CTV Advertising Trends 2026: What Marketers Need to Know Now
January 9, 2026
12
minutes read
In 2026, the most important TV story isn’t about channels or cords at all; it’s about the streaming screens quietly swallowing your audience and budget. This article unpacks the CTV advertising trends and connected TV trends reshaping how brands plan, target, and measure so you can see where to double down and what to test next.
CTV started life as a bolt-on to digital video plans: a way to pick up streaming audiences while most budgets stayed in linear. That balance has flipped. As streaming’s share of viewing hits new records and platforms introduce ad-supported tiers, CTV trends are now shaping how marketers think about TV as a whole.
Digital video is on track to capturenearly 70% of all U.S. TV/video ad spend in 2025, with CTV, social video, and online video all posting double-digit growth, according to IAB’s 2025 Outlook report. In the same study, linear TV is one of the few channels expected to decline.
That shift brings both opportunity and complexity:
Viewers are scattered across dozens of apps and devices.
Measurement currencies are still in flux.
New buying tools, especially self-serve and AI-powered workflows, are lowering barriers to entry.
In the sections that follow, we’ll unpack the CTV advertising trends reshaping 2026, then translate them into clear implications and next steps.
⚡ CTV is no longer a special line item on the plan, it is the context in which TV planning happens. Teams that still bolt CTV on at the end will struggle to keep up with audiences who have already moved.
Before we dive into individual trends, it helps to zoom out. The biggest CTV advertising trends for 2026 sit at the crossroads of three forces: shifting connected TV viewership, the rise of data-driven buying, and pressure to prove performance. The sections below break down how those forces show up in practice—from planning and retail media to creative, clean rooms, and measurement—so you can decide where to focus your next round of testing and investment.
The rise of converged TV planning
Marketers are finally treating “TV” as one converged channel that includes linear, CTV, and other digital video, instead of three separate silos.
In IAB’s 2025 outlook, buyers indicated that CTV would see double-digit spend growth, while linear TV would decline, reflecting a clear rebalancing within the broader TV bucket.At the same time, digital video overall (CTV + social + online) is projected to command nearly 70% of total TV/video spend in 2025, as mentioned previously.
What this means in practice:
Unified reach planning: Teams are moving away from separate “TV” and “digital” teams and tools. They are planning total video reach and frequency across linear and CTV together, using audience-based planning rather than pure GRPs.
Cross-screen frequency control: Advertisers want to avoid hitting the same household with the same message on linear, then again on three different CTV apps. Converged planning tools and identity solutions help cap frequency across screens.
Holistic reporting: Instead of isolated reports for linear and streaming, marketers are asking, “What did TV as a whole deliver?” That requires deduplicated reach across platforms, not just channel-level numbers.
💡 For a deeper grounding in how this fits with broader TV strategy, see AI Digital’s guide to TV advertising.
⚡ In 2026, the real competitive advantage is not choosing TV vs CTV—it’s controlling reach and frequency across both.
Retail media is no longer confined to search results and on-site banners. In 2026, retailers are extending their first-party commerce data into CTV environments, turning streaming into a measurable mid- and lower-funnel channel.
eMarketer’s latest forecast expectsU.S. retail media ad spend to reach $58.79 billion in 2025 and $69.33 billion in 2026, with much of the incremental spend flowing to Amazon Ads and Walmart Connect.Separate eMarketer analysis shows that retail media CTV ad spending will grow 45.5% in 2025, with one in five CTV ad dollarsprojected to go to retail media by 2027.
That combination—CTV’s storytelling power plus retail media’s closed-loop measurement—is changing how marketers think about CTV advertising growth:
Retailers can build CTV segments around past purchases, category interest, or loyalty behaviors.
Brands can run CTV ads against those segments and measure in-store or e-commerce sales.
Performance teams can treat CTV more like paid search or social, optimising toward ROAS and incremental sales rather than only reach.
For example, a packaged-goods brand can target “recent category buyers” from a major retailer’s data and then attribute CTV exposure to basket uplift, rather than relying on broad demographic proxies.
Projected retail media ad spend change ‘24 vs ‘25 (Source)
⚡ When retailer data powers CTV, your TV ads are talking to people based on what they actually buy. That makes CTV just as capable of closing a sale as it is at opening the conversation.
💡 For more background on how retail media networks operate, see AI Digital’s guide to retail media networks.
AI reshapes CTV creative
AI has moved from experimentation to everyday tool in marketing workflows, and CTV creative is one of the major beneficiaries.
According to an Insider Intelligence analysis of January 2025 data from Canva and Morning Consult, 49% of marketers worldwide use AI daily to generate images and videos. Marketing Week reports that 44.7% of marketers are using AI to produce multiple variants of campaign assets, showing that creative diversification is now a standard use case rather than a niche test.SurveyMonkey’s AI in marketing research further suggests that 88% of marketers use AI in their day-to-day roles, even if only for parts of the workflow.
Faster production of video assets Generative tools now help teams:
Draft scripts and storyboards.
Create or edit video sequences.
Localize or personalize assets for different markets or audience cohorts.
That makes it affordable to test more CTV ads per campaign—different offers, CTAs, or hooks—without tripling production budgets.
Dynamic creative optimization (DCO) for CTV: DCO engines can automatically swap elements (offers, imagery, product tiles, even voiceover lines) based on:
Audience segment (e.g. loyalty vs prospecting).
Context (time of day, device, content genre).
Real-time performance data.
In other words, the ad the viewer sees on their TV can adapt to who they are and how previous impressions have performed, not just a one-size-fits-all spot.
Interactive and personalized experiences: As platforms expand interactive formats (QR codes, overlays, shoppable units), AI helps map the right variant to the right household: which product to show, which promotion to feature, which landing page to route to.
⚡ AI won’t write your brand strategy, but it can give your CTV creative the scale your media plan already has.
💡 To connect this trend back to your broader marketing stack, you can read AI Digital’s piece on AI in digital marketing.
Clean rooms become essential
As privacy rules tighten and third-party identifiers fade, data clean rooms have moved from “experimental” to critical infrastructure for CTV trends.
Forrester’s Q4 2024 CMO Pulse survey found that about 90% of B2C marketers now use data clean rooms for marketing use cases, indicating widespread adoption well beyond early adopters. Market researchers estimate that the global data clean room market reached $1.42 billion in 2024 and is expected to grow at a 22.1% CAGR through 2033, driven partly by advertising and media use cases.
For CTV, clean rooms solve three pressing problems:
Privacy-safe activation: Brands can match their first-party data with publisher or retailer data without directly sharing raw customer information. That allows:
“Bring your own audience” targeting in CTV.
High-value segment creation (e.g. lapsed buyers) with strong privacy safeguards.
Attribution and outcome measurement: Clean rooms let partners securely join exposure logs (from CTV publishers) with conversion data (e.g. transactions, CRM events). That supports:
Sales lift and incrementality measurement.
Cross-publisher performance comparisons.
Frequency and overlap management: By analysing exposure across multiple publishers inside a clean room, brands can:
See how many households they hit via more than one CTV partner.
Adjust buys to reduce duplication and wasted impressions.
⚡ Clean rooms are quickly shifting from “nice to experiment with” to “necessary to compete.” Without them, it becomes much harder to use first-party data or prove the sales impact of CTV at scale.
Industry analysts and vendors like LiveRamp and Snowflake now describe clean rooms as a “must-have technology” for brands and media owners, not a niche experiment.
The CTV ecosystem is still fragmented, but 2026 is shaping up as a year of gradual consolidation and concentration.
Insider Intelligence’s H2 2025 CTV forecast highlights that big media mergers and streaming services combining forces are likely to make CTV budgets more concentrated across fewer large platforms.We are already seeing:
Major streamers bundling services and content libraries.
Media conglomerates consolidating their various apps under unified ad sales teams.
AVOD/FAST services expanding libraries and distribution deals to compete for share.
At the same time, supply-path quality is under scrutiny. The IAB Tech Lab recently addeddevice attestation to its Open Measurement SDK to combat device spoofing in CTV and mobile, improving trust in inventory authenticity and measurement reliability.
The net effect for advertisers:
Fewer but more powerful sellers: It may become easier to get scale from a smaller set of CTV partners, but those partners will have more leverage in rate negotiations.
Still-complex fragmentation: Even as major platforms consolidate, you will still deal with a mix of premium AVOD, FAST channels, vMVPDs, and OEM inventory.
Greater focus on supply quality: With higher budgets flowing into fewer pipes, advertisers are pressing for transparent supply paths, fraud safeguards, and consistent measurement.
For performance-driven marketers, that means being picky: prioritising partners that offer both high-quality inventory and robust measurement, while using programmatic controls (like supply-path optimization) to cut out low-value intermediaries.
Self-serve CTV platforms open the market to SMBs
For years, TV was a big-budget game. In 2026, that barrier has eroded. Self-serve CTV ad platforms and low minimum spends are opening connected TV to small and mid-sized businesses.
Hulu’s self-service platform, Hulu Ad Manager, explicitly markets itself as a way for “businesses of all sizes” to run streaming TV ads, with minimum campaign spends of $500.Roku’s Ads Manager similarly advertisesbudgets starting from $500 for TV streaming campaigns.Roku’s 2025 streaming predictions go further, stating that inventory pricing combined with low minimums on self-serve platforms will continue to lower the barrier for advertisers.
IAB’s digital video spend analysis reinforces this, calling out that programmatic self-serve tools are reshaping the CTV ad landscape for SMBs by making it as easy to launch a CTV campaign as a social ad set.
This trend is being amplified by AI:
SMBs can use AI tools to generate video creative quickly (as mentioned previously, nearly half of marketers are using AI for images and video). EMARKETER
Lightweight planning tools and templates help non-specialist marketers set up targeting, budgets, and measurement.
⚡ CTV in 2026 looks less like a walled garden for global brands and more like a marketplace open to ambitious local businesses.
💡 AI Digital’s Elevate platform is designed for this reality, combining AI-powered planning, cross-DSP optimization, and outcome-based insights so teams can run more efficient CTV and multi-channel programmatic campaigns.
Measurement standards begin to stabilize—slowly
Measurement has been one of CTV’s biggest headaches. The good news: in 2026, the industry is taking concrete steps towards more consistent, cross-screen metrics. The less good news: progress is gradual.
The IAB Tech Lab’s 2025 roadmap focuses heavily on evolving global technical standards for identity, attribution, and measurement to support converged TV.The IAB has also urged adoption of server-side conversion APIs for better, more privacy-safe outcome measurement, particularly for CTV and other environments where client-side tracking is constrained.
At the same time, industry forums like CIMM East highlight that currency fragmentation, clean room use, and data transparency are still major pain points for buyers and sellers.Many campaigns are still evaluated against multiple metrics and providers in parallel.
From a marketer’s perspective, 2026 measurement is defined by:
Multiple currencies, one set of goals: You may still deal with more than one audience “currency” (Nielsen, VideoAmp, etc.), but your internal KPIs—incremental reach, cost per outcome, sales lift—remain the anchor.
Greater transparency from platforms: Publishers are under pressure to provide more granular reporting and to support independent measurement and verification.
CTV integrated into MMM and attribution: As CTV’s share of spend grows, it is being pulled into media mix models and multi-touch attribution frameworks, rather than sitting in a separate “TV” bucket.
⚡CTV measurement will stay imperfect for a while, but that shouldn’t stop you from acting. Brands that pick a sensible framework and keep learning from each flight will move faster than those waiting for a final standard.
Taken together, these CTV advertising trends reshape how marketers plan, buy, and optimize video in 2026. Here is what changes in practical terms.
Planning shifts from channels to outcomes
You can no longer treat linear TV, CTV, and digital video as separate investments with separate goals. The reality of viewing behaviour (streaming surpassing broadcast + cable, as mentioned previously) means that TV planning needs to be converged.
That implies:
Budget discussions framed around total video reach and frequency.
Scenarios that show how different mixes of linear and CTV achieve the same reach goals at different costs.
A more outcome-oriented view of TV, where brand lift, traffic, and sales are standard metrics—not nice-to-haves.
Audience strategy becomes data-first, not demo-first
The collision of retail media and CTV, plus the rise of clean rooms, makes it possible to target on actual behaviours rather than broad demographics:
Use first-party data (CRM, app, site) to identify high-value segments and activate them in CTV via clean rooms.
Partner with retailers or other data providers to reach category buyers and measure sales, not just impressions.
Build “always-on” CTV programs that update audiences as new data flows in.
In practice, that moves TV targeting away from “Adults 25–54 watching primetime” toward “high-value customers who haven’t purchased in 90 days” or “new category buyers in the last 30 days.”
Creative becomes a performance lever, not just an asset
Because AI makes it easier to produce and test multiple video variants, creative now deserves the same optimization discipline you apply to search or paid social:
Plan for systematic creative testing in your CTV campaigns: multiple openings, offers, or CTAs.
Use DCO where available to tailor creative to segments, inventory types, or contexts.
Build feedback loops so performance data from CTV informs future creative briefs.
The teams that win are those who view creative not as a one-off production cost, but as a variable they can continuously improve.
SMBs and challengers become real TV competitors
Self-serve platforms and low minimums mean local and mid-market brands can now afford CTV advertising growth in their own right, instead of relying solely on search and social.
For larger brands, this brings both competition and opportunity:
Competition, because local players can now tell their story on the same living-room screen as national brands.
Opportunity, because franchisees, dealers, and local partners can co-fund and run their own CTV campaigns, adding local relevance on top of national work.
If you operate a distributed brand (franchises, dealer networks), 2026 is the year to formalize how you want those partners to use CTV.
Measurement demands a “good enough plus learning” mindset
Even as standards slowly improve, you will likely not get perfect cross-platform numbers in 2026. Instead, you should aim for:
A core measurement spine (e.g. brand lift + web/app conversions + sales where possible).
A limited set of currencies/providers you align on internally.
A culture of experimentation where CTV test results are fed back into your planning models (including MMM).
The organizations that move fastest are not the ones with perfect data, but the ones that make consistent decisions with the data they have.
Actionable recommendations
Here are practical steps you can take now to prepare for—and capitalize on—the 2026 connected TV trends.
1. Build a converged video plan
To make converged planning real rather than theoretical, start by tightening up the basics of how you structure and document your TV and CTV investment.
Combine your linear and CTV planning into a single process and document.
Ask your agencies or platforms for unified reach and frequency reports across all TV environments.
Run at least one scenario where you reallocate a portion of linear budget into CTV and estimate the impact on incremental reach and cost per outcome.
2. Treat CTV as part of your performance stack
IAB analysis of digital video buyers shows that the top reason advertisers reduce spend with a streaming partner is poor business outcome delivery, not weak brand metrics. That tells you how buyers are thinking.
Define performance KPIs for CTV: site visits, app installs, lead volume, or sales lift.
Ensure CTV campaigns are tagged and tracked in the same way as other performance channels where technically possible.
Use lift studies, conversion APIs, and clean rooms with key partners to quantify effect.
3. Put your first-party data to work in CTV
Use these steps to turn the customer data you already own into smarter targeting and more accountable CTV campaigns.
Audit what customer data you can legally and ethically use (emails, loyalty IDs, app IDs, CRM segments).
Map which CTV partners offer clean room integrations or other privacy-safe data matching options.
Start with one or two high-value use cases, such as:
Reactivating lapsed customers.
Upselling existing customers to higher-margin products.
The goal is to move from generic CTV audiences to segments grounded in your own data.
4. Lean into AI-assisted creative, with guardrails
These actions will help you tap AI for scale and speed in CTV creative without losing control of quality or brand voice.
Identify 1–2 AI tools to support video ideation and editing for CTV.
Set clear guidelines for your team: which parts of the process can AI handle, and where human review is required (e.g. brand tone, factual accuracy).
Design a creative testing plan for each major CTV flight:
At least two different openings or hooks.
At least two offers/CTAs if you have a performance objective.
A clear way of reading results (per-creative performance reports from your ad platform or DSP).
Complement this with AI Digital’s article AI in digital marketing, which explores broader governance and workflow considerations.
5. Pilot or expand use of self-serve CTV tools
Use the checklist below to test self-serve CTV in a controlled way, whether you are new to it or ready to open it up to more teams.
If you are a smaller brand or region, test self-serve platforms like Hulu Ad Manager or Roku Ads Manager for campaigns where a $500–$2,000 test is feasible.
If you are a larger brand, consider how these tools can be safely used by:
Local teams or franchisees.
Specific product lines that need agility.
💡 AI Digital’s Elevate can complement these tools by centralising planning and optimization while still allowing local experimentation.
6. Invest in clean room and measurement foundations
The points that follow focus on putting the plumbing in place so CTV can be measured, compared, and optimized alongside the rest of your media.
Choose a clean room partner (or work with publisher/retailer clean rooms) and run a pilot that connects CTV exposures with sales or CRM outcomes.
Align internally on a small set of core CTV metrics and providers to avoid “metric sprawl”.
Explore how CTV can be incorporated into your MMM and attribution frameworks, so its contribution is recognized fairly when budgets are set.
CTV in 2026 is defined by three words: measurability, data integration, and creative innovation.
Measurability, because buyers are increasingly judging CTV on business outcomes, not just GRPs.
Data integration, because first-party data, retail media, and clean rooms are changing how we target and attribute TV.
Creative innovation, because AI and new formats let brands tailor video to audiences with a level of agility that used to be reserved for social.
⚡ The brands that win CTV in 2026 will not be the biggest spenders—they’ll be the ones that treat TV as a test-and-learn engine.
If you want help applying these CTV advertising trends to your own roadmap, or you are exploring how AI Digital’s Open Garden model and Elevate platform can support your CTV strategy, you can get in touch with the AI Digital team.
Blind spot
Key issues
Business impact
AI Digital solution
Lack of transparency in AI models
• Platforms own AI models and train on proprietary data • Brands have little visibility into decision-making • "Walled gardens" restrict data access
• Inefficient ad spend • Limited strategic control • Eroded consumer trust • Potential budget mismanagement
Open Garden framework providing: • Complete transparency • DSP-agnostic execution • Cross-platform data & insights
Optimizing ads vs. optimizing impact
• AI excels at short-term metrics but may struggle with brand building • Consumers can detect AI-generated content • Efficiency might come at cost of authenticity
• Short-term gains at expense of brand health • Potential loss of authentic connection • Reduced effectiveness in storytelling
Smart Supply offering: • Human oversight of AI recommendations • Custom KPI alignment beyond clicks • Brand-safe inventory verification
The illusion of personalization
• Segment optimization rebranded as personalization • First-party data infrastructure challenges • Personalization vs. surveillance concerns
• Potential mismatch between promise and reality • Privacy concerns affecting consumer trust • Cost barriers for smaller businesses
Elevate platform features: • Real-time AI + human intelligence • First-party data activation • Ethical personalization strategies
AI-Driven efficiency vs. decision-making
• AI shifting from tool to decision-maker • Black box optimization like Google Performance Max • Human oversight limitations
• Strategic control loss • Difficulty questioning AI outputs • Inability to measure granular impact • Potential brand damage from mistakes
Managed Service with: • Human strategists overseeing AI • Custom KPI optimization • Complete campaign transparency
Fig. 1. Summary of AI blind spots in advertising
Dimension
Walled garden advantage
Walled garden limitation
Strategic impact
Audience access
Massive, engaged user bases
Limited visibility beyond platform
Reach without understanding
Data control
Sophisticated targeting tools
Data remains siloed within platform
Fragmented customer view
Measurement
Detailed in-platform metrics
Inconsistent cross-platform standards
Difficult performance comparison
Intelligence
Platform-specific insights
Limited data portability
Restricted strategic learning
Optimization
Powerful automated tools
Black-box algorithms
Reduced marketer control
Fig. 2. Strategic trade-offs in walled garden advertising.
Core issue
Platform priority
Walled garden limitation
Real-world example
Attribution opacity
Claiming maximum credit for conversions
Limited visibility into true conversion paths
Meta and TikTok's conflicting attribution models after iOS privacy updates
Data restrictions
Maintaining proprietary data control
Inability to combine platform data with other sources
Amazon DSP's limitations on detailed performance data exports
Cross-channel blindspots
Keeping advertisers within ecosystem
Fragmented view of customer journey
YouTube/DV360 campaigns lacking integration with non-Google platforms
Black box algorithms
Optimizing for platform revenue
Reduced control over campaign execution
Self-serve platforms using opaque ML models with little advertiser input
Performance reporting
Presenting platform in best light
Discrepancies between platform-reported and independently measured results
Consistently higher performance metrics in platform reports vs. third-party measurement
Fig. 1. The Walled garden misalignment: Platform interests vs. advertiser needs.
Key dimension
Challenge
Strategic imperative
ROAS volatility
Softer returns across digital channels
Shift from soft KPIs to measurable revenue impact
Media planning
Static plans no longer effective
Develop agile, modular approaches adaptable to changing conditions
Brand/performance
Traditional division dissolving
Create full-funnel strategies balancing long-term equity with short-term conversion
Capability
Key features
Benefits
Performance data
Elevate forecasting tool
• Vertical-specific insights • Historical data from past economic turbulence • "Cascade planning" functionality • Real-time adaptation
• Provides agility to adjust campaign strategy based on performance • Shows which media channels work best to drive efficient and effective performance • Confident budget reallocation • Reduces reaction time to market shifts
• Dataset from 10,000+ campaigns • Cuts response time from weeks to minutes
• Reaches people most likely to buy • Avoids wasted impressions and budgets on poor-performing placements • Context-aligned messaging
• 25+ billion bid requests analyzed daily • 18% improvement in working media efficiency • 26% increase in engagement during recessions
Full-funnel accountability
• Links awareness campaigns to lower funnel outcomes • Tests if ads actually drive new business • Measures brand perception changes • "Ask Elevate" AI Chat Assistant
• Upper-funnel to outcome connection • Sentiment shift tracking • Personalized messaging • Helps balance immediate sales vs. long-term brand building
• Natural language data queries • True business impact measurement
Open Garden approach
• Cross-platform and channel planning • Not locked into specific platforms • Unified cross-platform reach • Shows exactly where money is spent
• Reduces complexity across channels • Performance-based ad placement • Rapid budget reallocation • Eliminates platform-specific commitments and provides platform-based optimization and agility
• Coverage across all inventory sources • Provides full visibility into spending • Avoids the inability to pivot across platform as you’re not in a singular platform
Fig. 1. How AI Digital helps during economic uncertainty.
Trend
What it means for marketers
Supply & demand lines are blurring
Platforms from Google (P-Max) to Microsoft are merging optimization and inventory in one opaque box. Expect more bundled “best available” media where the algorithm, not the trader, decides channel and publisher mix.
Walled gardens get taller
Microsoft’s O&O set now spans Bing, Xbox, Outlook, Edge and LinkedIn, which just launched revenue-sharing video programs to lure creators and ad dollars. (Business Insider)
Retail & commerce media shape strategy
Microsoft’s Curate lets retailers and data owners package first-party segments, an echo of Amazon’s and Walmart’s approaches. Agencies must master seller-defined audiences as well as buyer-side tactics.
AI oversight becomes critical
Closed AI bidding means fewer levers for traders. Independent verification, incrementality testing and commercial guardrails rise in importance.
Fig. 1. Platform trends and their implications.
Metric
Connected TV (CTV)
Linear TV
Video Completion Rate
94.5%
70%
Purchase Rate After Ad
23%
12%
Ad Attention Rate
57% (prefer CTV ads)
54.5%
Viewer Reach (U.S.)
85% of households
228 million viewers
Retail Media Trends 2025
Access Complete consumer behaviour analyses and competitor benchmarks.
Identify and categorize audience groups based on behaviors, preferences, and characteristics
Michaels Stores: Implemented a genAI platform that increased email personalization from 20% to 95%, leading to a 41% boost in SMS click through rates and a 25% increase in engagement.
Estée Lauder: Partnered with Google Cloud to leverage genAI technologies for real-time consumer feedback monitoring and analyzing consumer sentiment across various channels.
High
Medium
Automated ad campaigns
Automate ad creation, placement, and optimization across various platforms
Showmax: Partnered with AI firms toautomate ad creation and testing, reducing production time by 70% while streamlining their quality assurance process.
Headway: Employed AI tools for ad creation and optimization, boosting performance by 40% and reaching 3.3 billion impressions while incorporating AI-generated content in 20% of their paid campaigns.
High
High
Brand sentiment tracking
Monitor and analyze public opinion about a brand across multiple channels in real time
L’Oréal: Analyzed millions of online comments, images, and videos to identify potential product innovation opportunities, effectively tracking brand sentiment and consumer trends.
Kellogg Company: Used AI to scan trending recipes featuring cereal, leveraging this data to launch targeted social campaigns that capitalize on positive brand sentiment and culinary trends.
High
Low
Campaign strategy optimization
Analyze data to predict optimal campaign approaches, channels, and timing
DoorDash: Leveraged Google’s AI-powered Demand Gen tool, which boosted its conversion rate by 15 times and improved cost per action efficiency by 50% compared with previous campaigns.
Kitsch: Employed Meta’s Advantage+ shopping campaigns with AI-powered tools to optimize campaigns, identifying and delivering top-performing ads to high-value consumers.
High
High
Content strategy
Generate content ideas, predict performance, and optimize distribution strategies
JPMorgan Chase: Collaborated with Persado to develop LLMs for marketing copy, achieving up to 450% higher clickthrough rates compared with human-written ads in pilot tests.
Hotel Chocolat: Employed genAI for concept development and production of its Velvetiser TV ad, which earned the highest-ever System1 score for adomestic appliance commercial.
High
High
Personalization strategy development
Create tailored messaging and experiences for consumers at scale
Stitch Fix: Uses genAI to help stylists interpret customer feedback and provide product recommendations, effectively personalizing shopping experiences.
Instacart: Uses genAI to offer customers personalized recipes, mealplanning ideas, and shopping lists based on individual preferences and habits.
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Questions? We have answers
How should advertisers rebalance budgets between linear TV and CTV in 2026?
Start by mapping where your audience actually spends time, then build scenarios that show total reach and cost with different linear/CTV mixes. In most cases, that will mean shifting a meaningful share of budget into CTV for incremental reach and performance, while keeping linear for specific use cases such as live events or older-skewing audiences. The right balance is the one that gives you the highest incremental reach and outcomes per dollar, not a fixed ratio.
What makes CTV a stronger performance channel in 2026 than in previous years?
CTV in 2026 benefits from better targeting via first-party and retail media data, broader access to shoppable and interactive formats, and more mature attribution tools. That combination turns CTV from a pure awareness play into a channel where you can track and optimize toward site visits, app installs, leads, and even sales. In practice, marketers can manage CTV performance much closer to how they already manage social or display.
Are FAST channels worth investing in for performance-driven campaigns?
Yes, FAST channels can be worthwhile when they are bought through partners that offer solid targeting, brand safety, and clear reporting. CPMs are typically lower than on premium AVOD services, which can make FAST useful for cost-efficient reach and retargeting. You should, however, monitor completion and conversion rates closely to confirm that the lower prices are translating into real performance, not just cheap impressions.
What types of creatives perform best on CTV in 2026?
The most effective CTV creative tends to brand clearly in the first few seconds, land a single focused message, and end with a direct, spoken call to action supported by on-screen cues such as a URL or QR code. Shorter spots (15–30 seconds) often work best for performance goals, while longer formats can support storytelling as long as they are paired with more direct follow-up messages. Tailoring creative to the audience and context—rather than using one generic TV spot everywhere—remains a major performance driver.
Which measurement models should marketers prioritize for CTV in 2026?
Marketers should focus first on outcome-based measurement such as conversion tracking, lift studies, or clean room–powered sales analysis, then feed those insights into media mix models to understand CTV’s role alongside other channels. Panel- and currency-based ratings still matter for trading, but internally you should anchor decisions on metrics like incremental reach, cost per outcome, and contribution to business KPIs. A simple, consistent framework you can maintain across campaigns is more valuable than chasing every new metric or provider.
How will AI change CTV buying and optimization in 2026?
AI will increasingly handle the heavy lifting of budget allocation, bidding, and frequency optimization across CTV inventory, using historical and real-time data to find the most efficient combinations. It will also surface patterns in creative performance and audience response that would be hard for humans to spot at scale, informing both planning and production. Your role as a marketer shifts toward setting clear objectives, defining constraints, and interpreting AI-driven recommendations rather than manually tweaking every lever.
Have other questions?
If you have more questions, contact us so we can help.