streaming TV: The best bet in CTV advertising The future of streaming is free. Discover why FAST and AVOD channels are redefining CTV and giving advertisers premium reach at lower costs.
New research reveals relevance is the key to ad-supported growth

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New research reveals relevance is the key to ad-supported growth Survey data shows growing user openness to ad-supported content — proof that relevance and transparency drive engagement.
Back to Basics: Guide to programmatic deals

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Back to Basics: Guide to programmatic deals Discover the key differences between the main types of programmatic deals: open auction, private exchange, preferred deals, and programmatic guaranteed.
The Evolving Privacy Mindset: What 2025 data reveals about user willingness to share

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The Evolving Privacy Mindset: What 2025 data reveals about user willingness to share We surveyed 4,000 consumers to uncover how people really feel about data sharing in 2025. Explore the key insights.
2025 holiday retail trends for media buyers

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2025 holiday retail trends for media buyers Holiday 2025 spending will be cautious, but that opens doors for programmatic buyers. Learn how to reach value-seeking consumers this season.
Expert advice: Profit from data while respecting privacy

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Expert advice: Profit from data while respecting privacy We surveyed 4,000 mobile users for the 2025 edition of our In-App User Privacy Report, and uncovered some eye-opening insights, including: People are more worried than ever about their privacy but are still willing to share their data (e.g., region, gender, age) as long as it doesn’t feel too personal. Three out of every four consumers say they’d rather watch an ad than pay for content. So ads definitely work. Surprisingly, it’s the 16-24 year olds who are most skeptical of in-app privacy. Their trust in privacy controls dropped by 13% compared to last year. This is the group you expect to be the most comfortable, digitally, and yet their skepticism shows they’re not so sure anymore. So how does our broader industry – brands, publishers, adtech partners – deal with these findings? How can we turn user data into dollars while still respecting user privacy? In our recent webinar with Business of Apps, our own Avi Edery asked three industry experts: Stephanie Pilon (Chief Marketing Officer at Singular), Davide Rosamilia (VP of Product at ID5), and Alex Yerukhimovich (Head of SDK at GeoEdge). And in a nutshell, they shared two overarching takeaways: (1) build trust with your users, and (2) be user-centric. Below, we break this down into actionable steps: 1. Build trust The best way to put users at ease with your ads and your brand is to build a relationship with trust at its core. This can’t happen overnight. It takes persistence and continuous education to make them understand how you use their data and what’s in it for them. Build trust through transparency Start with transparency. Users want to know: What first-party data you’re collecting How their data is going to be used What they’re getting in exchange for their data What data you’re sharing with third parties Be open and share this info with them. By making it clear you have nothing to hide, you’re putting their fears to rest about what happens to their personal information. Build trust through a value exchange Users are willing to share their data if the value they get in exchange is spelled out to them and they feel it’s worth it. The value exchange must be explicit: “If you share X, you get Y.” Also, give them reversible control. (e.g., “This is how to opt out.”) When users have more control over how their data is used, they will be more at ease. Build trust in stages Trust doesn’t come automatically. It’s built up incrementally, one action at a time. To do this, only ask for the minimum amount of data you need at the start. Don’t ask for everything on day one. “I don’t think enough apps do this right, but ask for the data further down the funnel. Don’t ask for it right away. You can make that part of the onboarding process. Doesn’t have to be day one, it can be day ten.” Stephanie Pilon, Chief Marketing Officer at Singular Next, explain how this data benefits the user: “We can give you more of what you like if you share more data.” Once they see the value they’re getting, they’ll be more willing to engage. 2. Be user-centric The second main strategy is to put the focus on the user. Build the kind of experience that you would want to get if you were in their place – the kind of experience that fosters long-term relationships. Don’t create experiences you’d hate if you were the user. Users want a good ad experience We know that ads work. Users are willing to see ads as long as they’re having a good ad experience. That means: Their time is being respected, not wasted. There is a relevant exchange of value. The experience is not creepy, big brother-type surveillance. (Remember those airline retargeting ads that show up and follow you around the internet right after you’ve just bought a plane ticket? They don’t want that.) Give them ads that are not terrible or plain deceptive (some gaming apps and shopping apps are notorious for this) and users will respond more positively. “If my app is stuffed with ads, one after the other, and I can’t enjoy the experience… at that point it‘s not really a value exchange, it just becomes torture and I end up not using the app at all.” Davide Rosamilia, VP of Product at ID5. Users will blame you for a bad experience For the user, there is no real difference between the ad experience and the entire user experience. If they see a lousy ad, they will blame you, not the advertiser! “If you make user trust your north star, you’ll realize that their ad experience is just an integral part of the overall user experience with your product… and you’re accountable for it.” Alex Yerukhimovich, Head of SDK at GeoEdge You must take ownership of the entire user experience. Make sure things work as intended. Don’t just use a checklist and call it a day; test the entire app and user experience yourself. See the ads firsthand. Find the faults and fix them. Listen to your users Users are vocal – particularly when they’re annoyed. They’ll tell you if your app is below par or if there are too many ads or if there are too many steps to register. Monitor social media and your app’s reviews in app stores. If you listen to what they want and act on their feedback, you’ll be a step ahead of your rivals. Strangely enough, the majority of apps never do this. Which means you instantly gain a competitive advantage by simply taking action based on user feedback! Balancing profit and privacy in adtech is doable As brands and publishers, the amount of first-party user data we have is staggering. And if we want to turn this data into dollars, we need to do a better job of allaying users’ fears regarding data privacy. The three industry experts at our webinar outlined how best to...
Back to Basics: Mobile video ads

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Back to Basics: Mobile video ads Mobile video ads deliver high-impact engagement for publishers and advertisers alike. Discover how these dynamic ads can capture attention and drive conversions.
Holiday campaign performance, powered by curated deals

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Holiday campaign performance, powered by curated deals Holiday shopping is starting early this year. Curated PMP bundles can help you reach high-intent shoppers with speed, precision, and performance.

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