Do you remember how, in June 2025, Pixar released Elio? No? No surprises. This original animated film with a 83% Rotten Tomatoes score and strong audience reactions, got the worst opening weekend in Pixar history. It finished at roughly $154 million worldwide against a budget reported between $150 and $250 million, with an estimated $100 million theatrical loss, according to The Direct.
Then why did it fail? Even though SlashFilm called Elio "a perfect study in how to fail a good movie," and concluded it was ultimately a victim of a parent company that decided to cut its losses and save money on an expensive marketing campaign. "CBR put it more bluntly:
"Without any marketing ahead of the film, it was difficult for anyone outside of people searching out new movies to even be aware of the upcoming Pixar movie."
This is a pattern, not an accident. Strange World (2022) was called by The Hollywood Reporter "the worst opening for a Disney Animation Thanksgiving title in modern times" and lost roughly $100 million on a $180 million budget. Among the reasons cited by Variety: "lackluster marketing compared to other Disney animated films." Lightyear (2022) ran into the same wall and ended at $215 million worldwide against a budget of over $200 million.
Three Pixar and Disney Animation films in three years. None of them is broken on creative grounds. All of them are broken on visibility.
Why under-advertising kills good films
An efficient movie marketing campaign is a coordinated set of paid, owned, and earned activities designed to deliver three things before opening weekend:
- A clear position in the audience's mind ("the alien adventure," "the fashion sequel," "the hero who can fly")
- Reach with the right people, measured at the impression level rather than the campaign level
- A conversion path from awareness to a ticket purchase, trackable to a specific creative or channel
In 2026, PwC's Global Entertainment & Media Outlook placed average print-and-advertising (P&A) spend at 28–32% of total production budgets, up from roughly 15% pre-COVID. Tentpole studio releases now routinely commit $80–120 million in marketing alone. For Warner Bros.'s 2025 Superman reboot, marketing came in around $200 million on a $225 million production budget.
The implication is simple: marketing is not a finishing touch. It is half the cost structure of a theatrical release.
At the same time, two industry shifts make under-marketing more dangerous than it used to be:
- Streaming substitution. When a film has no cultural footprint in the four weeks before release, audiences default to "I'll catch it on Disney+ or Netflix." This is what Elio, Strange World, and Lightyear all demonstrated.
- Attention compression. A modern moviegoer sees roughly 4,000 to 10,000 brand messages per day. A film that fails to break through in the trailer-to-release window is not in the consideration set on Friday night.
The cost of doing nothing is not flat. It compounds. A film that misses its opening weekend rarely recovers in week two, because exhibitors cut screens fast and word-of-mouth has nothing to amplify.
Six methods that drive efficient movie marketing campaigns
1. Earned media and cultural moment-making
Earned media is coverage and conversation generated by audiences and press without direct payment. It is the cheapest reach a studio can buy, but only if the campaign creates something culture wants to talk about on its own.
The clearest current example is the Devil Wears Prada 2 "AI meme that wasn't AI". The film opens with Runway Magazine in a reputational crisis, with Meryl Streep's Miranda Priestly drowning in online hate. One meme on screen for a brief moment shows her dressed as a fast-food worker with the caption "Would you like some lies with that?" — visually indistinguishable from AI slop, complete with blurred lettering and the warm yellow tint audiences now associate with generative imagery.
On 1 May 2026, the day of the release, digital artist Alexis Franklin posted on Instagram and X that director David Frankel had commissioned her to hand-paint the image in Procreate and Photoshop. She was not asked to mimic AI — only to "create a cheap meme." The post on X racked up 3.7 million views and was picked up by Variety, Deadline, NBC News, The Wrap, Fast Company, Parade, AV Club, and Creative Bloq within 48 hours. None of that coverage was paid for. The story carried itself because it sat exactly on top of the cultural anxiety the film was already satirising: a film about declining print and online manipulation had refused to use AI even when the script called for AI-style imagery, as the AV Club put it, "a conceptual ouroboros."
2. Brand partnerships and licensing collaborations
Co-marketing splits the cost of reach with brands that already have it. The most documented current example is Universal's Wicked and Wicked: For Good campaign across 2024 and 2025.
According to Universal's own disclosure, Wicked (Part 1) signed more than 400 brand partners and generated approximately $350 million in media and promotional value with 25 billion impressions. The 2025 sequel Wicked: For Good matched it: 400+ partners, $330 million in media value, and roughly 28 billion impressions — the second-biggest promotional partner campaign ever for a major studio film, behind only its predecessor. Industry estimates put Universal's global marketing spend on the first film at roughly $150 million.
Selected activations across the two films:
| Brand | Activation |
| Starbucks | First-ever collaboration of this scale with a film brand — themed cold brews (Elphaba green matcha foam), collectable drinkware, and beverages launched in the U.S., Canada, and select international markets |
| LEGO | The "ultimate fan destination" hub with 150+ exclusive items, including the Mattel Elphaba singing doll, Paul Tazewell apparel, and OPI nail polish |
| Stanley 1913 | Limited-edition Quencher tumblers in Glinda and Elphaba colourways, exclusive to Target — sold out repeatedly |
| Target | The "ultimate fan destination" hub with 150+ exclusive items including the Mattel Elphaba singing doll, Paul Tazewell apparel, and OPI nail polish |
| r.e.m. Beauty | Ariana Grande's own brand released character-themed makeup collections; generated $15 million in media impact value on its own |
| Amazon | "Oz on Amazon" — Prime member early screenings, a dedicated merch hub, an Alexa skill, Fire TV home-screen takeover, and a Twitch "Together for Good" stream-a-thon |
| Crocs, OPI, Béis, Voluspa, Lush, Le Creuset, Olay, Dunkin', H&M, Forever 21, Samsung Frame | Limited-edition product runs across fashion, beauty, home, and fragrance |
3. Programmatic mobile video and interactive ad creatives
This is where the largest share of digital P&A actually goes. More than half of film marketing budgets in 2025 sat in digital, with the biggest allocations in mobile video advertising and programmatic video advertising on YouTube, TikTok, and connected TV.
The reason is straightforward. Mobile video carries the trailer the way TV used to, but with three things TV cannot offer:
- Behavioural and contextual signals at the impression level
- Interactive ad creatives that turn a passive viewer into an engaged one
- Direct measurement from view to ticket search
For Sony Pictures Entertainment Malaysia's launch of Project Hail Mary (Ryan Gosling, 2026), using 3 Adello’s ad creative formats: Flipcard, Zero-G, and Full-page video.
The numbers against an entertainment-vertical benchmark of 1–2% CTR:
| Metric | Result |
| ZeroG CTR | 8.24% |
| ZeroG Rolling CTR | 5.86% |
| Campaign average CTR | 6.11% |
| Unique users reached | 465,000 |
| Strongest-performing segment | Women, sci-fi audiences, 25–34s |
Catherine Chai, Marketing Director at Sony Pictures Entertainment Malaysia, on the campaign:
Adello provided the precise mobile scale and creative sophistication required to drive high-impact awareness for Project Hail Mary. The interactive units significantly exceeded our standard engagement benchmarks, and the execution was seamless from strategy through to delivery.
🎬 Do you want a stunning creative for your movie? Contact Adello, fill out the form, and let’s make your movie reach its audience:
4. Out-of-home and experiential activations
Out-of-home (OOH) and experiential remain the strongest tools for cultural footprint. They are physical, photographable, and travel back into social feeds for free.
A larger-scale 2025 example is Netflix's Squid Game season 3 launch. The campaign deployed an anamorphic DOOH takeover at Shinsegae Square in Seoul as part of a global activation built with Palomino and Cheil Worldwide. The 3D illusion broke through the visual noise of a busy plaza and travelled into TikTok within hours.
The honest constraint: DOOH (digital out-of-home) only pays back inside a holistic system that pairs it with mobile. A screen in a plaza or transit hub generates one impression and ends there. The same screen, drop-pinned against a mobile retargeting layer in the surrounding cell zone, becomes a two-touch sequence: the viewer sees the billboard, then sees the trailer on their phone within minutes. That sequence is what lifts conversion. Studios running DOOH without a paired mobile DSP layer are buying a photograph, not a campaign.
5. Creator and influencer seeding
Creator partnerships fill the gap between paid media and audience trust. According to the IAB 2025 Creator Economy Ad Spend and Strategy Report, 86% of consumers now make viewing decisions based on creator recommendations, and creator-led ads deliver a 70% higher click-through rate and 159% higher engagement than traditional brand ads.
Deadpool & Wolverine (2024) is the cleanest tentpole example. Disney, Marvel, and Ryan Reynolds's Maximum Effort agency built the campaign around Reynolds and Hugh Jackman running a multi-month "fake rivalry" across Twitter, Instagram, and Facebook. Each post landed as a piece of comedy content rather than a paid ad.
Around that core, the team layered creator activations that matched specific scenes and characters in the film:
- A pre-release pooch screening with 20+ canine influencers (real dog accounts with real dog audiences), hosted by the dog who plays Dogpool
- A 10-city global publicity tour across four continents, including China, the first major Marvel talent visit since Avengers: Endgame
- A Turner Classic Movies night programmed by Reynolds himself
- Best Friends Animal Society is the official non-profit partner, running pet adoption PSAs across broadcast and print
The film became the highest-grossing R-rated movie ever. The structural lesson: for films with a defined community (genre fans, fandoms, music audiences, pet owners), paying creators who already speak to that community delivers more conversion per dollar than broad-reach paid media.
6. Data-driven attribution and testing
Studios that ship films at scale increasingly run them like performance products. Warner Bros. Discovery's ATLAS attribution platform, disclosed in Q1 2026 earnings, integrated 14 data streams — social sentiment, trailer view velocity, geo-targeted ticket searches — and predicted opening weekend grosses within a 4.2% margin of error across the full 2025 slate, down from 11.7% in 2022.
What this looks like operationally:
| Tool | What it does | Decision it informs |
| Trailer view velocity | Tracks views per hour after each trailer drop | Whether to push more spend behind a creative |
| Geo ticket search | Monitors Fandango / Atom Tickets searches by DMA | Where to add OOH or local TV |
| Social sentiment | Classifies positive vs. negative conversation | Whether to lean into or pivot a campaign angle |
| Mobile DSP frequency data | Shows reach and frequency per audience cluster | When to cap a segment and reallocate spend |
This level of attribution is no longer a tentpole-only capability. Mid-budget releases ($30–80 million production) increasingly run the same stack through DSPs and contextual platforms.
A film can be great and still fail to reach its audience. Strong reviews and strong direction do not land without a marketing system behind them — a clear position, a sharable artefact, and a media plan that ties earned reach, partnerships, programmatic mobile video, OOH, creators, and measurement into a single sequence. The decision is not whether to market a film. It is whether to back it with the full system, early enough to compound. Films that do not get watched on a laptop, six months later, by people who never knew the trailer existed.
Pinterest is the strangest social platform to write about. It isn't quite social — most users don't follow people, don't post comments, don't chase virality. It isn't quite a search engine — though more than 8 out of 10 weekly users say they discover new brands through it. It isn't quite e-commerce — though it generates roughly $4.30 in attributed sales for every $1 spent on ads. It is, increasingly, all three at once: a visual search engine sitting on top of a shopping graph, with an ad system optimized for the long tail of buying intent.
For a decade, Pinterest was treated by media planners as an "always-on, low-priority" channel. In 2026, that posture is harder to defend. The platform crossed 600 million monthly active users in Q3 2025, daily video views are up roughly 240% year-over-year, and Pinterest has spent the last 24 months rebuilding its ad stack around AI-driven automation, contextual signals, and CTV expansion. This is a guide to where the platform actually is right now — what the ad ecosystem looks like, why video has taken center stage, how targeting works under the hood, and what's changing in 2026.
What makes Pinterest different from other ad platforms
Three structural facts shape everything else.
Pinterest users arrive with intent. On Meta or TikTok, users come to be entertained; advertising interrupts that. On Pinterest, users come to plan — kitchen renovations, weddings, fall wardrobes, vacation itineraries, gift lists — often weeks or months ahead of purchase. Roughly 85% of weekly users say they've made a purchase based on a Pin. Around 96% of searches are unbranded, meaning the user is looking for a solution, not a brand. That gap is where new advertisers can win share without outbidding incumbents.
Pins compound. A Pin posted today can still drive impressions and clicks three months later. Promoted Pins continue generating organic engagement after paid spend ends — when a user saves a promoted Pin, the "promoted" label disappears, and what was paid media becomes earned reach. Roughly half of ad-driven purchases on Pinterest happen more than two weeks after the initial impression. This breaks most attribution models built for Meta's 7-day click window.
The audience skews differently. Around 70%+ of users are women, Gen Z is the fastest-growing cohort (now~42% of global users), and over 80% of the audience lives outside the United States. ARPU is heavily skewed toward the U.S. ($7.64 in Q3 2025) versus Europe ($1.31) and the rest of the world ($0.21). In other words, international markets remain drastically under-monetized. For brands with non-U.S. footprints, that's an arbitrage window.
The Pinterest ad ecosystem in 2026
Pinterest's ad inventory is now wider and more specialized than most marketers realize. The current format roster — per Pinterest's own ad spec documentation and up-to-date 2026 spec guides:
Standard Pin Ads. Single-image promoted Pins, recommended at 1000×1500 (2:3 aspect ratio). Native, low-friction, and the workhorse of most campaigns.
Video Pin Ads. Available in standard width (matching static Pin dimensions) and max width, which expands to fill the entire mobile feed. Autoplay triggers when 50% of the Pin is in view. Recommended runtime is 6–15 seconds for paid; 45–90 seconds for organic Video Pins. Aspect ratios from 1:1 to 9:16 are supported, with vertical performing best.
Carousel Ads. Up to 5 swipeable images in a single Pin, each with its own title, description, and destination URL. Strong for product ranges and step-by-step storytelling.
Collections Ads. A hero asset (image or video) followed by up to 24 secondary images, expanding into a full-screen mini-shop on tap. Designed for e-commerce catalogs.
Shopping Ads. Product-feed-driven single-image ads with the highest measured ROAS of any Pinterest format — averaging 2.3x against 1.7x for consideration and 1.2x for awareness campaigns. The natural format for retailers with synced catalogs.
Showcase Ads. A title card plus up to 4 swipeable feature cards, each supporting interactive overlays. Good for highlighting multiple products or features within a single creative unit.
Quiz Ads. Interactive title card → up to 3 multiple-choice questions → a personalized results card. Used heavily by beauty, fashion, and home brands to route users to product recommendations.
Idea Ads. The multi-page, full-screen storytelling format evolved from organic Idea Pins. Engagement rates typically 4–8x higher than standard Pins.
Premiere Spotlight. Pinterest's premium reservation product. A max-width video ad that takes the first ad slot on the home feed (page 2) or the first slot in the search carousel for an entire day. Around 50% of mobile screen real estate. Brands report 8–12x higher recall than standard placements; pricing reflects that.
This list grew. Three years ago, Pinterest essentially had Promoted Pins and Promoted Videos. The current spread reflects a platform deliberately trying to give performance advertisers and brand advertisers separate tools, instead of one generic ad unit.
Why video became the headline format
Pinterest's roots are static. So the video push deserves an explanation.
The performance gap is real. Pinterest's own creative benchmarks put video Pin ads at roughly 3.2x the engagement of static Pins, with about 2.4x higher brand lift. Save rates run 0.3–0.5% on video against 0.15–0.25% on static — a meaningful, consistent gap. Beyond the numbers, video answers Pinterest's core search behavior better than a still image: a user searching "small kitchen storage" is more convinced by a 6-second clip showing a drawer organizer in motion than by a glamour shot.
A few practical realities every marketer running Pinterest video should internalize:
- Sound is off. Around 85% of users watch without audio. If your story depends on voiceover, the story fails. Use captions, on-screen text, and visual hooks.
- You have ~1.7 seconds. That's the median scroll-stop window on Pinterest. The hook, the brand, and the value proposition need to land inside the first 3 seconds.
- Vertical wins. 9:16 and 2:3 outperform 1:1, which outperforms 16:9. Mobile-optimized vertical creative has been shown to drive completion rates up to 80% higher than horizontal across visual discovery platforms.
- 6–15 seconds is the paid sweet spot. Longer runs better organically, but paid placements perform best in the bumper-to-short-form window.
- Branding stays present. Show the logo or product within the first 3 seconds and hold it at the end. Pinterest's autoplay-then-scroll pattern means many viewers never reach the back half.
How targeting actually works on Pinterest
Pinterest's targeting stack has three layers that most advertisers think about, and a fourth that's becoming the differentiator.
Keyword targeting maps ads to user search terms. Because Pinterest is a visual search engine more than a feed, this layer is unusually powerful — closer in mechanics to Google Ads than to Meta. Match types matter; broad match on Pinterest tends to leak into adjacent intent that may or may not convert.
Interest targeting uses Pinterest's taxonomy of categories (home, beauty, food, etc.) and is most useful for top-of-funnel reach. It's blunt by design; performance campaigns rarely lean on it.
Audience targeting includes customer list match, retargeting via the Pinterest Tag, engagement audiences (people who've interacted with your Pins), and "actalikes" — Pinterest's lookalike equivalent, modeled on behavioral affinities rather than declared interests.
Contextual targeting is the layer that's been quietly transforming. Cookieless by definition, contextual targeting places ads based on what's in the surrounding content rather than who the user is. On a platform like Pinterest, where most engagement is content-driven rather than identity-driven, contextual signals can be more predictive than user-level data — and they remain stable even as third-party identifiers continue to degrade.
For static Pins, contextual targeting is relatively well understood: it operates on image classification, board context, and keyword adjacency. For video Pins, it's harder. Conventional contextual systems tag a video by metadata, title, and surface-level keywords — which means a yoga mat ad placed against "morning routine" videos may end up running against everything from skincare hauls to commute vlogs. The signal is too coarse for performance advertisers in regulated or specialized verticals.
This is where AI-powered video contextual platforms have started to fill the gap. PXLSTRM, the AI contextual targeting spinoff of Swiss/US AdTech firm Adello, is one of the better-known examples in the European market: its AI analyzes video content at the object, scene, and dialogue level — not just metadata — and clusters millions of analyzed videos by genuine semantic similarity.
The platform launched on YouTube in 2023, expanded to TikTok, then into Asia-Pacific, and as of March 2026, supports Pinterest campaigns across the DACH region (Germany, Austria, Switzerland), with reach to roughly 24 million high-intent users in those markets. Reported relevance uplift across markets averages above 100%, with comparative tests against YouTube TrueView showing meaningful media savings while reaching more on-topic audiences. For advertisers in regulated categories (alcohol, pharma, gambling, finance) — a category set that matters disproportionately in DACH — contextual video AI is rapidly becoming the path of least resistance to brand-safe scale.
The broader point: in 2026, "targeting on Pinterest" no longer means just keywords plus interests. It means a stack — first-party platform signals, behavioral audiences, plus a contextual video layer.
Pinterest's own AI: Performance+
Pinterest is also automating its way up the stack. Performance+ is the company's AI-driven campaign suite, comparable in spirit to Meta's Advantage+ or Google's Performance Max. It bundles automated bidding, creative optimization, and audience targeting under a single objective.
The numbers Pinterest reports on Performance+ adoption are strong: retail advertisers' spending on Performance+ saw an average 24% higher conversion lift, and mid-market and small advertisers saw meaningfully higher monthly spend growth post-adoption. CPA across Pinterest more broadly dropped roughly 28% year-over-year in Q4 2025, with Performance+ delivering ~18% lower CPA than manually optimized campaigns.
The trade-off is the same as on every automated platform: less manual control, less granular reporting, and a creative-quality dependency. Performance+ rewards advertisers with clean catalogs, multiple creative variants, and well-instrumented conversion tracking. Without those, the AI has nothing to optimize against, and the budget gets wasted on cheap but irrelevant impressions.
Measurement, attribution, and the long-tail problem
The Pinterest Tag — a JavaScript pixel — handles conversion tracking, retargeting audiences, and catalog measurement. The server-side conversion API is also available and increasingly recommended for accurate measurement under iOS privacy constraints.
The harder problem is attribution windows. Pinterest's purchase journey is long: as noted, roughly 50% of ad-driven purchases happen more than two weeks after first exposure. A 7-day click model — the default in most last-click systems — undercounts Pinterest dramatically. Marketers running unified MMM (marketing mix modeling) or MTA (multi-touch attribution) tend to discover that Pinterest's true contribution is significantly higher than last-click models suggest, particularly in home, fashion, and beauty.
Practically, this means Pinterest deserves longer attribution windows (28-day click, 1–7 day view-through at minimum) and incrementality testing rather than naive last-click ROAS comparisons.
What's coming in 2026 and beyond
Three structural shifts are worth tracking.
CTV expansion via tvScientific. Pinterest closed its acquisition of CTV ad-platform tvScientific in February 2026 and launched tvScientific by Pinterest shortly after, extending Pinterest's first-party audiences into connected TV inventory. Early test data from LG showed a 73% increase in unique households reached and a 24% lift in net new customers when Pinterest audiences were layered onto CTV. This effectively turns Pinterest into a cross-screen platform for the first time.
AI shopping agents. During Cyber Week 2025, around 20% of global e-commerce orders were influenced by AI shopping agents — an inflection point. Pinterest's visual search and product graph make it unusually well-positioned to be a source surface for those agents, which has implications for how brands structure product feeds and Pin metadata.
Video is the dominant ad format. Premiere Spotlight expansion, max-width video defaults, video shopping ads converting at higher rates than standard video, and 240% YoY video view growth all point in the same direction. Brands that haven't yet built a vertical-video pipeline for Pinterest will be at a structural disadvantage by the end of 2026.
The takeaway for advertisers
Pinterest in 2026 is not the platform marketers wrote off in 2019. It's a search-driven, intent-rich, increasingly AI-automated ad system with a long-tail attribution profile and an unusually strong fit for video — particularly contextual, brand-safe video. The advertisers winning on it are the ones treating it like a hybrid of Google Search and YouTube, not like a third Meta channel.
For non-U.S. markets, the structural under-monetization of European and rest-of-world inventory creates a real efficiency window — one that closes as more advertisers move in. The fundamentals (lower CPMs, less competition, an intent-rich audience, growing Gen Z share) won't last forever. They're priced into the next 12–24 months, not the next 5 years.
If your brand is investing in video and not yet running it on Pinterest, the question isn't whether to test — it's how fast you can get a vertical-first creative pipeline live.
January 2026 Opened With a 3.9% Drop
According to the European Automobile Manufacturers' Association, new vehicle registrations in the EU fell 3.9% year-over-year in January 2026, to 799,625 units. Gasoline-powered cars fell 28.2%. France was down 48.9%, Germany down 29.9%, Italy down 25.5%, and Spain down 22.5%.
Volkswagen is reported to be roughly 500,000 vehicles short of its annual targets — equivalent to two full plants' output. Audi is shedding 7,500 jobs by 2029.
Porsche is about 3,900. Suppliers Bosch, ZF, Continental, and Schaeffler announced sweeping cuts in 2024 and are still cutting.
Meanwhile, Chinese entrants are taking a share. BYD's battery electric vehicle (BEV) registrations rose 86% in January 2026. Leap Motor rose 357%.
This is the operating environment for automotive marketing in 2026.
Why the Squeeze Is Harder This Time
Past downturns were cyclical. Production paused, showrooms eventually refilled, and demand returned. 2026 is structural.
The supply side is cutting capacity, not pausing it. When suppliers disappear, model lineups narrow. Marketing teams end up with fewer products to sell and longer gaps between launches.
The buyer has already moved online. The Cox Automotive Car Buyer Journey Study 2025 reports that car buyers now spend around 14 hours and 19 minutes researching online, roughly 7 hours of it on specific vehicle research. They visit an average of 4.6 websites before contacting a dealer. Over 70% use a smartphone as their primary research device.
The electrification message has to be rebuilt. Dutch BEV registrations jumped over 30,000 units in December 2025 on tax scheme changes, then fell 35.4% in January 2026. Campaigns written six months ago are already outdated in several markets.
The old media mix — TV brand campaign plus dealer print ads plus paid search plus some Facebook — no longer matches the buyer or the product cycle.
Six Moves That Work Now
Each move below addresses a specific gap that 2026 has exposed. They are not sequential. Most automotive brands will run several in parallel.
1. Activate First-Party Data Before Third-Party Signals Fully Disappear
First-party data is data you own: test-drive requests, service records, configurator sessions, newsletter signups, CRM records.
Audience segments built on 2022 third-party cookie data are decaying. First-party data is the asset that survives the change. It is what direct-to-consumer competitors are already building on.
Practical steps:
- Unify web, dealership, and aftersales data into a single addressable record per household.
- Suppress existing customers from acquisition campaigns to avoid wasted spend.
- Retarget unfinished configurator sessions with offers tied to the exact trim chosen.
- Build lookalike audiences in cookieless environments using your own customer base as the seed.
2. Move Budget and Measurement to Mobile
Over 70% of automotive internet shoppers use a smartphone during the car-buying journey. Desktop-first analytics still dominate many OEM dashboards, which is a mismatch.
A mobile-first stack for automotive marketing in 2026 includes:
- Vertical video creative (9:16) built for the phone, not the TV.
- Mobile DSP platforms that can bid on in-app inventory where buyers research.
- Click-to-call and click-to-dealer-locator actions are native to the ad unit.
- Geolocation targeting around dealerships, service centres, and competitor locations.
Programmatic mobile ads now account for the majority of premium mobile inventory. Skipping this layer means advertising against the wrong screen.
3. Use Contextual Video Targeting Across YouTube, TikTok, and Pinterest
With signal loss growing, contextual advertising is rebuilding as the primary way to match message to audience on video platforms. The logic is direct: show a car ad next to content the buyer is already consuming — motorsport, road trip videos, EV reviews, luxury lifestyle, family vlogs — rather than inferring a demographic profile from cookies.
This is where Adello's PXLSTRM applies directly. PXLSTRM is a patented AI-powered contextual video targeting solution for YouTube, TikTok, and Pinterest. It analyses video content, dialogues, and on-screen objects, and clusters millions of videos into behaviour-aligned categories, including Automotive, Sport, Luxury, Travel, and Shopping.
An Adello benchmark comparison showed PXLSTRM delivering +53.9% more relevant impressions and +118% more relevant channels against TrueView, while lowering eCPM by 29.38%. For automotive campaigns that need brand-safe placements at scale — particularly in markets with restricted content environments — this is a measurable advantage.
4. Rebuild Audience Targeting on Deep Behavioural Signals
Segment-average optimisation — the classic programmatic approach — is no longer accurate enough when lead volumes are shrinking. Optimisation at the individual impression level is what Adello's deep-learning DSP does. Users exposed to an ad are followed through the full conversion funnel, not just to the click. Algorithms predict the conversion probability of every single impression, taking prior data and new signals into account.
Adello's Audience Class includes Automotive as a dedicated segment, built on in-app and contextual signals. For OEMs and importers, this enables:
- Lookalike modelling from existing service customers.
- Suppression of non-converting traffic types before the bid.
- Full-funnel measurement from impression to dealership visit.
- Brand safety and fraud detection are applied pre-bid, so invalid traffic is eliminated before spend.
More than 500 advertising partners, including BMW, use Adello's platform across Europe, North America, and Asia.
5. Extend Campaigns into Programmatic DOOH and CTV
Two channels are growing while linear TV contracts:
- Programmatic Digital Out-of-Home (pDOOH): highway screens, petrol stations, shopping centres, transit hubs. Bought in real time, with creative variations by daypart, weather, or inventory availability.
- Connected TV (CTV) ads: streaming inventory on smart TVs, measurable at the household level, and addressable with first-party data.
The real shift is combining them. Mobile programmatic, pDOOH, and CTV now run through the same DSP and measurement layer, which means one audience and one attribution framework across screens. Industry analysts at eMarketer flag CTV and pDOOH among the fastest-growing programmatic categories through 2026. Running them as a coordinated omnichannel strategy — rather than three separate buys — is what turns them into a reach and frequency system instead of parallel line items.
6. Treat Generative Engine Optimisation (GEO) as a Core Channel
The Cox Automotive study found that approximately 19% of all vehicle buyers and 25% of new-vehicle buyers in the US used AI chatbots (ChatGPT, Copilot) or AI-generated search overviews (Google, Gemini) during research in late 2025.
If the brand page is not structured for AI retrieval, it is invisible at that moment. GEO practices that matter for automotive pages:
- Definition-first paragraphs for every model, trim, and financing term.
- FAQ blocks with standalone question-and-answer pairs, marked up with the FAQ schema.
- Specific, cited statistics rather than generic marketing claims.
- Content freshness — AI engines prefer content that is on average 25.7% fresher than traditional search citations.
Brands cited in AI overviews see +35% organic clicks and +91% paid clicks compared with those not cited. The cost of being absent is measurable.
Summary Table: What Each Move Solves
| Move | The 2026 gap it closes | Primary channel |
| First-party data activation | Third-party cookie decay | CRM, DSP |
| Mobile-first stack | 70%+ buyers on smartphone | In-app, mobile web |
| Contextual video targeting | Signal loss on social video | YouTube, TikTok, Pinterest |
| Deep audience targeting | Segment-average inaccuracy | Programmatic display, video |
| pDOOH and CTV | Linear TV decline | Out-of-home screens, streaming |
| GEO | AI search displacing Google | Owned web content |
Why Now, Not Next Quarter
Three conditions make waiting expensive.
Share is being redistributed in real time. When an EU market drops 48.9% on ICE, and Chinese BEV entrants grow triple-digit, the 2027 order book is being shaped now by the brands still advertising.
Measurement changes compound. Cookieless adoption, AI-driven search, and first-party data consolidation each add a layer of complexity every quarter. A team that starts rebuilding in Q4 2026 is two years behind a team that started in Q4 2024.
Media inflation is returning. As automotive marketers who paused in 2024–2025 come back, CPMs on video and mobile are rising. Early commitments lock in better rates.
What customers must do: audit the current mix against these six moves, identify which one closes the biggest gap, and deploy a first test within the next 60 days. A test on a single model line is enough to produce the internal evidence needed for a full-year plan. Request a demo with Adello to scope the first test.
The automotive marketing playbook of 2019–2022 no longer fits the 2026 market. Sales are down, competition has shifted east, and the buyer has moved to mobile and AI-assisted search. Brands that align their media stack — first-party data, mobile, contextual video, deep audience targeting, pDOOH and CTV, GEO — will protect share while the market corrects. The ones that wait will be paying higher CPMs to reach a smaller audience.
🚙 Marketing budget cut for 2026, but the showroom targets didn't move?
Book a 20-minute scoping call with Adello. We'll map your current media mix against the six moves above and show where the biggest gap is.
FAQ
Why is contextual advertising replacing cookie-based targeting for automotive? Third-party cookies are being deprecated, and audience segments built on them lose accuracy quarter by quarter. Contextual advertising matches ads to the content being consumed instead. AI-powered solutions such as PXLSTRM analyse video content, dialogue, and on-screen objects to assemble precise, brand-safe audience clusters at scale.
What role does programmatic advertising play in automotive in 2026? Programmatic advertising is the default buying method for display, mobile, video, CTV, and DOOH. It enables real-time bidding at the individual impression level, brand safety and fraud detection pre-bid, and unified measurement across channels.
How is AI changing automotive search and research? Around 19% of all vehicle buyers and 25% of new-vehicle buyers used AI chatbots or AI-generated search overviews during research in late 2025. Brands cited in AI overviews see a +35% organic and +91% paid click uplift. Pages need GEO optimisation — structured data, definition-first paragraphs, and fresh statistics — to be retrieved by these engines.
Is mobile advertising still the priority for car brands in 2026? Yes. Over 70% of automotive internet shoppers use a smartphone as their main research device. A mobile DSP platform, vertical creative, and geolocation targeting are required, not optional.
AI Shopping Agents Are Already Processing Billions in Transactions
During Cyber Week 2025, 20% of global e-commerce orders were influenced by AI agents, according to Salesforce. AI chatbot traffic to U.S. retail sites grew 670% year-over-year during that same holiday season, as Adobe reported. And in January 2026, Google CEO Sundar Pichai announced the Universal Commerce Protocol (UCP) at the National Retail Federation conference — a clear signal that the infrastructure for AI-completed purchases is no longer theoretical.
McKinsey projects the global agentic commerce opportunity at $3 trillion to $5 trillion by 2030, with up to $1 trillion in U.S. B2C retail alone. AI platforms are expected to account for 1.5% of total U.S. retail e-commerce sales in 2026 — roughly $20.57 billion — nearly quadruple the 2025 figures, per EMARKETER.
These are not projections from AI enthusiasts. These are numbers from McKinsey, Morgan Stanley, and Forrester. The shift is measurable, and it has direct consequences for how brands advertise.
What Is Agentic Commerce?
Agentic commerce is an online shopping model where AI agents make purchasing decisions across the entire buying journey — from product discovery through checkout and post-purchase support — on behalf of the consumer.
The consumer sets intent and constraints. The AI agent handles research, comparison, selection, and in some cases, the transaction itself.
This is different from conversational commerce, where a chatbot recommends a product and the consumer still completes the purchase manually. In agentic commerce, the agent queries product catalogs, evaluates pricing and availability in real time, checks shipping and return policies, and can execute the checkout.
Think of it this way: a chatbot that suggests a moisturizer based on your skin type is conversational commerce. An AI that queries multiple skincare brands, compares ingredients and prices, and selects the best option within your budget — that is agentic commerce.
Why Agentic Commerce Changes Everything for Advertising
For over two decades, digital advertising operated on a predictable model. Brands competed for attention on search results pages, product listing pages, and social feeds. The consumer clicked, browsed, compared, and purchased. Advertisers measured clicks, impressions, and conversions.
Agentic commerce removes the session layer. The consumer no longer opens ten tabs. They no longer scroll through product listing ads. They describe what they need, and the agent handles the rest.
This creates a structural problem for advertisers. If the AI agent does not surface your product, your brand is not part of that transaction. The consumer never sees your ad, your listing, or your landing page. The entire traditional advertising funnel — awareness, consideration, conversion — gets compressed into a single AI-mediated decision.
U.S. advertisers will spend $71.98 billion on retail media in 2026, up 18.7% from 2025, according to an EMARKETER March 2026 forecast. AI shopping agents that bypass traditional search and browse behavior directly reduce the value of sponsored product placements, display ads, and keyword advertising.
The metric that matters is shifting. Click-through rate measures human interaction with a page. In agentic commerce, the more relevant metric is the AI citation rate — whether a shopping agent retrieves, references, or recommends your product during fulfillment.
How Agentic Commerce Works: The Three-Layer Architecture
When a consumer types a request like "Find me running shoes under $120, size 10, that ship before Thursday," the AI agent activates three distinct layers:
Intent Layer. The AI model parses the request, extracting constraints: budget, size, delivery window, brand preference, and return policy requirements. This is where natural language understanding meets structured product queries.
Commerce Layer. The agent queries product catalogs, pricing services, inventory feeds, and shipping estimators through structured APIs. It evaluates options against the consumer's constraints and ranks results by relevance, trust signals, and fulfillment reliability.
Transaction Layer. For approved purchases, the agent communicates with the merchant's checkout systems using protocols like the Universal Commerce Protocol (UCP) or the Agentic Commerce Protocol (ACP). Payment is processed through pre-authorized methods, and the agent handles order confirmation, tracking, and returns.
The critical insight: this architecture does not rely on websites, product pages, or traditional ad placements. It relies on structured data, API accessibility, and machine-readable product attributes.
The Key Players Building the Agentic Commerce Ecosystem
| Platform | Protocol / Product | Status (Q1 2026) |
| Universal Commerce Protocol (UCP), AI Mode checkout, Business Agent | Active. Brands like Keen Footwear and Pura Vida are already selling through it | |
| OpenAI / Stripe | Agentic Commerce Protocol (ACP), ChatGPT Instant Checkout | Live since September 2025 for 900M+ weekly ChatGPT users |
| Microsoft | Copilot Checkout | Active. Brands like Keen Footwear and Pura Vida already selling through it |
| Shopify | Agentic Storefronts | Available to millions of Shopify merchants as of March 2026 |
| Perplexity | Instant Buy (PayPal-powered) | Live with conversational product discovery and checkout |
| Amazon | Rufus (proprietary agent) | Restricted ecosystem. Sponsored prompts available |
Google, OpenAI, and Microsoft are building open or semi-open ecosystems. Amazon is taking a more controlled, proprietary approach. For advertisers, this fragmentation means maintaining product data for multiple agent ecosystems simultaneously.
What Brands and Advertisers Must Do: 5 Actionable Strategies
1. Treat Product Data as Advertising Infrastructure
In an agentic commerce environment, your product catalog becomes your most important advertising asset. AI agents do not read display ads. They read structured data feeds.
If your product data is incomplete, inconsistent, or lacks machine-readable attributes, the AI agent skips your product without a human ever seeing it. The difference between a "correct" catalog and an "optimized" catalog is no longer a marginal performance lift. It determines whether you are in or out of the conversation.
Priority actions: enrich product descriptions with real use-case language, add structured attributes for compatibility, accessories, substitutes, FAQs, and keep pricing and inventory synchronized in real time.
2. Invest in AI Engine Optimization (AEO) Alongside SEO
SEO was built for keyword-based search. AI agents operate differently. They interpret intent, evaluate tradeoffs, and surface products based on structured relevance, not keyword density.
Answer engine optimization and generative engine optimization are becoming operational requirements. This means structuring content so that AI systems can accurately represent your products when consumers ask questions across ChatGPT, Gemini, Perplexity, and Copilot.
Bain & Company estimates that 30% to 45% of U.S. consumers already use generative AI to research and compare products. If your brand does not appear in these AI-driven discovery moments, you lose consideration before the consumer even reaches a traditional advertising surface.
3. Build Structured Fulfillment Signals for Agent Legibility
AI shopping agents struggle with ambiguity. They need delivery windows, shipping costs, and return terms that are structured, comparable, and consistent. If this information is unclear across channels, the agent defaults to a competitor whose offer is easier to execute.
This is a form of competitive advantage that has nothing to do with creative or messaging. It is purely operational. Make your delivery promises, return policies, and availability data machine-readable and consistent across every channel.
4. Run Contextual and Cookieless Advertising to Reach Consumers Before Agent Delegation
Here is the part most advertisers are not discussing yet: agentic commerce compresses the funnel, but it does not eliminate the need for brand awareness and preference. Consumers still need to form opinions before they instruct their AI agents.
A consumer who tells their agent, "find me waterproof running shoes under $150 with next-day delivery," has already been influenced by something — a contextual video ad they saw during a trail running review, a brand mention in a comparison article, or a recommendation from a creator they follow.
This is where contextual targeting and cookieless advertising become critical. Brands that reach consumers in the right context — while they are still forming preferences — can shape the instructions consumers give to their AI agents.
Adello's cookieless advertising stack and its mobile DSP further support this approach, delivering programmatic advertising across mobile, DOOH, and video channels without reliance on deprecating identifiers.
The outcome: brands that invest in contextual, privacy-compliant advertising build the upstream awareness that shapes downstream agentic purchases.
5. Prepare for Agent-to-Agent Negotiation in B2B
Forrester predicts that by the end of 2026, 1 in 5 B2B sellers will face AI-powered buyer agents delivering dynamically generated counteroffers. This means advertising and pricing strategies need to account for machine-to-machine interactions, not just human decision-makers.
B2B advertisers should begin structuring their pricing, terms, and product data for agent consumption now — before competitors establish presence in these emerging channels.
Why Acting Now Matters: The Window Is Narrow
Retailers that deployed AI capabilities between 2023 and 2024 saw 14.2% sales growth, compared to 6.9% for those without AI capabilities, according to Capital One Shopping research. The performance gap is accelerating, and it applies to advertising strategy as well.
Shoppers directed to retail sites from AI platforms are 30 times more likely to make a purchase, per Adobe data cited by EMARKETER. That is an extraordinary conversion signal — but only for brands whose products the AI agent can find, evaluate, and recommend.
The practical window for establishing presence in agentic commerce ecosystems is 2026. The protocols are being standardized now. The consumer behaviors are forming now. The brands that structure their data, advertising, and fulfillment for AI agent accessibility in this window will have a measurable advantage over those that wait.
The Advertising Playbook Is Being Rewritten
Agentic commerce does not replace traditional advertising overnight. Consumer trust is still developing — only 46% of shoppers fully trust AI recommendations, and 89% still verify information before purchasing, according to the IAB. High-value and identity-sensitive purchases will remain human-directed for now.
But the direction is clear. The consumer journey is moving from pages to conversations. From clicks to delegated decisions. From keyword-based discovery to structured-data-driven recommendations.
Advertisers who prepare for this shift now — by investing in AI agents for advertising readiness, contextual targeting, cookieless advertising solutions, and structured product data — will be positioned to capture demand in a channel that is growing at multiples of traditional e-commerce.
The brands that will succeed in agentic commerce are the ones that are already visible, already trusted, and already structured for the machines that will increasingly do the shopping.
Marketing teams face a paradox. There are more AI tools available than ever — hundreds of platforms across content, advertising, analytics, automation, and personalization. Yet most teams report the same symptoms: fragmented workflows, inconsistent output quality, and rising tool costs that outpace measurable returns.
The root cause is straightforward. Most teams are collecting tools instead of solving problems. They sign up for a content generator, an SEO optimizer, an ad creative platform, a social scheduler, and a CRM with AI features. Each tool works in isolation. None of them talks to each other in meaningful ways. The result is a bloated marketing stack that creates more operational overhead than it eliminates.
There is also a skills gap. Only about 17% of marketing professionals have received detailed AI training. That creates a disconnect between tool capability and team competency. The tools are getting smarter. The teams using them are still figuring out prompt engineering and workflow design.
For marketing leaders evaluating their AI stack in 2026, the question is no longer whether to adopt AI. The question is which specific tools solve which specific bottleneck — and whether those tools can integrate into existing workflows without adding complexity.
Where AI Tools Deliver Measurable Impact in Marketing
Not all AI marketing categories deliver equal returns. Based on current data and documented outcomes, here are the areas where AI tools create the most measurable value for marketing teams in 2026.
Workflow Automation and No-Code AI Orchestration
Beyond custom agents, there is a growing layer of no-code and low-code automation tools that let marketing teams build AI-driven workflows without engineering resources.
Gumloop connects any LLM model to internal tools and workflows without code. Teams at Webflow, Instacart, and Shopify use it for tasks like sentiment analysis on social media, automated lead enrichment, and multi-step campaign orchestration.
n8n is an open-source alternative that gives technical teams full control over workflow logic while still offering a visual interface. Both integrate with CRMs, email platforms, analytics dashboards, and content management systems.
Agentic automation tools have been shown to reduce task completion time by 76% compared to manual execution. Practical applications include lead scoring and routing, automated campaign reporting, social listening alerts, and content distribution sequences.
AI-Powered Video and Creative Production
Video content demand continues to grow, and AI production tools are reducing both cost and turnaround.
Synthesia produces professional videos using AI-generated avatars and voiceovers in 160+ languages, reducing production time by up to 90%.
Creatify generates video ads from product URLs — paste a Shopify or Amazon link, and the platform produces 5–10 script variations optimized for TikTok, Meta, or YouTube in under 10 minutes.
Captions automates short-form video editing for TikTok, Reels, and YouTube Shorts — adding zooms, transitions, B-roll, and sound effects based on content analysis.
AI for Email Marketing and Personalization at Scale
Email marketing remains one of the highest-ROI channels, generating roughly $36–$42 for every dollar spent. AI tools in this category focus on send-time optimization, subject line testing, dynamic content personalization, and predictive churn modeling.
Platforms like ActiveCampaign, Klaviyo, and HubSpot now embed AI features directly into their existing subscription tiers. Automated email campaigns generate approximately 320% more revenue compared to non-automated campaigns. The AI layer adds predictive audience segmentation and real-time personalization that manual setup cannot replicate at scale.
Contextual Video Targeting With PXLSTRM by Adello
AI advertising spending is projected to rise by more than 60% through 2026. AI-driven ad campaigns report 41% higher conversion rates on average. But there is a specific problem that general programmatic platforms do not solve well: contextual precision in video environments.
PXLSTRM, developed by Adello, fills this gap using patented AI to analyze video content at the object, dialogue, and scene level. Instead of targeting based on what a user has searched or browsed, PXLSTRM clusters millions of videos by their actual content — identifying behavioral affinities inside videos rather than relying on surface-level interest categories.
Social Listening and Competitive Intelligence
Understanding what audiences say about your brand — and your competitors — in real time is no longer optional.
Brandwatch processes social media conversations, reviews, and digital signals at scale, using AI to categorize mentions by topic, sentiment, and source.
Brand24 offers a lighter-weight alternative with real-time mention monitoring and influencer identification.
For competitive intelligence, Browse AI turns any public webpage into a live database without code. Marketing teams use it to build self-updating competitor pricing dashboards, monitor SERP rankings by location, and track product changes across rival sites. It ships with 250+ prebuilt robots for common monitoring tasks.
Custom AI Agents by Lab51
The fastest-growing segment in marketing AI is agentic AI — systems that can plan multi-step actions, execute across platforms, and adjust without human instruction at each step. The agentic AI market is projected to reach $10.8 billion in 2026 and grow to $196.6 billion by 2034. Gartner projects that by 2028,60% of brands will use agentic AI for customer interactions.
Lab51 builds custom AI agents tailored to specific business workflows. Instead of selling a generic product, Lab51 starts by analyzing a company's business model, customer touchpoints, and existing tools. From there, they architect and deploy AI agents that sit inside the client's actual operations — handling customer inquiries, automating competitive intelligence, managing multi-platform engagement, and feeding structured insights back into marketing and sales processes.
AI marketing tools in 2026 are no longer experimental, but a part of operational infrastructure. The teams that will perform best over the next 12–24 months are those that choose tools based on measurable bottlenecks, integrate them into existing workflows, and maintain the editorial judgment and strategic direction that AI cannot replace. Start with the problem, not the tool.
Kuala Lumpur, March 2026 — Adello, a leading AdTech company with patented AI technology and 17 years of operational history, announces the return of Cheong Wei Mung to its commercial team as Sales Consultant, based in Kuala Lumpur, Malaysia. Wei Mung previously worked with Adello and brings with her both institutional knowledge of the company's technology and established relationships in the Malaysian market.
Her background spans digital advertising and client services. Before rejoining Adello, she held a Client Services Associate role at Yahoo Malaysia — giving her early exposure to digital media operations and the regional advertising ecosystem at scale.
Her return is part of Adello's continued expansion across Southeast Asia. Over the past year, the APAC team has grown steadily — adding client-facing roles across key markets to meet rising demand from brands and agencies in the region.
Southeast Asia's mobile advertising market is projected to grow approximately 23% between 2023 and 2028, driven by smartphone penetration, rising digital ad spend, and increasing demand for contextual targeting. Malaysia, as a regional hub for digital commerce and media buying, sits at the center of that growth.
Wei Mung's focus will be on client acquisition and partnership development across the Malaysian market — supporting brands and agencies from initial evaluation through campaign execution.
Cheong Wei Mung said, "Coming back to Adello feels like the right move at the right time. The digital advertising landscape in Malaysia has matured significantly, and I'm excited to reconnect with clients and help them get real value from Adello's advanced technology."
About Adello Adello analyzes human behavior in real-time and combines it with fully automated, self-learning technology for mobile marketing performance, operating across Europe and APAC. The company's technology includes PXLSTRM for contextual video targeting and Privately for on-device age verification in regulated industries. Adello serves brands and agencies seeking measurable, privacy-compatible advertising outcomes.
96% of Pinterest Searches Are Unbranded — and That's the Opportunity
Here is a number that changes how you should think about Pinterest advertising for travel: 96% of top searches on the platform contain no brand name whatsoever.
People are not searching for your hotel, your ski resort, or your destination. They are searching for "highland aesthetic," "adventure tourism ideas," or "spring destination Europe."
Pinterest's own Predicts 2026 report — compiled from 600 million monthly active user searches — shows travel searches moving in two clear directions: adventure-focused "Darecations" (searches for adventure tourism up 75%, auto racing events up 85%) and atmospheric, remote destinations like the Scottish Highlands (searches for "scotland highlands aesthetic" up 465%). Both directions are search-intent driven. Both represent traveler decisions forming weeks or months before booking.
For hospitality and tourism marketers, this is a structural advantage. The question is whether you are set up to reach people at that specific moment — or whether you are running ads that show up too late, in the wrong context, with the wrong signal.
Travel Intent Forms Early, But Most Ads Target Too Late
Travel decisions are among the longest purchase cycles in consumer behavior. Research from Amra and Elma LLC found that 8 out of 10 travelers use their phones to book trips — but the inspiration phase starts well before any booking engine interaction. By the end of 2023, international tourist arrivals had recovered to 88% of pre-pandemic levels, and nights spent in Q1 2024 exceeded the equivalent period in 2019. Demand is back. But competition for that traveler's attention earlier in the funnel — during inspiration and consideration — has increased at the same rate.
Pinterest is structurally positioned at that inspiration stage. It operates more like a visual search engine than a social platform. A user saving pins about alpine landscapes in February is building a travel plan, not scrolling passively. They are signaling destination intent, format preference (immersive, scenic, outdoor), and timing — all before they open a booking site.
Most tourism advertisers are not capturing this. Travel industry digital ad spending grew 132% to $344 million in 2023 and continues to climb. But the majority of that budget flows into Google Search (high intent, high cost, short window) or Meta (broad awareness, high competition, declining organic reach). Pinterest sits between those two stages — reach at the intent-formation phase — and it remains underdeveloped in most tourism advertising mixes.
Why Generic Interest Targeting Fails on Pinterest
The standard approach on Pinterest is to run promoted pins targeted at "travel" or "outdoor adventure" interest categories. This works at a basic level. But it misses what makes the platform valuable.
When 96% of searches are unbranded and discovery-first, the user is in a genuinely open state. They have not made a decision. Your ad does not need to interrupt — it needs to match the visual and contextual moment they are in. An alpine skiing video that appears inside a board about "winter sport destinations" lands differently than the same video shown to anyone tagged as "travel enthusiast."
Generic interest targeting flattens this. It reaches people who have previously shown travel interest, but it does not differentiate between someone researching budget city breaks and someone deep in a planning session about ski resorts in Austria. The result is wasted impressions on audiences who are not in the right mental frame — and missed impressions on those who are.
Adello's PXLSTRM campaign data illustrates this gap. In YouTube contextual targeting, standard placement (TrueView) reached relevant impressions 45% of the time. PXLSTRM's contextual video targeting reached 98% relevant impressions — a 118% improvement — while simultaneously reducing eCPM by approximately 29%. The mechanism: analyzing the actual content context of the video environment, not just audience demographics or declared interests.
The same gap between context-matched and interest-matched targeting exists on Pinterest. And the opportunity to close it is now accessible.
6 Approaches to Advertising Hospitality and Tourism on Pinterest
1. Pinterest Video Pins and Idea Pins for Destination Storytelling
Pinterest users respond to content that shows a place. Standard static pins still work for product-style visuals (hotel room, dish, slope view). But for travel specifically, video formats — Video Pins and multi-frame Idea Pins — produce measurably higher engagement because they communicate atmosphere and scale.
Practically, this means:
- Video Pins (6–15 seconds) work best for destination reveal moments: aerial approaches, landscape transitions, seasonal moments. No dialogue required. Captions should include destination-specific terms that Pinterest's algorithm will index.
- Idea Pins (multi-page, persistent format) are suited for itinerary-style content: Day 1 in the Dolomites, three-day ski itinerary, spring hiking guide. These remain discoverable for months after posting.
- Both formats benefit from high-resolution, color-accurate production. Pinterest's user base skews toward planners who curate carefully — low-quality visuals are filtered out in the discovery algorithm.
Operational note: Pinterest's video ads do not autoplay with audio in the feed. Visual communication must carry the message without relying on sound.
2. Pinterest SEO: Keywords Drive Discoverability Before Ads Do
Pinterest functions as a search engine. Board names, pin titles, and descriptions are all indexed. For paid campaigns, the keyword strategy that you would apply to a Google Search campaign applies here — but with visual intent context.
High-value keywords for alpine and hospitality destinations currently include location + activity combinations ("austria ski resort 2026," "south tyrol spring hiking"), aesthetic descriptors ("highland aesthetic," "mountain lodge interior"), and experiential phrases tied to Pinterest's 2026 trend data ("adventure tourism europe," "remote destination travel").
Organic keyword optimization compounds the value of paid placements. A destination board that has built consistent search authority over six months will receive algorithmic preference — organic saves and engagement reduce the effective cost of promoted pins targeting the same audience.
Build the organic content layer first, then allocate ad budget to amplify what is already performing.
3. Pinterest Top of Search Ads for High-Intent Destination Queries
Pinterest launched Top of Search ads in September 2025. During testing, these placements produced 29% higher click-through rates than standard in-feed placements. The mechanism is direct: when a user searches "ski resort austria" or "alpine holiday spring," a Top of Search ad appears before organic results.
This is the closest equivalent to Google Search advertising on Pinterest — placement is triggered by a specific query, not an interest profile. For tourism brands with defined geographic targets, this format justifies higher CPM because the search signal is explicit and narrow.
Qualification logic for this format:
- Destination is specific enough to define search terms (not "travel" but "skiing dolomites")
- Budget allows for CPM at a competition-driven rate in the relevant market
- Landing page matches the destination and format of the pin (mismatch kills conversion rate)
4. Audience Segmentation Using Life Events and Behavioral Signals
Pinterest's audience targeting includes a life events category that is particularly relevant to travel: "planning a trip," "newly engaged" (honeymoon intent), "planning a move" (relocation tourism), seasonal peaks. These are declared intent signals, not inferred interests.
Layering life events onto geographic targeting allows meaningful segmentation without requiring large creative budgets:
| Audience Signal | Campaign Type | Format |
| Planning a trip + Germany/Austria/CH | Destination awareness | Video Pin |
| Newly engaged + Western Europe | Honeymoon package | Idea Pin |
| Seasonal (December–February) + skiing interest | Winter sport offer | Promoted Pin |
| Previous website visitor | Retargeting | Standard Pin |
For DACH-market tourism brands, combining geo-targeting (AT, DE, CH) with life events reduces wasted impressions significantly compared to broad interest categories.
5. Contextual Video Targeting via PXLSTRM for Pinterest
Adello's PXLSTRM technology has recently expanded to Pinterest placements, adding to its existing YouTube presence. PXLSTRM operates differently from Pinterest's native targeting system. Rather than targeting users based on declared interests or demographic data, it analyzes the content environment — what type of content surrounds a given video placement — and matches ads to contextually relevant moments.
In practice for tourism and hospitality: a video ad for a ski resort in Schladming would appear within Pinterest video content contextually related to alpine landscapes, winter sports, outdoor adventure, or Austrian travel — not simply to anyone tagged as "travel interested." The distinction matters because Pinterest users in active planning sessions produce denser contextual signals than standard interest profiles can capture.
What this addresses operationally:
- Impression relevance rate increases from standard ~45% to 98% under contextual targeting (measured in analogous YouTube deployments)
- Brand safety: ads do not appear in unrelated content contexts
- Budget efficiency: lower eCPM on relevant impressions (~29% reduction observed in comparable campaigns)
For tourism brands running mobile programmatic video on Pinterest, PXLSTRM's contextual layer provides targeting precision that platform-native tools do not. The result is a higher proportion of impressions seen by users who are actively engaged with travel content — the segment most likely to save, click, and convert.
The 2026 Planning Window Is Already Open
The Pinterest Predicts 2026 report is based on search data from September 2023 through August 2025. The trends it identifies — adventure tourism, remote atmospheric destinations, experience-first travel — are not forecasts. They are already present in the platform's search behavior. The recommendation to act on them in 2026 means the planning window is already open.
Tourism brands that build Pinterest presence and audience authority in Q1 and Q2 2026 will compound against those who wait until peak season. Pinterest's algorithm rewards consistent, high-engagement content with increasing organic distribution over time. Paid campaigns launched before destination interest peaks will benefit from lower competition CPMs and established pin authority.
There is also a practical budget argument. The Social/YouTube/Pinterest ad cluster represents 19,080 monthly search volume in English, with Adello's current coverage rated as "Very Low" — meaning the competitive pressure on these placements has not yet reached the saturation of Google or Meta. Early-mover allocation while CPMs remain below their likely 2027 ceiling is a straightforward efficiency argument.
Specifically for DACH-market tourism brands: the "marketing für restaurants" and hospitality vertical keywords, where Adello is already ranking (position 21), signal an existing audience that responds to tourism content. Pinterest advertising, coordinated with a programmatic mobile DSP campaign, extends the same reach into the visual planning phase.
Pinterest is a structurally useful channel for tourism and hospitality advertising because it captures users at the formation stage of a travel decision — before destination loyalty is set, before booking intent narrows into price comparison.
The platform rewards content that matches the user's current moment of exploration: contextually relevant video, destination-specific keywords, mobile-native format.
The travel sector's digital ad spending continues to grow. The question is where in the funnel the budget is deployed.
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The AI Visibility Paradox
Today, 75% of a marketing agency's inbound leads come from visibility in ChatGPT and similar AI platforms, not traditional search. Meanwhile, 95% of B2B marketers have adopted AI content tools. Yet only 39% report improved performance.
This gap exposes a structural problem: Brands across technology, healthcare, real estate, and tourism are producing exponentially more content while simultaneously losing visibility where it matters.
This is why it is happening: AI-powered answer engines now extract up to 48% of their response content from open sources without directing users to brand websites. Your content becomes a source, not a destination. The question isn't whether your audience can find you through traditional search anymore. It's whether AI systems recognize your brand as authoritative enough to cite when making recommendations.
What Changed: From Clickable to Citable
For two decades, digital marketing operated on a simple premise: Rank high in search results, capture clicks, convert visitors. Traditional SEO rewarded keyword optimization, backlink profiles, and page speed. The conversion funnel was linear.
Today, that model is breaking.
AI assistants now sit between your brand and your audience. Most queries never generate a website visit. Zero-click searches are the new normal.
This creates three compounding problems. First, traditional traffic metrics no longer correlate with influence. A brand can lose 40% of its website visitors while simultaneously increasing its impact on purchase decisions if AI platforms frequently cite its expertise.
Second, content volume has become a liability. The average B2B brand publishes 5x more content than in 2020, creating internal competition for attention.
Third, AI-generated content floods every channel with grammatically correct but strategically hollow material that commodifies entire categories.
Solutions for AI-Era Brand Relevancy
Build Content Designed for Extraction, Not Just Reading
AI systems need clear signals to understand when and how to cite your brand. This requires structural changes to how content is created.
Implement extractable frameworks. Each piece should include one-sentence takeaways, clear definitions, specific methodologies, and quantified outcomes.
AI rewards precision. Instead of "our platform improves efficiency," write "reduces processing time from 14 days to 3 days through automated workflow routing." The second version gives AI systems concrete information they can extract and attribute.
Create topic clusters with authoritative depth. Rather than publishing 50 surface-level blog posts, develop comprehensive resources on 10 core topics. Each cluster should include primary research, case studies with specific metrics, and documentation of methodology. AI platforms favor sources that demonstrate subject matter depth over breadth.
Establish First-Party Data Architecture for Privacy-Compliant Targeting
Third-party cookies are gone. Contextual signals and first-party data now determine targeting precision.
Build zero-party data collection mechanisms. Interactive tools, preference centers, and value exchanges generate data that users actively provide.
Implement progressive profiling. Rather than demanding 12 form fields upfront, collect 2-3 pieces of information per interaction across multiple touchpoints. After five interactions, you have comprehensive account intelligence without friction.
Connect data sources into unified customer views. Most organizations collect first-party data in six separate systems that never communicate. CRM, marketing automation, website analytics, event registration, support tickets, and product usage each hold partial pictures. Integration creates targeting accuracy that third-party cookies never could.
Limitation: First-party strategies only work when traffic exists. Brands with limited awareness need complementary approaches to generate initial engagement.
Implement Thought Leadership Programs With Verifiable Expertise
AI platforms favor sources that demonstrate original thinking backed by empirical evidence.
Only 4% of B2B organizations rate their thought leadership programs as "leading", creating an opportunity for brands willing to invest in substantive content.
Document proprietary methodologies transparently. Share the frameworks your organization uses to solve problems, including decision criteria, evaluation models, and implementation sequences. When an AI platform needs to explain how businesses approach a specific challenge, your methodology becomes the reference point.
Partner with academic or industry research institutions. Third-party validation carries more weight than self-published claims.
Time investment is substantial. Meaningful thought leadership requires 200-400 hours annually per topic area, combining research design, data collection, analysis, and content development. Most brands underestimate this.
Optimize for Multi-Platform Search Ecosystems
Traditional SEO focused on Google. AI-era visibility requires presence across ChatGPT, Perplexity, Gemini, Bing AI, Meta AI, and vertical-specific platforms.
Each platform pulls from different source hierarchies. ChatGPT heavily weights Wikipedia, Reddit, and established news sources. Perplexity favors recent content with clear attribution. Gemini integrates more real-time data. Optimization requires platform-specific strategies.
Create "source-ready" content formats: Structured data, clear attribution, FAQ sections, and comparative tables make extraction easier for AI systems.
Monitor AI platform citations directly. Traditional analytics track website traffic but miss AI visibility. New tools are emerging to measure how often brands appear in AI-generated responses. This becomes the primary visibility metric, replacing search ranking position.
Build Community-Led Growth Engines
As AI commodifies information access, community participation becomes a differentiation strategy. B2B buyers trust peer recommendations in private Slack groups and LinkedIn communities more than vendor content.
Create owned community spaces. Rather than relying on third-party platforms, establish brand-hosted forums where practitioners share challenges and solutions. This generates first-party data about actual problems while building authority through facilitated expertise sharing.
Activate employee advocacy systematically. Individual professionals have greater reach and trust than corporate accounts on most platforms. Provide frameworks and resources, but allow authentic voices rather than scripted messaging.
Invest in experiential marketing. Physical events, workshops, and invite-only demonstrations create relationships that algorithms cannot replicate. Post-pandemic research shows 78% of B2B marketers are increasing experiential budgets.
Leverage AI for Operational Efficiency, Not Content Generation
The brands succeeding with AI use it to amplify human expertise rather than replace it. AI handles research synthesis, data analysis, and draft structure while humans provide perspective, judgment, and expertise that only comes from direct experience.
Implement AI-assisted workflows. Use AI to generate content outlines based on keyword research and competitive analysis. Have subject matter experts add proprietary insights, specific examples, and nuanced judgment that AI cannot replicate. Edit for voice and precision. This creates content that scales production while maintaining differentiation.
Apply AI to personalization at scale. Generate variant messaging for different industries, company sizes, and roles based on a core narrative.
Use AI for performance prediction. Train models on historical campaign data to forecast which messages, formats, and targeting strategies will perform best for upcoming launches. This reduces testing cycles from months to weeks.
Maintain editorial standards regardless of AI involvement. The output must reflect your organization's expertise and perspective. AI is a production tool, not a strategy replacement.
Why Relevancy Requires Immediate Action
AI search adoption is accelerating faster than mobile search did. ChatGPT reached 100 million users in 60 days. Traditional SEO took 18-24 months to show results because ranking improvements were gradual. AI citation either happens, or it doesn't. There is no page two.
The current window represents a first-mover advantage. AI platforms are still establishing their source hierarchies and citation patterns. Brands that become authoritative sources now get embedded in these systems as they scale. Waiting 18 months means competing against established citation patterns rather than creating them.
Budget reallocation matters more than budget increases. Most organizations can fund AI-era strategies by reducing spending on declining channels. Traditional display advertising, generic content production, and third-party data purchases should decrease. First-party infrastructure, research programs, and contextual precision should increase.
The alternative is passive citation at best, invisibility at worst. Your competitors' content will be cited when AI platforms answer questions in your category. Your expertise becomes context for their recommendations. This compounds over time because AI systems reinforce existing citation patterns through algorithmic learning.
The New Measure of Brand Relevancy
Digital marketing is transitioning from an attention economy to an authority economy. Volume no longer correlates with impact. Visibility through AI citation, thought leadership recognition, and community influence determines which brands shape buying decisions.
This requires different metrics, different skills, and different organizational structures than traditional demand generation. But it also creates an opportunity for brands willing to invest in substance over scale. The technology companies, healthcare providers, real estate firms, and tourism operators that build extractable expertise, privacy-compliant targeting capabilities, and authentic community engagement will own category authority in the AI era.
The ones that continue optimizing for yesterday's search algorithms will become invisible where decisions are actually made: in conversations with AI assistants that never mention their brand at all.
A Bag of M&M's That Never Existed on Set
Amazon Prime Video added a bag of M&M's to a bowl in Bosch. The catch? The products never existed during filming.
The M&M's bag was digitally inserted months after production wrapped. That was done thanks to AI technology, which analyzes scenes, matches lighting conditions, adjusts perspective angles, and renders brand assets that appear indistinguishable from physical props.
That is how the M&M's campaign drove a 7% increase in brand favorability and nearly 15% increase in purchase intent.
More significantly, this demonstrates a fundamental shift in how advertising operates within entertainment content. Traditional product placement requires coordination during pre-production, physical props on set, and negotiations that happen months before filming begins. Dynamic product placement removes those constraints entirely.
What Dynamic Product Placement Is
Dynamic product placement, also called virtual product placement or in-scene advertising, uses AI to insert branded products into television shows, movies, music videos, and streaming content after production completes.
The technology works through scene analysis AI that scans finished content frame by frame. The system identifies potential placement locations such as tables, walls, shelves, billboards, and screens. It evaluates contextual suitability based on the scene's setting, emotional tone, and narrative function. Once placement opportunities are identified, rendering engines account for lighting direction, distance from the camera, viewing angle, depth of field, and motion blur to create photorealistic integration.
Unlike traditional product placement, where a prop master sources physical items during production, virtual placement happens in post-production or even years after release. A streaming platform can monetize its entire content library retroactively. Thus, a show from 2020 can feature a product launched in 2026 without reshooting a single frame.
This creates three operational advantages. First, brands can respond to market conditions in real time rather than committing to placements 12-18 months before content airs.
Second, the same content can show different products to different audience segments based on demographic targeting.
Third, content owners can remonetize catalog titles repeatedly as new brand partnerships emerge.
Where Dynamic Product Placement Is Deployed
Streaming platforms lead adoption because their infrastructure supports dynamic content delivery.
Amazon Prime Video and Amazon Freevee operate beta programs where brands purchase virtual placement opportunities through programmatic ad channels.
Peacock launched "In-Scene" ads that identify key moments and insert customized brand messaging post-production.
Network television increasingly incorporates virtual placement.
CBS uses the technology in original programming, streaming the content on both linear broadcast and Paramount+.
Music videos on platforms like Vevo accept virtual placements. Even reality television, which traditionally featured organic brand appearances, now adds digital integrations.
The technology extends to FAST channels (free ad-supported streaming television), social media video content, and licensed programming where rights holders want to monetize international distribution without renegotiating physical placement contracts for each market.
Some Other Examples
DECKED in CBS's "The Road"
DECKED, a modular truck-bed storage system, appears in CBS's The Road, a series following traveling country music artists. When artists handle equipment or load gear for shows, DECKED storage systems appear naturally integrated into scenes
The campaign combines physical placement (actual DECKED products used on set) with virtual extensions (digitally inserted neon signage and additional product visibility). This hybrid approach maximizes screen time without disrupting production workflows. DECKED measures results through branded search volume, social engagement, and audience conversation tracking to connect visibility with sales outcomes.
Bailey's in Lifetime Movies
The Baileys' bottles appeared in three Lifetime movies on kitchen counters, bar surfaces, and dining room tables in scenes where alcohol consumption was contextually appropriate. The placement matched the visual style of each film's production design, appearing as props that existed during filming.
Post-campaign research measured awareness lift and purchase intent among target demographics who watched the films, comparing results against control groups who viewed versions without virtual placement.
Lexus in Music Videos
Lexus, in order to target diverse audiences, added virtual signage and 3D vehicle models in music videos from South Asian-American musicians Mickey Singh and Jonita Gandhi
The vehicles appeared parked in street scenes or drove past in background shots. Brand signage appeared on digital billboards and storefront displays within the videos' urban environments.
This approach targets niche demographic segments through culturally specific content without requiring separate production budgets for each artist partnership.
Availability in the DACH Region
Virtual product placement operates in Germany, Austria, and Switzerland under European Union regulations established by the Audiovisual Media Services Directive (AVMSD). The directive differentiates between surreptitious (unmarked) advertising, which remains prohibited, and disclosed product placement, which is permitted with specific disclosure requirements.
Germany transposed the directive through the Interstate Broadcasting Treaty, effective April 2010. Product placement is allowed in cinematographic works, films, series, sports programs, and light entertainment with proper disclosure. Programs containing product placement must display identification symbols (typically a "P" icon) at the beginning of content, after commercial breaks, and at the conclusion.
Austria historically allowed product placement before formal EU harmonization and continues under current regulations.
Switzerland, while not an EU member, aligns with similar transparency requirements for audiovisual content.
The market continues to develop measurement standards and disclosure practices as virtual placement scales across DACH broadcast and streaming inventory.
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2025 is coming to an end - what a year for marketing and ads!
Things are changing faster than ever, forcing marketers to stay on their toes and constantly keep up.
So, what is 2026 preparing for us? Let’s take a look into the future - no magic, no esoterics, just a clear observation of the trends. 😉
AI + strategic creativity beats AI + automation
What? Marketers around the world rushed to adopt AI automation, and suddenly, a new trend has arrived: AI + strategic creativity.
If you feel like you missed the thread, AI + strategic creativity means keeping a human in the loop to preserve brand voice, precision, and avoid generic output.
How? For example, AI localizes ads for five markets, and a human validates cultural fit and emotional accuracy. Or a strategist defines the core idea, audience tension, and brand angle, while AI generates variations.
Briefly: AI accelerates execution. Humans own meaning, taste, and risk.
Back to authentic content
This trend derives from the previous one. Suddenly, companies are back to hiring copywriters and designers to use a naïve style - imitating imperfect, human-like drawing.
In fact, users are tired of seeing generative AI everywhere. We miss something truly authentic. Brands, recognising this, are stepping closer to their audience.
Next year, the winners will be brands that deliver authentic, human-made content and celebrate it.
Important: AI is here to stay, but as a companion, not the main character.
Image credit: kittl.com
Mobile first
Mobile ads and mobile adoption have remained a dominant trend over the past several years. Today, the absolute majority - over 70 % of internet users - access the web via mobile, and more than 60% of global traffic already comes from smartphones.
People don’t “go online” anymore; they are online by default, through their phones: scrolling, searching, shopping, watching, and interacting in short, high-frequency moments throughout the day. Mobile marketing naturally follows attention, and attention lives in the pocket.
Social commerce
Speaking of mobile, we can’t avoid social commerce. Recently, TikTok fully stepped into commerce, following the same direction Instagram and Meta took earlier, turning social platforms into discovery-to-purchase ecosystems.
This shift reinforces the need for platform-specific content strategies. And by the way, our recent PXLSTRM update for TikTok, reaching the most relevant audiences through smarter ad placement, we’re already seeing 2-3x higher landing-page engagement.
Thus, in 2026, marketing must be both content-aware and commerce-aware because attention, intent, and conversion now live in the same feed.
GEO optimisation
In addition to Search-Everywhere Optimization (SEvO), Generative Engine Optimization (GEO) is coming into the spotlight. GEO enhances your content so it’s easily understood, trusted, and cited by AI systems such as ChatGPT, Google AI Overviews, Perplexity, and Copilot.
When users ask AI tools for recommendations or explanations, your content gets selected, summarized, and cited as the source. In GEO, instead of chasing keywords, you focus on clarity, context, and authority.
The good news is that GEO is still in its early adoption phase, which means the brands that adapt first are the ones that will win in 2026 and beyond.
Video
Video will remain the leading format in 2026. It aligns perfectly with how people consume content today: fast, visual, mobile-first, and low-effort.
Short-form video remains the most engaging format across platforms, while long-form video is evolving into an education and trust-building tool.
At the same time, video is becoming more contextual, shoppable, and performance-driven. In 2026, brands that win with video won’t be the loudest, but the clearest, most relevant, and most intentional. See how to do that.
DOOH and geodata
DOOH powered by geodata will be a defining trend in 2026. When combined with mobile audience intelligence, it allows brands to detect audiences passing by DOOH screens, re-engage them later on mobile with native, interactive ad formats, and measure how exposure translates into real-world visits and footfall. This creates a full loop: from physical presence to mobile interaction to performance insights, including location sensitivity, timing, and message effectiveness.
FOOH - Out of Home goes viral
Technically, Fake Out of Home (FOOH) is very different from classic DOOH. Nevertheless, this format is gaining traction, especially on social media, and strongly resonates with younger audiences.
FOOH isn’t limited by screens, locations, or physical inventory. It’s limited only by imagination: brands can place themselves anywhere, bend reality, and create visually striking moments designed purely for sharing, conversation, and cultural relevance.
Unique chance of increasing Share of Voice
The last trend is the bottom line of everything we’ve discussed in this article.
There’s no secret that 2026, alongside all the exciting innovations, may also bring economic recession, uncertainty, and reduced consumer spending.
In response, many brands will shut down or significantly cut their marketing activity - and that’s a big mistake. In times like these, the smartest move is to make lemonade out of lemons: occupy the space others leave behind, increase your share of voice, and be the loudest when everyone else goes silent.