AI agents already run billions in ad spend, and most agentic projects still fail

Two of the most widely deployed agentic marketing systems in the world are not startups. Meta Advantage+ and Google Performance Max manage billions of dollars in ad spend through autonomous AI decision-making. Meta's Advantage+ line alone is generating roughly $60 billion in annualized revenue. AI adoption across advertising has climbed in step, with social and video channels leading at 85–86%.

As Viant's CEO put it, autonomous media buying is no longer theoretical.

The deployment record is harder. Gartner projects that more than 40% of agentic AI projects will be cancelled by the end of 2027, citing escalating costs, unclear business value, and weak risk controls. A 2025 RAND meta-analysis found that around 80% of enterprise AI projects fail to deliver their promised business value — roughly twice the failure rate of conventional software.

For a marketing team, the decision that matters is which approach survives contact with real data, a compliance review, and a real budget. A clean demo says little about that.

What a marketing AI agent is

A marketing AI agent is a software system that takes a goal, breaks it into steps, and carries those steps out across connected tools with limited human supervision. It reads the current state of a campaign or audience, decides the next action, executes that action through an API or platform, observes the result, and adjusts. The defining traits are autonomy, a goal it optimizes toward, and the ability to act rather than only suggest.

This is the practical meaning of agentic AI in advertising: software that runs a loop of perceive, decide, act, and learn, instead of waiting for a person at each step.

How an agent differs from automation and a chatbot

Rule-based automation, assistants, and agents are often grouped together. They behave differently in production.

Capability	Rule-based automation	Chatbot / assistant	AI agent
Triggers	Fixed if-then rules	Responds to a prompt	Sets its own sub-steps toward a goal
Decision-making	None	Suggests; you decide	Decides the next action itself
Action	Executes a preset task	You act on the output	Acts across tools via APIs
Adapts to new data	No	Only within a reply	Yes, adjusts as results change

What marketing AI agents do across the funnel

The functions below are operational today across major ad platforms, marketing clouds, and specialist tools.

• Media buying and bidding. Agents adjust bids, expand query matching, and reallocate budget continuously. Google AI Max, an AI layer applied to Search campaigns and announced at Google Marketing Live in May 2025, typically lifts conversions by about 14% at a similar CPA or ROAS, according to Google's own data. Meta Advantage+ and Performance Max operate on the same principle.
• Creative production and dynamic creative optimization. Agents generate and test ad copy, images, and video, then shift spend toward the variant that performs.
• Audience building and targeting. Agents define and refine segments from first-party and behavioral signals, increasingly without manual demographic inputs.
• Autonomous ad optimization. Agents monitor accounts continuously, pause weak placements, and scale winners. This is the layer behind AI-powered campaign management and self-improving platforms such as Adello's own AdCTRL optimization engine.
• Predictive targeting and pacing. Agents forecast conversion probability to guide bids and budget, the core idea behind predictive ads.
• Content and generative engine optimization. Agents produce structured content so a brand is cited inside AI answers from systems like ChatGPT, Gemini, and Perplexity — the practice known as generative engine optimization, or GEO.
• Cross-platform orchestration and reporting. Agents pull results across Meta, Google, and TikTok, normalize attribution, and recommend or execute budget shifts.

Why do marketing AI agents break between the demo and production

Most marketing AI agents look excellent in a demo. The demo runs on a clean dataset, one channel, and no compliance review. Production is a different environment. The agent meets fragmented ad accounts, a CRM that was never built to be queried in real time, brand rules that live in someone's head, and a data protection officer with questions. The space between those two settings is where projects stall.

Four causes are concrete and measurable.

• Integration friction. Gartner research reports that about 70% of developers face integration problems connecting agents to existing systems, and roughly 42% of enterprises need eight or more data sources to make an agent useful. Marketing data is among the most fragmented: ad platforms, a CDP, a CRM, analytics, and creative libraries rarely share a schema.
• The black-box and lock-in tradeoff. Platform-native agents optimize toward the platform's goals, which are not always the advertiser's. An independent Wicked Reports analysis of more than 55,000 Meta campaigns found new-customer acquisition cost through Advantage+ more than doubled between May 2024 and May 2025, from $257 to $528. Autonomy without transparency can raise CAC quietly.
• Data ownership and compliance. Switzerland's revised data protection act (revDSG), in force since September 2023, requires controllers to show where personal data is processed and stored, who can access it, and on what legal basis. Agents that route data through US-controlled inference add contractual and assessment overhead.
• Total cost of ownership. Per-action or per-conversation pricing is the visible portion. Implementation, knowledge-base maintenance, model updates, and human supervision often exceed the licence line in year one.

Four ways to put a marketing AI agent into production

When a team decides to deploy an agent, the market offers four categories of vendors. The clearest examples below come from customer service, where agentic AI is most mature, but the build-versus-buy choice and the compliance, integration, and cost dynamics transfer directly to marketing agents. A fuller side-by-side sits in this 2026 buyer's comparison.

1. Multi-market generalist platforms

A fast-scaling vendor that covers many markets and channels under one contract. The clearest example is Wonderful AI, a Tel Aviv vendor founded in early 2025 that had raised about $284 million by March 2026 at a $2 billion valuation and expanded across several European and EMEA markets. It covers voice, chat, and email with a stated 80% resolve rate, and positions on per-market linguistic fluency.

Where it fits: organizations operating across many markets that want a single vendor and are comfortable with a hyper-growth partner still building its governance footprint. Where it does not: compliance teams that need data residency and processor mapping before signing. Pricing is enterprise-negotiated, and the track record in regulated verticals is still short.

2. Regional specialist platforms

A scoped platform with local legal standing and fast deployment. Typewise, a Zurich scale-up (Y Combinator S22) co-developed with the ETH Zurich AI Center, is used by around 60 enterprises including Unilever, DPD, and Brack.ch for written customer service. In February 2026 it launched an AI Supervisor Engine for multi-agent orchestration. Stated benchmarks include a 50% or higher reduction in agent effort, deployment in one to two days, ISO-certified and GDPR-compliant infrastructure, and outcome-based pricing.

Where it fits: written-channel use cases that want a Swiss legal counterpart and quick deployment. Where it does not: voice-first work, or scope that extends well beyond customer service.

3. Platform-native and CRM-embedded agents

An agent layer inside a stack the organization already runs. Salesforce Agentforce is available to Salesforce Enterprise Edition customers and above. As of April 2026, its pricing page lists a free Foundations tier, consumption at $500 per 100,000 Flex Credits (about $0.10 per action), $2 per customer-facing conversation under a fixed model, or per-user add-ons at $125 per user per month; Agentforce 1 editions start at $550 per user per month, on top of Enterprise ($165 per user per month) or Unlimited ($330). Third-party estimates put the first-year total for a ten-person team near $140,000 once licences, implementation, and training are included.

The same pattern exists in pure marketing. Google AI Max and Meta Advantage+ are platform-native agents that live inside one ad ecosystem. The benefit is the speed of activation. The tradeoff is optimization toward the platform's goals and the difficulty of forecasting consumption costs.

Where it fits: organizations already standardized on the platform with clean data inside it. Where it does not: fragmented data outside the platform, or buyers who want control over where optimization decisions point.

4. Custom-built agents (Lab51 by Adello)

A custom agent is built around a defined scope, deployed on infrastructure the buyer controls, and integrated directly into the data sources that matter. The 2026 architecture is well understood: a curated knowledge base, a retrieval layer (a vector database with hybrid keyword and semantic search), a defined response matrix, channel integration through Model Context Protocol or direct APIs, and a benchmark dataset signed off before launch.

A representative mid-complexity scope is indicative rather than fixed: about 8 weeks to build the knowledge and retrieval engine, 8 to 12 weeks to integrate channels, implementation in the range of USD 70,000–90,000, plus model monitoring in the low hundreds per month. Voice and multimedia agents sit at the higher end. These figures scale with data complexity and channel count.

For a marketing team, the custom model addresses the production problems directly. Data stays in a defined environment, which matters under revDSG. The agent connects to the ad, CDP, and analytics stack the team actually runs on rather than a generic layer placed on top. And the cost is a one-time build plus low ongoing fees, instead of per-seat or per-conversation licensing that grows with volume.

Lab51, by Adello, builds in this category for Swiss and DACH enterprises, with revDSG-compliant deployment patterns, a defined 8-week knowledge-base build, and phased channel integration. For marketing, that means an agent wired into owned campaign and audience data, integrated with the systems already in use.

Where it fits: regulated organizations, teams whose differentiation depends on specific workflows, and buyers who prefer a build-and-own cost model. Where it does not: very generic needs with no compliance constraints, where a fast SaaS deployment wins on time-to-value.

Want to discover how AI agents can drive efficiency and growth for your business? Fill out the form today, and one of our sales specialists will contact you shortly.

The four models side by side

Approach	Best for	Data residency control	Integration depth	Pricing model	Time to value
Multi-market generalist	Many markets, one vendor	Vendor-managed; assessment needed	Broad, generalist	Enterprise-negotiated	Fast
Regional specialist	Written-channel work, local counterpart	Swiss / ISO / GDPR	Scoped to its domain	Outcome-based	Very fast (days)
Platform-native / CRM	Teams already on the platform	Platform-controlled	Deep in-platform, limited outside	Consumption or per-seat	Fast if data is in-platform
Custom build (Lab51)	Regulated, workflow-led, build-and-own	Buyer-controlled	Deep, to chosen sources	One-time build + low monthly	Weeks (≈8–20)

Why this is a 2026 decision, not a 2027 one

Three forces are moving at once.

The failure rate is documented and high. Decisions made on hype rather than fit surface as cancelled projects 12 to 24 months later, after the implementation cost is already sunk.

Procurement takes time. In Swiss-regulated industries, compliance review, a data protection impact assessment, and an IT security review for a new external processor typically run two to four months. Starting in Q2 2026 means production by late 2026 at the earliest.

The operational gap compounds. Teams that deploy effective agents in 2026 build data assets, prompt libraries, and process knowledge that grow more valuable each quarter. Teams that wait face a baseline that keeps moving.

The practical move for buyers is to sequence the decision. Define the scope, the channels, the data sources, the compliance constraints, and the success metric before the first vendor demo. Then use that scope as the testing ground for every category.

Marketing AI agents have moved from pilot to production faster than most teams have built the governance to run them. The capability is real and already running paid media at scale. The differentiator in 2026 is fit: matching the deployment model to your data, your compliance posture, and your budget. Define what success looks like first, then choose the approach that can reach it.

Created with the help of AI.

80% of Web Traffic Is on Mobile, 

Eight out of ten travelers now book their trips on a phone. Thirty-nine percent prefer apps over websites because apps are faster. And in 2023, global digital ad spend in travel jumped 132% to $344 million, with continued growth into 2024 and beyond.

The phone serves as a research, comparison, payment, check-in tool, as well as a boarding pass, room key, restaurant booking, and post-trip review. For destinations, hotels, airlines, and tour operators, this means the marketing decision is settled before the customer ever touches your desk.

Hospitality and Tourism Marketing in 2026

Hospitality and tourism marketing in 2026 is moving a person from intent ("I want to take a trip") to a booking, using primarily mobile channels, in a market where third-party cookies are gone, AI assistants increasingly shape the discovery layer, and Online Travel Agencies (OTAs) capture most of the first-touch demand.

The job has three components:

• Demand creation — putting a destination, hotel, or route into the consideration set before search.
• Demand capture — converting in-market travelers via direct channels rather than ceding margin to OTAs.
• Loyalty and re-activation — returning past guests at the right moment, on the right device, with the right offer.

International tourist arrivals recovered to 88% of pre-pandemic levels by the end of 2023, and overnight stays in Q1 2024 already exceeded Q1 2019. Demand returned. The problem is that the marketing environment has not returned to what it was.

Three signals matter most.

Cookies are gone, and signal loss is permanent. iOS App Tracking Transparency removed the IDFA at scale. Chrome has phased out third-party cookies. GDPR enforcement in the DACH region and across the EU is now stricter. Audience pools built on cookie matching have shrunk. Cookieless advertising is the default, not a contingency plan.

AI search reshapes the discovery layer. Travelers ask ChatGPT, Gemini, and Perplexity for itineraries, hotel comparisons, and visa rules. Booking funnels that depended on Google's classic ten blue links now compete for a single mention inside an AI summary. LLMs cite two to seven sources per response. Destinations and hotels without structured, machine-readable content are invisible in that window.

Ad blindness is measurable. Mobile users scroll past static creative within fractions of a second. Click-through rates on banner formats sit below 0.1% in most travel verticals. Engagement-led creative, by contrast, holds attention long enough to drive intent — and the gap is no longer marginal.

The result is a squeeze. Demand is high. Inventory costs are stable. But customer acquisition cost (CAC) keeps rising because OTAs dominate generic search, the signal is harder to recover, and the discovery layer is fragmenting across AI assistants, social platforms, and traditional search.

What Actually Works: Seven Approaches for 2026

Geolocation Targeting for Destination Demand

Mobile advertising is the only channel that lets you reach a defined audience inside a defined polygon at a defined moment. Hyper-local targeting matters in tourism because demand is geographically clustered.

Geolocation mobile marketing also reduces waste. If your ski resort serves the DACH region, there is no reason to spend impressions in Iberia or the UK. Geo-targeting routes budget toward addressable demand.

Practical signals to use:

• IP and GPS location at impression time.
• Country, region, and city.
• Inventory is restricted to in-region publishers.
• Time-of-day rules tied to local booking patterns.

Mobile Video Advertising and Interactive Ad Formats

Interactive ads and mobile video advertising hold attention because they show, rather than describe, the experience. A 360° video of an alpine landscape conveys what a list of amenities cannot. A swipe-cube creative that turns under the user's finger creates engagement at a click-through rate well above category benchmarks.

Adello offers a #Immersive3D format — 360° video where viewers tilt the phone to change perspective and rotation is measured pre-click, enabling gamification such as hidden prizes at specific points. Such a format was used for the Austrian ski region Skicircus Saalbach Hinterglemm Leogang Fieberbrunn.

The principle is simple: in a feed that scrolls at speed, only the creative that interrupts the scroll earns attention. Documented results across DACH tourism campaigns are covered further down.

Cookieless Contextual and Behavioral Targeting

With cookies retired, audience targeting depends on first-party data, contextual signals, and behavioral affinity inside content. Contextual advertising places ads next to travel-relevant articles, videos, and apps. Behavioral affinity goes further — it analyzes what people watch, install, and engage with to infer trip intent without identifying the individual.

The same logic extends to retargeting. Travel booking funnels leak: users browse a hotel, build a basket, and abandon. Cookieless retargeting recovers those users without third-party cookies by combining first-party signals from the brand, server-side conversion data, and contextual matching at the impression level. Travelers who reach the checkout step have already qualified themselves; bringing them back within 24 to 72 hours is cheaper than acquiring a new visitor through generic search.

Adello operates a mobile DSP and managed service for cookieless mobile advertising, covering both prospecting and retargeting. Adello AdCTRL™ relied from the very beginning on user consent and observed human behavior in order to maintain privacy. It complies with all applicable data protection laws, including the European Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Brazilian General Data Protection Law (LGPD).

Omnichannel Marketing Services Across Mobile, CTV, and DOOH

A single channel rarely closes a booking. Travelers research on mobile, watch CTV in the evening, see DOOH at airports and train stations, and book on mobile again. Omnichannel marketing services connect those touchpoints into one campaign with one audience definition and one measurement framework.

CTV ads have grown sharply in travel because they reach high-value households at the moment they are making leisure decisions. Programmatic digital out-of-home (DOOH) extends presence to airports, transit hubs, and city centers — places where intent is already physically present.

The benefit of omnichannel is not coverage; it is sequence. The same person sees the brand on CTV at home, on DOOH at the airport, and on mobile during the layover.

Contextual Video Targeting 

Travelers heavily consume travel content on YouTube, Pinterest and TikTok — destination vlogs, hotel walkthroughs, route reviews, gear breakdowns. The challenge for advertisers is reaching the right slice of that audience without third-party cookies and without falling back to the broad interest segments the platforms expose by default.

PXLSTRM, Adello's patented contextual targeting product, addresses this for video. It analyzes video content, dialogue, and objects to cluster inventory by behavioral affinity rather than declared interest. Targeting happens at the level of what audiences actually engage with on screen — destinations, activities, scenery, sport — instead of what they declared in a profile.

AI-Driven Dynamic Creative Optimization

Travel inventory is variable. Different rooms, routes, seasons, and offers all need their own message. AI-powered dynamic creative optimization assembles the right ad — image, headline, price, offer — for the right user at the right time, drawing on a content library rather than producing each variant manually.

For multi-property hotel groups, large airlines, and destination management organizations, this is what keeps creative refresh cycles tight enough to stay ahead of ad fatigue.

Why Tourism Marketers Need to Act in 2026

The 2026 window is small. Travel ad spend continues to grow. Inventory is available. The technology to target without cookies, measure attention, and personalize creative at scale is in the market today. The marketers who set up the infrastructure this year will spend the next two years compounding learnings; the marketers who wait will be buying audience access at a premium.

Hospitality and tourism marketing in 2026 runs on mobile, depends on cookieless targeting, and is measured by attention and incremental bookings rather than last-click conversions. The destinations and hotels that perform are the ones that combine geolocation precision, interactive creative, behavioral audience signals, and omnichannel sequencing inside a single managed campaign.

The high season is coming. Now is the time for hospitality marketers to choose the right partner. Learn how Adello can help you maximize your marketing performance and reach more guests. Contact us today:

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.

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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.

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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.

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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

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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.

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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.

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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.

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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.

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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.

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The Key Players Building the Agentic Commerce Ecosystem

Platform	Protocol / Product	Status (Q1 2026)
Google	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.

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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.

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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.

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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.

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.

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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.

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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.

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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.

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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.

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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)

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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.

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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.

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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.

✈️⛱️ Would you like to learn how to advertise your travel and hospitality business on Pinterest?
Fill out the form, and our sales team will reach out to you shortly:

Zurich, 23.03.3026 - PXLSTRM, Adello's AI-based contextual advertising spinoff, now supports Pinterest campaigns in Germany, Austria, and Switzerland. The expansion adds Pinterest to PXLSTRM's existing contextual solution for YouTube and TikTok.

PXLSTRM applies AI-driven contextual targeting to video and image platforms without relying on third-party cookies. 

For advertisers already using PXLSTRM on YouTube and TikTok, Pinterest adds an additional audience that is largely unreachable on other channels.

The incremental reach versus TikTok alone is approximately +50%. Adding Pinterest to an existing PXLSTRM campaign extends coverage to a segment that current platform combinations miss.

Initial Pinterest campaigns through PXLSTRM show a 10% CPA improvement and a 4:1 ROAS in case studies. Further campaigns will shed light on the scale-out of these initial numbers.

PXLSTRM processes behavioral signals across multiple dimensions and correlates these with proprietary contextual data. The result is audiences instead of demographics alone. Leveraging proprietary contextual data and domain-specific know-how is what makes the solution unique.

Pinterest has more ~24.5 million users in DACH and reaches 29–36% of the online population. 55% of users report purchase intent — compared to 12% on Instagram and Facebook. 98% say they have discovered new products on the platform. 44% of German Pinterest users fall into high-income households. This proves that while Pinterest is smaller in absolute numbers, it can add a highly engaged audience for certain target groups.

About PXLSTRM

PXLSTRM is a pioneering AI-driven video advertising technology company, a spin-off of Adello. By analyzing video content—including dialogues, objects, and visuals—PXLSTRM ensures that ads reach the right audience with unmatched precision. Advertisers leveraging PXLSTRM’s technology experience engagement and conversion rate improvements of over 100%. Brands looking to optimize their Return on Ad Spend (ROAS) while ensuring contextual relevance and brand safety are encouraged to connect with the PXLSTRM team.

Contact: info@adello.com

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.

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There is no secret that the current economic situation is, let’s say, far from favorable. Companies are firing employees, consumers are losing money, and with that, their buying power is dropping; meanwhile, the situation in the world remains unpredictable. A vicious circle. Most likely, you have already felt how this crisis is influencing both business and daily life. 

Here are the main risks for businesses that may occur very soon:

Further decline in consumer demand

When consumers realize their income is not the same as it used to be, they stop spending on anything that isn’t critical. That means fewer sales for brands, slower cash flow, weaker quarterly numbers, and a tougher fight for every transaction. That is how demand doesn’t collapse overnight; it always fades gradually.

Wave of business closures and consolidations

The companies with no buffer - thin margins, high debt, or unstable demand - will be the first to disappear. Some will shut down quietly; others will be swallowed by bigger players. 

Those brands that will survive will operate in a colder, more defensive environment.

Price instability 

The worst scenario is when growth slows but prices don’t follow,  especially for basics like energy, rent, food, and logistics. That means you can’t “save” your way out: even if you cut costs, your purchasing power still erodes. 

Government policy backlash

At some point, governments will try to “fix” the situation, and, unfortunately, not always wisely. They may raise taxes, restrict credit, cut subsidies, freeze prices, or tighten regulations. 

Historically, late policy interventions often make business conditions worse, not better. And when public budgets get squeezed, companies cannot count on the same safety net they had during the pandemic.

How can Businesses Survive a Recession?

Hard times force us to gather what we have - skills, people, money, attention - and use them with intent instead of on autopilot. The point isn’t to freeze or react chaotically, but to move with strategy. The question is not if we should act, but how to channel our effort so it actually works. Here is a couple of advice for the hard economic times:

Stop trying to win everyone. Double down on the segments that still buy

You will see many brands in panic, trying to target as many people as they can, hoping that it will increase their revenue. A shrinking market, however, punishes broad targeting. Keep the customers who still have money and still have a need. Survival is about depth, not width.

Do not cut the marketing costs

Companies die not because they cut, but because they cut the wrong things: marketing, R&D, customer support. The practice and various studies show, cutting marketing during the crisis can only worsen the situation. Thus, when your competitors are getting silent, it’s your high time to raise your voice through marketing.

Instead, remove vanity spend; protect what feeds demand.

Shift messaging from “nice to have” to “must have”

In a recession, buying decisions shift from desire to defense. So your product cannot be framed as an upgrade or a nice perk in the current situation. Instead, you need to reframe it as a risk-reducer, cost-saver, or performance enabler. 

As an example, during the pandemic of 2020, Airbnb shifted its focus from delivering “travel experiences” to “safe local escapes”. Thus, before the pandemic, they forced global travel, freedom, adventure, and switched during the crisis to “stay nearby, isolate safely, live & work elsewhere short-term”

Make loyalty cheaper than acquisition

Acquiring a new customer in a recession is a premium-priced sport: higher CPMs, longer decision cycles, more objections, more stakeholders, and less willingness to try anything new. Retention, on the other hand, works with people who already trust you and already pay you. The unit economics are completely different.

That’s why during downturns, the smartest brands lock in the base:

• Re-engagement  - don’t wait; proactively pull “silent” users back before they disappear.
  
• Upsell bundles - make it cheaper to buy more from you than to go shop around.
  
• Membership perks/loyalty tiers - give people a reason to stay even when everyone is cutting expenses.
  

Be open to changes

The principle is the same as in nature: only the most adaptive make it through. The crisis may drive you to consider different opportunities that will require risk and changes on your part. 

During a recession, flexibility becomes a competitive advantage. You work with the resources you already have, and you stay alert to new openings the market creates in chaos. Those who move first when opportunities appear usually own them.

Extra Advice from Adello

Adello was founded in 2008, right in the middle of a global crisis. Since then, we have gone through several downturns, including the 2020 pandemic. We have experience not only surviving, but operating through volatility.

Everything mentioned above reflects what actually helped us get through hard cycles. But there is one more principle worth stating explicitly: consolidation is crucial. We know the kinds of pressures companies are facing now - we have been there.

That is why we invite you to a free consultation on how to navigate marketing during this period. If you want to discuss realistic strategies for the current climate, fill out the form below, and let’s talk.

The restaurant business is probably one of the most interesting and versatile sectors. Like all businesses, it requires a well-designed marketing strategy to stay afloat, increase public awareness, and attract and retain customers. In this guide, we give recommendations on how to do marketing for the restaurant business, taking into account the emerging trends and old, solid strategies that have proven to be effective over time.

Why digital marketing is a must for restaurants

As a rule, marketing for restaurants requires a holistic approach, which includes both digital and non-digital methods. In the industry, many rely heavily on the print media, using it for their marketing brochures, ads in magazines, etc. We are not trying to say that these methods are completely irrelevant or not effective; rather, they do not encompass the same amount of your audience that can be reached.

Digital marketing must prevail in restaurant marketing because it enables real-time engagement, precise targeting, and measurable ROI in an industry where consumer behavior is increasingly influenced by online discovery and social proof. As customers now turn to platforms like Google, Instagram, and TikTok to find and evaluate dining options, a strong digital presence directly impacts foot traffic and sales. Moreover, digital channels allow restaurants to build first-party data, personalize offers, and foster loyalty at scale, all while adapting quickly to trends or feedback. Thus, in a competitive, fast-paced market, traditional methods alone can't match the reach, agility, or efficiency that digital marketing delivers.

So, what digital marketing methods are suitable for the restaurant business in 2025 and beyond?

Make Your Visual Content Stand Out

This is a sub-advice that is relevant to the other tips listed below. Restaurant marketing must be highly visual. Thus, creating an appealing visual of the food and interior is the first thing that must be considered.

To create irresistible visual content, keep these tips in mind:

• Hire a person who can do professional photography with a good portfolio. It will save you time and guarantee a result. 
• Restrain from the AI-generated images. As a rule, customers can identify these images are fake. Also, they can be very different from what your chef is cooking, so do not create false expectations.
• Use natural lighting whenever possible to make your dishes look fresh and appetizing.
• Experiment with different angles to highlight each dish’s best features.
• Focus on close-ups to emphasize textures and vibrant colors.
• Create short, engaging videos (like quick cooking tips or plating techniques) for social media.
• Develop a consistent visual style that reflects your brand’s personality

Search Optimization

Recently, users’ Internet searches have drastically changed. Nowadays, when it comes to searching for a place to dine, users rely on Search Everything Optimisation (SEvO). That means, people will not only search restaurants near them in Google (or other search engines), they will also search them through maps or social media.

Also, the appearance of AI models such as ChatGPT has drastically changed the way Search Engine Optimization works. People will more often type a prompt in AI chats like “What are the best restaurants in my town?” instead of just googling it.

Make sure your digital presence is optimized for various channels. Keep your Google Business Profile, Instagram, and TikTok pages up-to-date with accurate info, high-quality photos, and fresh content. Use keywords naturally in your bio, captions, and posts that reflect what people might ask AI tools.

Mobile marketing

Mobile marketing remains one of the top strategies for the restaurant business. Mobile devices are the ultimate device through which your customers make a decision where to dine, starting from searching places in map apps to visiting your social media profile. 

That is why considering mobile marketing is a must. Mobile programmatic advertising deserves your special attention. By using automated, data-driven platforms, restaurants can serve hyper-targeted ads to users based on location, time of day, behavior, and even weather conditions.

For example, a pizza restaurant can target commuters near their location with a “hot slice on your way home” offer right at rush hour. 

Programmatic ads also allow for dynamic creative, which makes your messaging more relevant and effective. 

Social Media Marketing for Restaurants

As we mentioned above, social media is another place where your customers will search for a restaurant. Very often, before visiting, users check a restaurant’s social media profile, especially Instagram, since it is highly visual. That is how social media presence can become a dealbreaker before deciding where to dine. 

Success on social media comes down to creativity and authenticity, staying true to your brand while finding innovative, engaging ways to interact with followers. Top strategies for social media success include:

• Sharing high-quality photos and videos of your dishes
• Posting behind-the-scenes glimpses of your kitchen and team
• Responding promptly to comments and messages
• Leveraging features like Instagram Stories and Reels, TikTok, and/or Shorts trends
• Collaborating with local food bloggers and influencers to tap into new audiences

Video marketing

Video content is quickly becoming one of the most powerful tools in restaurant marketing. Whether you're creating short clips for TikTok or longer-form content for YouTube, videos help you connect emotionally with potential customers. 

If you consider YouTube local advertising, ad placement is important. Your ad will perform better if it is presented along the right video content, and for the right audience. Solution such a PXLSTRM analyzes video content, including objects, brands, and dialogue, to intelligently place your restaurant in the most relevant YouTube ad spots. This ensures that your video marketing is not just creative, but strategically impactful.

Influencer marketing

Influencer marketing is still considered one of the most effective marketing methods, which is very suitable for the restaurant industry. It will help you expand your reach by introducing your restaurant to new audiences who already trust and engage with these content creators.

If you think hiring a very famous influencer would be a burden for your budget, consider a micro-influencer. While having a small audience, they can make an impact on the hyper-local groups.

User-generated content

User-generated content (UGC) possesses lots of benefits. Firstly, your customers do your marketing by themselves, posting stories and posts mentioning your restaurant location. Also, you create a sense of community and make your followers feel like part of the experience. Behind-the-scenes glimpses and customer spotlights can humanize your brand and spark meaningful interactions. Moreover, UGC increases trust by seeing the real people reacting to your business.

Email Marketing

Retaining your loyal customers and informing them about special deals and upcoming events is so much easier to do digitally rather than sending them brochures to their mailboxes. A newsletter is an excellent tool that helps to automate and facilitate such processes.

Also, sending personalized newsletters with customized messages for special occasions like birthdays or anniversaries adds a thoughtful, personal touch that strengthens loyalty. Additionally, targeted email campaigns are a great tool for re-engaging customers.

🍽️ Do you want to know how digital marketing can help your business in the F&B and hospitality industry?

Adello Team can help you! Discover what’s possible – just fill out the form and let’s get started!

There are some digital marketing teams. Remember, effective marketing doesn’t happen overnight. It takes consistency, creativity, and effort. But the long-term payoff is well worth it when it comes to building a thriving, successful business.