Native advertising: a complete guide for marketers in 2026
Tatev Malkhasyan
October 2, 2025
15
minutes read
Native advertising blends paid messages into the surrounding experience so they read like the content people already chose to consume. This guide explains what native ads are, how they work, and how to measure them.
Native advertising has moved from test-and-learn to table stakes. Instead of interrupting like banners, native placements live inside feeds, stories, and recommendation slots—matching the look and rhythm of the content people already chose to see.
That matters because audiences are harder to reach than ever. Nearly 32.8% of internet users run ad blockers, so traditional display keeps losing ground. Native slips past that resistance by reading as part of the experience, not an add-on.
The dollars follow the results. In 2023, U.S. marketers put nearly $100B into native—about 63% of digital display spend—because it typically outperforms standard banners on click-through, time spent, and brand lift.
What follows is a practical walkthrough: types of native ads and where they fit, the mechanics of setup and bidding, the platforms worth testing, and a measurement plan that ties clicks and on-page engagement to brand lift and outcomes.
What is native advertising
Native advertising is paid media designed to match the form and function of the environment in which it appears. In practice, that means the ad uses the same layout, typography, and behavior as surrounding content (for example, an article inside a publisher feed or a short video inside a social stream). Industry bodies define it this way and require that it be clearly identified as advertising with labels such as “Ad” or “Sponsored.”
⚡ Native ads match the page’s form and function—but they’re still ads. Clear ‘ad’ labels belong near the headline or thumbnail.
How it differs from banners/display
Display banners are separate, standardized ad containers (think 300×250, 728×90, or their responsive successors) that sit alongside content rather than inside it. They’re specified in the IAB ad portfolio and are typically bought and trafficked as discrete placements.
Native units, by contrast, are assembled from components (headline, image, source/brand) and rendered to look and behave like the host content, while still carrying a clear disclosure.
Here’s the practical split marketers should keep in mind:
Placement and presentation. Banners occupy predefined slots outside the editorial stream; native appears in-stream/in-feed or within a content recommendation module and mirrors the page’s look and feel.
Creative assembly. Banners are uploaded as finished files that fit standard sizes; native creatives are modular and templated by the publisher or platform to match local styles.
User expectation. Banner ads are obviously promotional; native is content-like and therefore must include prominent, proximate disclosure so people can tell ads from editorial at a glance.
Formats. Banners cover display and rich media sizes from the IAB portfolio; native spans in-feed, sponsored/branded content, native video, and recommendation widgets, each using the publisher’s own templates.
Types of native ads
Native advertising covers a family of formats that mirror the look and behavior of the surrounding content while remaining clearly labeled as ads. The IAB’s current taxonomy groups the core formats into in-feed/in-content ads, content recommendation ads, and branded/native content; video can appear in any of these (for example, in-feed video or out-stream video inside an article). All native units must include prominent disclosures so people can distinguish ads from editorial.
In-feed ads
In-feed ads appear directly inside content feeds on publisher sites or social platforms and mimic the page’s layout and typography so the scroll experience feels continuous. They’re assembled from components (headline, image or video, brand/source) and carry a clear label such as “Sponsored” or “Ad.”
In-feed units can run on content feeds, product feeds, or social feeds (for example, sponsored posts in Facebook, Instagram, or LinkedIn). Clicking can keep the user on-site (to a native article page) or take them to an external landing page.
Sponsored posts (social). On social platforms, the in-feed unit takes the form of a sponsored post that looks like any other post in the feed but is marked as paid and targeted to an audience. Social in-feed ads are explicitly called out as a primary context for in-feed native.
Sponsored content
“Sponsored content” is often used generically, but in the IAB framework it maps to branded/native content: paid content created with or by the publisher and published in the same format as full editorial (article, interactive, or video) on that site. This content can then be promoted by in-feed units or recommendation widgets. It lives on the publisher’s domain, follows the publisher’s design, and includes clear sponsorship disclosure.
Branded/native video
Video can be rendered natively in feeds (e.g., short videos in a publisher or social feed) or out-stream within an article where no video player existed before.
Out-stream and in-feed video are classified by the IAB as video that plays outside of a traditional in-stream video (pre/mid/post-roll) and are common native executions when the surrounding context is article-based.
Also called content discovery units, these are “You might also like”/“Sponsored” panels typically placed below or alongside articles. Each tile is a native ad (article, video, or product) that, when clicked, redirects off-site or to another URL controlled by the source. The widgets match the site’s styling but remain clearly labeled as paid. Examples of suppliers in this category include Taboola, Outbrain, Revcontent, Yahoo, and MGID.
📌To align our taxonomy with the IAB, note that the 2019 Native Advertising Playbook 2.0 recognizes three core native types: In-Feed/In-Content, Content Recommendation Ads, and Branded/Native Content. Video isn’t a separate type in this model; it’s an execution that can appear within these categories (e.g., in-feed or in-article video). The update also consolidates prior buckets: Promoted Listings are folded into In-Feed, and Paid Search is no longer treated as a native type. Use our detailed sub-sections for planning, but anchor classification to these three IAB types.
How to recognize native ads
Native ads are paid messages designed to match the surrounding content, but they must still be identifiable as advertising.
The clearest signal is a visible disclosure—labels like “Ad,” “Sponsored,” or similar—placed close to the unit so readers can see it before engaging.
The FTC’s business guide and enforcement policy make this the central test: if the format risks misleading people about a message’s commercial nature, a clear and prominent disclosure is required.
An advertisement or promotional message shouldn’t suggest or imply to consumers that it’s anything other than an ad. — Federal Trade Commission
Practical cues to look for:
Labeling that’s obvious and near the focal point. Disclosures should sit immediately in front of or above the headline (or on the image/thumbnail if that’s the focal point). Labels placed far to the right or below the unit are less likely to be noticed.
Readable presentation on any device. The FTC expects clear, plain-language disclosures in a font/color that stands out, with video/audio disclosures long and loud enough to be understood.
Disclosure on every page a user can land on. If people can reach the sponsored article or video without first seeing the teaser card, the click-into page also needs a disclosure near the headline.
Individual labels in recommendation widgets. In a grid of links below an article, each sponsored tile should be labeled; a single blanket label for a mixed set isn’t sufficient.
Consistent identification when content is shared. When native content is republished in search, social, or email, disclosures should travel with the link or snippet so the ad nature remains clear.
Publisher- or platform-standard treatments.Industry bodies (IAB) stress that disclosure must be clear and prominent regardless of the unit type; many publishers add borders or shading in addition to text labels.
⚡ If the disclosure isn’t visible before you click or tap, fix the placement. The label should be obvious on the unit and on the landing page.
Marketers choose native advertising because it fits the way people consume content today, scales across major platforms and the open web, and can be measured from attention to brand lift to conversions.
It reaches people where they actually spend time. In-feed environments command large, growing budgets: Insider Intelligence estimated $80.39B in U.S. native display on social in 2024 and forecast $82.88B in total U.S. social ad spend for 2024—evidence that in-feed placements have become a primary way brands buy reach.
It earns more meaningful attention than standard display—and you can optimize for it. Verification providers now publish attention and in-view time metrics that let buyers compare placements and creative quality, not just viewability. Oracle Moat’s attention frameworks outline how to track exposure time and interaction signals, while Lumen’s 2023 research links higher attention to stronger brand outcomes. The IAB is also formalizing Attention Measurement Guidelines to make these metrics comparable across platforms.
It lifts awareness and consideration when the content is the message.Nielsen’s analysis of 1,000+ U.S. brand-lift studies found branded content can add ~9–10 points to awareness metrics, underscoring why advertisers use native to move upper-funnel outcomes (and not only clicks).
It benefits from trusted contexts. Large-sample studies of news environments report brand-lift advantages when ads appear alongside reputable journalism (for example, a Stagwell experiment with ~50,000 U.S. adults testing ad adjacency across news content). While methodology differs by study, the direction is consistent: credibility of the host environment supports brand impact.
It’s built for privacy-forward, contextual strategies. As third-party cookies fade, native’s alignment with contextual signals (category, topic, semantics) gives planners durable targeting levers, supported by IAB Tech Lab’s Content Taxonomy and broader IAB guidance on privacy-by-design measurement.
It scales and optimizes programmatically. Native is not just bespoke publisher deals; it’s widely transacted via OpenRTB with modular creative components that platforms render to match each site or app. Programmatic now represents the bulk of U.S. digital ad revenue, giving native buyers standard controls for frequency, bidding, pacing, and brand safety.
When people see ads for longer, they’re much more likely to remember the brand. — Lumen Research
Business impact of native advertising
Native advertising delivers when three pieces line up: a clear objective, content people choose to engage with, and precise delivery. Done well, it improves visibility in trusted environments, strengthens mid-funnel intent, and lowers acquisition costs as you refine targeting and creative. Here’s how those gains show up in practice.
⚡ Optimize for attention and quality of engagement, then watch awareness, consideration, and conversion lift follow.
Better brand visibility
Native placements sit where attention already flows—inside feeds and article streams—so they’re well suited to build reach and awareness at scale. In the U.S., native continues to command a majority share of display budgets, per Insider Intelligence’s 2024–2025 forecasts, underscoring its role as a primary visibility channel.
Beyond sheer reach, branded/sponsored content has repeatedly shown positive lifts on awareness and consideration in large-sample studies. As mentioned, Nielsen’s analysis of 1,000+ U.S. campaigns across branded content, influencers, and podcasts documents consistent brand-lift effects when content is the vehicle for the message.
Full-funnel performance
Native doesn’t stop at the top of the funnel. Attention studies show that when people spend longer with content-like ads, outcomes rise across the funnel—recall, choice intent, and other mid-/lower-funnel indicators increase with dwell time. Independent reviews of Lumen’s campaign analyses (with PwC review) and the Teads×Lumen whitepaper chart stronger recall and choice lift as attention seconds increase. The IAB has also begun standardizing how attention should be measured, making these signals more actionable for planners.
Correlation between attention and brand outcomes (Source).
Increased ROI
Because native ads can be optimized to hold attention and drive qualified engagement, they often improve efficiency metrics. Recent IAS research tying “high-attention” impressions to business results found up to a 130% lift in conversion rates versus low-attention impressions, suggesting a clear path to stronger return when buyers optimize toward attention quality, not just viewability.
Optimization and targeting
Modern native is programmatic. Using the IAB Tech Lab’s OpenRTB Native spec, buyers send modular creative assets (headline, image, logo, etc.) and platforms render them to match each site or app—enabling standard controls for bid strategies, frequency, privacy flags, and event tracking. Major exchanges and platforms support this workflow, including Google’s Authorized Buyers.
Native campaigns combine clear objectives, precise targeting, and content that renders in the host’s style with proper disclosure.
Campaign setup
Before you buy a single impression, define the playing field. Clarify what success looks like, choose the right formats for that goal, plan disclosure from the start, and set up measurement so every click and view tells you something useful. Here’s the workflow, step-by-step:
Start with the objective and audience. Decide whether you’re optimizing for awareness (viewable reach, attention), consideration (qualified visits, scroll depth, video quartiles), or conversion (lead or sale). This choice determines formats, KPIs, and how you’ll measure success.
Choose formats and supply. Map goals to formats: in-feed, sponsored/branded content, out-stream/native video, or recommendation widgets. Use the IAB playbook and native specs to align creative components with publisher requirements.
Plan disclosure and compliance. Build “Ad”/“Sponsored” labels into the unit and the landing page for content pieces; disclosures must be clear, prominent, and proximate to the ad.
Instrument measurement. Append UTM parameters, define GA4/Adobe events (e.g., scroll depth, engaged time, form submit), and, if used, add viewability/attention tags (Moat/IAS) so you can optimize beyond clicks.
QA the experience. Check rendering and labeling on mobile and desktop, verify links, and confirm that targeting and frequency caps align with the brief. The goal is a content-like experience that’s easy to identify as advertising.
⚡ Objective set → audience defined → formats chosen → disclosures in place → measurement tagged. Don’t launch until all five are green.
Targeting & bidding
Native inventory is commonly bought programmatically. Buyers pass modular creative assets (headline, image, logo, call-to-action, brand) and target settings; exchanges/SSPs render the ad to match each placement using the OpenRTB Native spec. You can bid CPC, CPM, or CPE, set frequency caps, and optimize to engagement or attention signals with event tracking and privacy flags supported in the spec.
Targeting typically blends:
Contextual signals (section, topic, semantics) for durable reach as third-party cookies fade.
Audience data (first-party, platform, or privacy-compliant third-party) for precision.
Retargeting and lookalikes to move engaged users down-funnel.
Pacing and bid strategies (e.g., value/auto-bidding) to prioritize high-quality placements.
These controls come from the native spec and standard programmatic tooling rather than bespoke deals, which keeps optimization continuous.
Content integration
Native ads are assembled to match the host: typography, layout, and interaction model mirror the page or app while keeping sponsorship clear. Specifications outline the assets publishers require (e.g., title, image, brand/sponsored line, body, rating data), and the ad server/templates handle styling so units feel part of the feed. For content-led executions, ensure the click-in page also carries a visible disclosure near the headline.
⚡ Cross-channel tip: align native creative and measurement with your video and TV plans so attention and lift metrics are comparable across screens.
💡 For an overview of TV planning concepts and terminology, see TV advertising.
Native advertising platforms
Choosing where to buy matters as much as what you buy. Native delivery lives in three main channels: open-web content discovery networks, programmatic native exchanges/SSPs, and the social walled gardens. The right mix depends on your audience fit, inventory quality, measurement and brand-safety controls, and the level of support you need.
What they are
Native advertising platforms help brands buy and deliver ads that match a site or app’s look and behavior.
On the open web, you’ll see two big categories: content recommendation networks (widgets and in-feed units across large publisher networks) and programmatic native exchanges/SSPs (biddable native inventory rendered to each publisher’s template via OpenRTB Native).
Many publishers also run sponsored/branded content through specialized platforms, and of course the social “walled gardens” (Meta, TikTok, X, LinkedIn, Pinterest, Snapchat) are themselves large native environments.
Top digital advertising platforms to try
Below is a practical, starting list:.
Taboola (content discovery/open web). Powers native widgets and feeds across major publishers and now runs Yahoo’s native ad inventory under an exclusive 30-year deal, giving buyers consolidated access to Yahoo properties via Taboola’s stack. Recent investor disclosures cite ~600 million daily active users across its network. Useful for performance content, commerce pages, and broad reach.
Outbrain (content discovery/open web). Long-time peer to Taboola for recommendation widgets and in-feed units; in 2025 it completed a merger with Teads, bringing more video and premium publisher access into the fold. Company filings and product pages reference 1B+ monthly users.
Sharethrough (programmatic native exchange/SSP). A large native-heavy exchange with sustainability and attention features; the company highlights significant daily ad volume and publisher breadth, and the platform supports native, display, and video in one workflow. Good when you want biddable native at scale through your DSP.
TripleLift (creative SSP/programmatic native). Known for pioneering programmatic native and templated, publisher-matched formats; also active in CTV and retail media. Recent updates include support for Amazon Ads’ Native Responsive eCommerce (REC) on third-party supply and statements of 1T+ monthly ad transactions across formats—useful for omnichannel creative consistency.
Nativo (publisher-hosted sponsored content/native articles). Specializes in hosting branded articles and stories on publisher sites, then promoting them through native placements; recent releases focus on mid-funnel measurement (e.g., Brand Rank) and expanded app inventory access. A fit when your strategy centers on content-led influence with premium publishers.
Dianomi (finance/business native marketplace). A finance- and business-focused native network with partnerships across premium publishers and claims of hundreds of millions of reachable devices globally—useful for wealth, fintech, B2B, and corporate campaigns that value contextual alignment.
MGID and Revcontent (open-web native networks). Both offer large open-web reach with content recommendation and in-feed units; good for scale testing outside the walled gardens. Evaluate inventory quality, brand safety controls, and optimization tooling for your category before committing spend.
⚡ Tip: For video-first plans, line up native video inventory alongside CTV and out-stream so your creative and measurement frameworks stay consistent.
How to measure native ad success
Start by mapping metrics to intent, then choose instruments that validate quality, not just volume.
Tie primary KPIs to the campaign goal, then add diagnostics that explain why performance moved.
Awareness: viewable impressions and in-view time. A viewable impression follows the MRC standard—≥50% of pixels for ≥1s (display) or ≥2s (video)—which is the baseline before attention quality is assessed.
Consideration: CTR and post-click engagement. Track scroll depth, engaged time, pages per session, and video quartiles/completions. GA4’s enhanced measurement and Tag Manager’s Scroll Depth trigger make this straightforward to implement.
Conversion: CVR, CPA/CPL, and assisted conversions (including view-throughs with a clearly stated window).
Attention (quality signals): go beyond viewability with in-view time, interaction rate, and attention quality indices from verification providers such as Oracle Moat. These quantify exposure time and interaction—useful for optimizing native units that behave like content.
Native often aims to change what people think and feel, so run brand-lift tests when budgets allow.
What to measure: unaided/aided awareness, ad recall, favorability, consideration, and purchase intent via control vs. exposed surveys. Providers like Nielsen and Kantar offer standardized methodologies and dashboards.
Why it matters: Nielsen reports that improvements in awareness and consideration are linked to sales outcomes; their 2023 analysis cites that a 1-point lift in awareness/consideration can translate into downstream sales lift or lower short-term CPA. That supports using native to build demand, not only chase last-click conversions.
he average effect of display advertising vs native advertising (Source).
Attribution challenges
Attributing sales to native is hard because journeys span devices and platforms, and privacy changes limit user-level tracking.
Signal loss and policy changes: Apple’sAppTrackingTransparency requires explicit user permission to track across apps/sites; without consent, IDFA is inaccessible.
Cookies and the web: Google’s Privacy Sandbox has shifted the Chrome roadmap toward more user choice and privacy-preserving APIs rather than a hard, fixed deprecation date; plan for less deterministic cross-site tracking and more aggregate measurement.
Practical fixes: use view-throughs with conservative windows, apply geo/incrementality tests where feasible, adopt multi-touch or data-driven attribution for on-site behavior, and complement with brand-lift to capture upper-funnel impact. IAB’s State of Data reporting and Tech Lab guidance provide additional direction on ID alternatives and privacy-safe signals.
⚡Awareness → viewability and attention. Consideration → CTR and on-page engagement. Conversion → CPA/CPL and assisted paths. Verify with third-party tags.
Tools to use (Moat, IAS, GA4, platform-native)
Use a layered toolkit: third-party verification to confirm viewability, attention, and invalid traffic; analytics to track post-click behavior and conversions; and platform-native studies to quantify lift. The tools below play different roles—use them together for a complete read on performance.
Oracle Moat for attention diagnostics: in-view time, interaction rate, attention quality. Use to optimize creative and placement quality for native units.
Integral Ad Science (IAS) for viewability, brand safety, and attention scoring; IAS reports show up to 130% higher conversion rates from high-attention vs. low-attention impressions, making attention a credible optimization target.
GA4 (and Tag Manager) for engagement and outcomes: scroll depth, engaged-session time, events/goals, and conversion paths.
Platform-native measurement for lift and diagnostics at scale (e.g., Meta or YouTube brand-lift studies), supplemented by third-party verification for consistency.
⚡ If you use AI Digital’s Elevate, you can centralize planning, forecasting, optimization, and cross-channel analytics, and ingest third-party verification data (e.g., Moat or IAS) for optimization and reporting.
Conclusion on digital native advertising
Native advertising isn’t a replacement for banners or pre-roll. It’s a complementary format that fits the surrounding content and earns attention by feeling natural to the experience. Results depend on the basics: set a clear objective, ship high-quality creative, and target with intent. Do those three well, and native can carry its weight from awareness to action.
Looking ahead, expect more native—especially in feed-based environments and publisher integrations—as brands prioritize credible, content-led ways to build trust in a crowded ad economy.
Advances in planning and measurement will help connect native to broader video and TV strategies; if that’s on your roadmap, see The rise of AI in TV advertising.
Need a hand?AI Digital can plan, execute, and measure native as part of a full programmatic mix:
Open Garden (DSP-agnostic, transparent, cross-platform): unify performance across channels while keeping control of where budgets go and how supply is curated.
Managed service (end-to-end execution): strategy, buying, and optimization across CTV/OTT, display, social, search, native, and audio.
Elevate (planning, optimization, and cross-channel insights): predictive planning, real-time optimization, and holistic analytics to keep campaigns aligned with business KPIs.
If you want a pragmatic plan—formats, platforms, KPIs, and tests—we’re ready to help.
Blind spot
Key issues
Business impact
AI Digital solution
Lack of transparency in AI models
• Platforms own AI models and train on proprietary data • Brands have little visibility into decision-making • "Walled gardens" restrict data access
• Inefficient ad spend • Limited strategic control • Eroded consumer trust • Potential budget mismanagement
Open Garden framework providing: • Complete transparency • DSP-agnostic execution • Cross-platform data & insights
Optimizing ads vs. optimizing impact
• AI excels at short-term metrics but may struggle with brand building • Consumers can detect AI-generated content • Efficiency might come at cost of authenticity
• Short-term gains at expense of brand health • Potential loss of authentic connection • Reduced effectiveness in storytelling
Smart Supply offering: • Human oversight of AI recommendations • Custom KPI alignment beyond clicks • Brand-safe inventory verification
The illusion of personalization
• Segment optimization rebranded as personalization • First-party data infrastructure challenges • Personalization vs. surveillance concerns
• Potential mismatch between promise and reality • Privacy concerns affecting consumer trust • Cost barriers for smaller businesses
Elevate platform features: • Real-time AI + human intelligence • First-party data activation • Ethical personalization strategies
AI-Driven efficiency vs. decision-making
• AI shifting from tool to decision-maker • Black box optimization like Google Performance Max • Human oversight limitations
• Strategic control loss • Difficulty questioning AI outputs • Inability to measure granular impact • Potential brand damage from mistakes
Managed Service with: • Human strategists overseeing AI • Custom KPI optimization • Complete campaign transparency
Fig. 1. Summary of AI blind spots in advertising
Dimension
Walled garden advantage
Walled garden limitation
Strategic impact
Audience access
Massive, engaged user bases
Limited visibility beyond platform
Reach without understanding
Data control
Sophisticated targeting tools
Data remains siloed within platform
Fragmented customer view
Measurement
Detailed in-platform metrics
Inconsistent cross-platform standards
Difficult performance comparison
Intelligence
Platform-specific insights
Limited data portability
Restricted strategic learning
Optimization
Powerful automated tools
Black-box algorithms
Reduced marketer control
Fig. 2. Strategic trade-offs in walled garden advertising.
Core issue
Platform priority
Walled garden limitation
Real-world example
Attribution opacity
Claiming maximum credit for conversions
Limited visibility into true conversion paths
Meta and TikTok's conflicting attribution models after iOS privacy updates
Data restrictions
Maintaining proprietary data control
Inability to combine platform data with other sources
Amazon DSP's limitations on detailed performance data exports
Cross-channel blindspots
Keeping advertisers within ecosystem
Fragmented view of customer journey
YouTube/DV360 campaigns lacking integration with non-Google platforms
Black box algorithms
Optimizing for platform revenue
Reduced control over campaign execution
Self-serve platforms using opaque ML models with little advertiser input
Performance reporting
Presenting platform in best light
Discrepancies between platform-reported and independently measured results
Consistently higher performance metrics in platform reports vs. third-party measurement
Fig. 1. The Walled garden misalignment: Platform interests vs. advertiser needs.
Key dimension
Challenge
Strategic imperative
ROAS volatility
Softer returns across digital channels
Shift from soft KPIs to measurable revenue impact
Media planning
Static plans no longer effective
Develop agile, modular approaches adaptable to changing conditions
Brand/performance
Traditional division dissolving
Create full-funnel strategies balancing long-term equity with short-term conversion
Capability
Key features
Benefits
Performance data
Elevate forecasting tool
• Vertical-specific insights • Historical data from past economic turbulence • "Cascade planning" functionality • Real-time adaptation
• Provides agility to adjust campaign strategy based on performance • Shows which media channels work best to drive efficient and effective performance • Confident budget reallocation • Reduces reaction time to market shifts
• Dataset from 10,000+ campaigns • Cuts response time from weeks to minutes
• Reaches people most likely to buy • Avoids wasted impressions and budgets on poor-performing placements • Context-aligned messaging
• 25+ billion bid requests analyzed daily • 18% improvement in working media efficiency • 26% increase in engagement during recessions
Full-funnel accountability
• Links awareness campaigns to lower funnel outcomes • Tests if ads actually drive new business • Measures brand perception changes • "Ask Elevate" AI Chat Assistant
• Upper-funnel to outcome connection • Sentiment shift tracking • Personalized messaging • Helps balance immediate sales vs. long-term brand building
• Natural language data queries • True business impact measurement
Open Garden approach
• Cross-platform and channel planning • Not locked into specific platforms • Unified cross-platform reach • Shows exactly where money is spent
• Reduces complexity across channels • Performance-based ad placement • Rapid budget reallocation • Eliminates platform-specific commitments and provides platform-based optimization and agility
• Coverage across all inventory sources • Provides full visibility into spending • Avoids the inability to pivot across platform as you’re not in a singular platform
Fig. 1. How AI Digital helps during economic uncertainty.
Trend
What it means for marketers
Supply & demand lines are blurring
Platforms from Google (P-Max) to Microsoft are merging optimization and inventory in one opaque box. Expect more bundled “best available” media where the algorithm, not the trader, decides channel and publisher mix.
Walled gardens get taller
Microsoft’s O&O set now spans Bing, Xbox, Outlook, Edge and LinkedIn, which just launched revenue-sharing video programs to lure creators and ad dollars. (Business Insider)
Retail & commerce media shape strategy
Microsoft’s Curate lets retailers and data owners package first-party segments, an echo of Amazon’s and Walmart’s approaches. Agencies must master seller-defined audiences as well as buyer-side tactics.
AI oversight becomes critical
Closed AI bidding means fewer levers for traders. Independent verification, incrementality testing and commercial guardrails rise in importance.
Fig. 1. Platform trends and their implications.
Metric
Connected TV (CTV)
Linear TV
Video Completion Rate
94.5%
70%
Purchase Rate After Ad
23%
12%
Ad Attention Rate
57% (prefer CTV ads)
54.5%
Viewer Reach (U.S.)
85% of households
228 million viewers
Retail Media Trends 2025
Access Complete consumer behaviour analyses and competitor benchmarks.
Identify and categorize audience groups based on behaviors, preferences, and characteristics
Michaels Stores: Implemented a genAI platform that increased email personalization from 20% to 95%, leading to a 41% boost in SMS click through rates and a 25% increase in engagement.
Estée Lauder: Partnered with Google Cloud to leverage genAI technologies for real-time consumer feedback monitoring and analyzing consumer sentiment across various channels.
High
Medium
Automated ad campaigns
Automate ad creation, placement, and optimization across various platforms
Showmax: Partnered with AI firms toautomate ad creation and testing, reducing production time by 70% while streamlining their quality assurance process.
Headway: Employed AI tools for ad creation and optimization, boosting performance by 40% and reaching 3.3 billion impressions while incorporating AI-generated content in 20% of their paid campaigns.
High
High
Brand sentiment tracking
Monitor and analyze public opinion about a brand across multiple channels in real time
L’Oréal: Analyzed millions of online comments, images, and videos to identify potential product innovation opportunities, effectively tracking brand sentiment and consumer trends.
Kellogg Company: Used AI to scan trending recipes featuring cereal, leveraging this data to launch targeted social campaigns that capitalize on positive brand sentiment and culinary trends.
High
Low
Campaign strategy optimization
Analyze data to predict optimal campaign approaches, channels, and timing
DoorDash: Leveraged Google’s AI-powered Demand Gen tool, which boosted its conversion rate by 15 times and improved cost per action efficiency by 50% compared with previous campaigns.
Kitsch: Employed Meta’s Advantage+ shopping campaigns with AI-powered tools to optimize campaigns, identifying and delivering top-performing ads to high-value consumers.
High
High
Content strategy
Generate content ideas, predict performance, and optimize distribution strategies
JPMorgan Chase: Collaborated with Persado to develop LLMs for marketing copy, achieving up to 450% higher clickthrough rates compared with human-written ads in pilot tests.
Hotel Chocolat: Employed genAI for concept development and production of its Velvetiser TV ad, which earned the highest-ever System1 score for adomestic appliance commercial.
High
High
Personalization strategy development
Create tailored messaging and experiences for consumers at scale
Stitch Fix: Uses genAI to help stylists interpret customer feedback and provide product recommendations, effectively personalizing shopping experiences.
Instacart: Uses genAI to offer customers personalized recipes, mealplanning ideas, and shopping lists based on individual preferences and habits.
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Questions? We have answers
What is the difference between native and traditional advertising?
Native advertising is paid media that matches the look and behavior of its surroundings (for example, an article card in a news feed) and is clearly labeled as advertising. Traditional display uses fixed ad containers that sit beside content (e.g., 300×250, 728×90) and are obviously separate from the experience. Native is assembled from components and rendered to fit the page or app; banners are uploaded as finished files.
How much does native advertising cost?
Pricing depends on format and goal. Self-serve native (open web or social) is commonly bought on CPC or CPM; video may use CPV/CPE; publisher sponsored content often uses a flat package fee for creation and distribution. Final costs vary by audience quality, placement, seasonality, and creative performance, so plan to start with a test budget, set a target CPA/CPL, and optimize bids and inventory toward that outcome.
What is mobile native advertising?
Mobile native advertisements are units that fit the design and interactions of mobile web or in-app environments—think scrollable cards in a feed, Stories, or rewarded video in games. They prioritize fast load, readable typography, and gesture-friendly layouts, and they must carry clear “Ad” or “Sponsored” labels. Measure success with mobile-relevant signals such as viewable impressions, in-view time, scroll depth, video quartiles, and on-site actions.
What is native advertising content?
Native content advertising is brand-funded content—articles, videos, listicles, interactives—published in the style of the host site or platform and clearly identified as paid. Strong native content teaches or entertains first and sells second, aligning topic, audience, and call to action. For articles and long-form video, include a visible disclosure on the landing page as well as on the teaser unit.
What is native programmatic advertising?
Programmatic native delivers these formats through real-time bidding and standardized specs (e.g., OpenRTB Native). Advertisers upload modular assets (headline, image, body, logo), set targeting and bids, and the exchange/SSP renders the ad to match each placement. You get the usual controls—frequency, pacing, brand safety—and can optimize to engagement, attention, or conversion goals.
What industries are a good fit for native advertising?
Any category that benefits from education or storytelling tends to perform well: B2B and SaaS, financial services (with appropriate disclosures), health and wellness (within regulatory guidelines), education, travel and hospitality, automotive, retail/ecommerce, and entertainment/media. Native helps introduce complex ideas, compare options, or inspire consideration before a purchase—so it’s especially useful for considered decisions and mid-funnel influence.
What are the most successful examples of native advertising campaigns?
Frequently cited standouts include Netflix’s “Women Inmates” paid post in The New York Times (for Orange Is the New Black), Netflix’s “Cocainenomics” with The Wall Street Journal (for Narcos), and Purina’s “Dear Kitten” with BuzzFeed. Each blended a strong editorial-style story with transparent disclosure and distribution in a context where the audience was already engaged.
Have other questions?
If you have more questions, contact us so we can help.