Where clicks used to play a key role in the customer journey of discovering, evaluating, and eventually purchasing a product, zero-click search is changing how consumers discover and interact with brands. Learn how advertisers can adapt attribution models and media strategies for AI-driven search.
Key Takeaways:
With the emergence of zero-click search environments, how consumers discover and evaluate brands is fundamentally changing. AI-driven summaries and chatbot responses now deliver near-instant answers, curated recommendations appear without clicks, and purchase decisions often happen quickly.
Today, users who see AI summaries in Google only click a link in the search results 8% of the time, compared to 15% when those summaries don’t appear. And about 80% of consumers now rely on zero-click results in at least 40% of their searches. For advertisers who have built discovery strategies around driving measurable traffic through organic and paid search, that foundation is shifting.
Thanks to zero-click search, today’s customer journey is often shorter and faster. Where users may have previously conducted multiple searches, clicked through various links, and synthesized information themselves, many are now choosing rapidly based on AI-generated results—often without clicking through to any of the sources cited. For advertisers, this means rethinking measurement frameworks, adjusting channel strategies, and optimizing content for AI consumption rather than just human readers.
Zero-click search environments fundamentally change how audiences encounter brands. In traditional search, advertisers compete for clicks through SEO-optimized content and paid placements. In AI-driven search, whether within browsers or large language models (LLMs), the algorithm decides which sources to surface, synthesize, and recommend.
Consider someone searching for vegan protein powder. Upper-funnel queries like “Are there non-dairy protein powders?” now yield AI-generated summaries pulling from reviews, blogs, and retail sites. Middle-funnel searches for “best” recommendations now often surface lists scraped from affiliate content rather than brand pages. And lower-funnel branded searches often show retail listings, not the manufacturer’s site.
As a result, AI serves as a sort of intermediary between brands and consumers, contextualizing information in ways advertisers and brands can’t control. This shift is accelerating: As of late 2025, about 50% of Google searches included AI summaries, and this figure is expected to surpass 75% by 2028. This means approximately half of searches now include AI-generated content that may reduce click-through rates or obscure brand messaging.
This new search environment creates winners and losers. Small publishers and content creators, for instance, report traffic falling by as much as 70% after the introduction of AI Overviews. And brands relying on broad upper-funnel queries, rather than product-specific information, have faced similar drops. Take, for example, HubSpot. The company previously drove pipeline through broad searches like “famous sales quotes”—content that attracted traffic but wasn’t tightly aligned to their product. When AI Overviews launched, their traffic dropped between 70% and 80%. AI systems prioritize content that directly addresses what a product does or solves, so teams must optimize for relevance over volume.
This trend extends beyond traditional search engines. Between about 40% and 70% of LLM users use these platforms for traditional search engine use cases: conducting research and summarizing information, understanding the latest news and weather, and asking for shopping recommendations. The shift from click-based to zero-click discovery is becoming the norm across multiple interfaces.
The attribution challenges that follow zero-click are fairly predictable: If users don’t click, traditional tracking breaks down.
Historically, clicks on non-brand search terms (i.e., generic category searches like “vegan protein powder”) signaled awareness-stage engagement. Teams tracked users gathering information, then returning later to convert through branded search. In zero-click environments, that initial touchpoint disappears. Users may not enter attribution models until (or if) they appear in brand searches, making it difficult to measure which campaigns drove discovery.
For advertisers, this means top-of-funnel visibility now often gets cut off. Someone researching products may not appear in measurement systems until they search for a specific brand name. This measurement gap makes it even harder to understand the already complex “messy middle” consumer journey that connects awareness to conversion.
Yet drops in click-through rates don’t necessarily signal poor performance. In fact, conversion rates may increase even as fewer people click, as the users who do take the time to click through may have already completed their initial research and be closer to making a decision. Users may see ads alongside AI summaries without clicking, and those impressions still influence purchase decisions. In some ways, zero-click makes non-brand paid search campaigns even more valuable. Ads appearing in category searches deliver messages that brands and advertisers can control, versus AI-generated results that they cannot. The challenge is that impression-based influence is harder to measure and easier to overlook. And higher conversion rates from fewer clicks can mask the total impact of a campaign. As such, pulling back on search investments because CTRs are declining could mean abandoning a channel that’s still driving conversions.
To adapt, advertisers should adopt broader measurement frameworks that account for both the quality of clicks and the reach of impressions. Statistical modeling across platforms, on-site surveys that ask “How did you hear about us?,” and brand lift studies can help replace lost upper-funnel indicators. As zero-click behavior further fragments the customer journey, understanding campaign impact across channels becomes more complex. Tools like automated advertising platforms that consolidate and unify data from search, social, programmatic, and video into clear dashboards help teams see patterns that single-channel reporting can miss.
Zero-click search demands strategic shifts across channels:
As a growing share of searches conclude within the results pages themselves, the brands that adapt most effectively will diversify their channel strategies, invest in measurement tools that capture impression-based influence, and optimize content for AI consumption. Success in a zero-click search environment requires expanding beyond reliance on search traffic alone and maintaining presence across channels where messaging remains controllable.
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Looking for more insights on how search and programmatic advertising are evolving? Our 2026 Programmatic Trends report explores the shifts reshaping digital advertising in the year ahead.
Key Takeaways:
That video advertising playbook you relied on last year? It’s already outdated. Between shifting viewer behavior, emerging platforms, and evolving quality concerns, the video ecosystem is changing fast.
By 2030, connected TV will capture more than 40% of global TV ad investment, reflecting a fundamental shift in how audiences consume video content. Today, however, linear TV still offers mass reach—which means advertisers must strategize around extracting maximum value now while planning for continued viewership declines. Meanwhile, the rise of social video, growing concerns about inventory quality, and complexities around addressability are reshaping what it means to run a successful video campaigns.
For advertisers building video strategies this year, understanding the nuances of this changing landscape is critical. Read on for six insights to guide your TV and CTV planning in 2026:
With nearly seven in 10 advertisers planning to increase their CTV spend in 2026, the industry’s commitment to CTV is continuing to accelerate. However, there's still an increasingly wide gap between ad spend and viewership: In 2027, there will be a 14-point gap between the percent of time US adults spend with CTV per day and the percent CTV ad spend makes up of total US ad spending.
CTV's advantages make this gap notable. The channel combines television's high-impact storytelling with digital precision targeting, superior completion rates, and direct attribution to consumer actions. In fact, three-quarters of American CTV owners prefer targeted ads to enhance their viewing experience, and more than one in five viewers have used their CTV devices to complete a purchase after seeing an ad. Add to this the emergence of new CTV ad formats and expanding inventory options, and it's clear that advertisers who match their spend to viewership now stand to gain significant competitive advantage before the market catches up.
But don’t write off linear TV just yet: While connected TV continues its steady climb, traditional television still delivers the kind of mass reach that many campaigns need, particularly those focused on driving brand awareness.
And no, this isn’t just your grandparents watching Jeopardy (or you watching Jeopardy, if Jeopardy is your thing!). Audiences across all age groups still tune in to traditional broadcasts, though younger generations are doing so less frequently than their older counterparts.
However, linear TV’s reach is eroding as more viewers shift to streaming alternatives: In 2026, CTV offers access to 15% more of the US population than linear. Advertisers must ensure their linear and CTV strategies complement each other in the short term, while planning for linear’s decline and the continued rise of CTV and social video.
This might look like running broad awareness campaigns on linear TV during high-profile events like live sports, then using CTV to extend reach to cord-cutters and younger viewers who don't watch traditional TV. Or, it could look like managing CTV campaigns with a platform that offers Open Addressable Ready (OAR) capabilities, which enable consistent, addressable campaigns across both linear and streaming using unified audience data and measurement. Advertisers should also allocate budget dynamically—shifting spend to CTV as linear reach declines, while maintaining traditional TV presence where it remains cost-effective.
Ultimately, success lies in treating linear and CTV as complementary tools in a holistic video strategy that evolves alongside viewer behavior.
The boundaries between TV and social media are dissolving faster than audiences can scroll to the next video in their TikTok feed. This is especially true among younger audiences, with nearly 80% of young people aged 10-24 reporting that they watch movies or TV shows on social platforms.
Sports content, in particular, is driving social video engagement (as well as live CTV engagement): Between 2020 and 2024, the percentage of Americans who reported they watched live sports games on social media platforms in the last month grew by 34%.
Following these viewership trends, US advertisers invested more than $10 billion more in social video than in linear TV in 2025.
Recent spending trends show social video and CTV budgets are climbing while linear investments decline: In 2025, CTV and social video dominated the priority list for video advertising budgets, setting the stage for continued growth in 2026.
The living room TV? Still relevant. But today, it’s far from the only screen that matters for reaching video-watching audiences.
In 2026, buying inventory from a recognizable streaming service doesn’t guarantee your ads will appear in brand-safe, high-quality environments. As the streaming ecosystem has matured, the term “premium” has been applied so broadly that it’s lost much of its meaning. Spoiler alert: Slapping a well-known logo on an ad buy doesn’t automatically make it premium.
Much of what advertisers purchase on major platforms runs within long-tail apps, user-generated content channels, or bundled placements that offer minimal transparency. As a result, 15% of streaming TV ad spend is wasted in low-quality environments rather than premium streaming content.
Considering this, it’s critical that advertisers demand transparency from their CTV providers. Just as important is implementing quality controls when buying CTV inventory to ensure spend isn’t wasted on low-quality placements—for example, by checking in on campaigns midstream to make sure ads are showing up where intended. Overlaying ACR (automatic content recognition) data into CTV buys can also help by offering more precise visibility into placements, verifying exactly what content appeared on-screen when your ad ran.
Ultimately, premium placement in streaming comes from verification and control, not brand recognition alone.
While video strategies of the past focused on specific channels and distribution methods, the video strategies of the future will focus on following engaged audiences wherever they’re consuming content, regardless of the screen.
This means treating CTV, social video, and linear TV as complementary tools in a unified strategy rather than competing channels. Advertisers must align their content objectives with inventory-specific tactics across platforms. Broad awareness campaigns might justify run-of-content purchases, but performance-focused initiatives demand curated placements and app-level visibility.
The shift from channel-first to audience-first planning is showing up in how advertisers choose their partners: 66% of media buyers cite audience personalization capabilities as the most important factor when choosing video ad partners.
Marketing teams are implementing this audience-first approach by leveraging CTV targeting parameters including behavioral and demographic segmentation as well as content-level contextual targeting to connect with viewers in high-quality environments—then extending those learnings across social video and other channels. AI-powered, all-channel platforms can help with this by automatically applying these learnings to optimize buys across channels.
Streaming TV’s promise of precise, addressable advertising faces a critical data quality challenge. Many platforms claim they can offer addressability, but the accuracy varies significantly based on the kind (and quality) of data powering it.
IP-based targeting, which many platforms rely on, suffers from significant accuracy problems. IP-to-postal linkages are correct just 13% of the time on average, while IP-to-email connections hit the mark only 16% of the time. Yes, that means they’re wrong a whopping 87% and 84% of the time, respectively! These error rates undermine the targeting precision that makes addressable TV attractive in the first place.
As the addressability landscape develops, advertisers must understand what kind of addressability the platforms they invest in offer. To accomplish this, teams should ask their CTV partners specific questions: What data sources power your targeting capabilities? How accurate is your addressability, and how do you measure it? Do you primarily use deterministic data or probabilistic data? Platforms that can’t answer these questions transparently may not offer the precision they promise. And to enhance precision, advertisers should layer first-party and deterministic data—which offer the highest level of targeting accuracy—into their buys.
Today’s streaming landscape offers tremendous opportunities for advertisers willing to navigate its complexities. Success requires moving beyond assumptions about premium inventory, channel effectiveness, and targeting precision, and crafting strategies grounded in audience behavior, content quality, and data transparency.
Six Key Takeaways:
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Want to dive deeper into what’s shaping the future of advertising? Check out Rewinding to Fast Forward: The 2026 Digital Advertising Trends Report for more insights into how the media landscape is evolving and what it means for your marketing strategy.
Welcome to our recurring blog series, “The Breakdown.” Each post breaks down a complex marketing concept and explores its applications—helping you make smarter decisions that drive meaningful results.
Marketers face a pivotal choice in 2026: to frame their use of AI around driving business growth, or around cutting costs.
While AI can accelerate efficiency and reduce costs by speeding production and scaling content, its real power lies in the effectiveness it can deliver in the form of optimized creative, personalization, and predictive insights. Marketing leaders should guide their teams toward strategies that use AI to strengthen brand equity and long-term enterprise value, rather than focusing solely on its ability to drive efficiency gains and short-term margin improvements.
Data readiness is critical to achieving this goal. Without a strong foundation of unified first-party data and custom AI solutions trained on that data, organizations will struggle to create the differentiated outputs that drive brand and business growth.
How marketing leaders approach and position their use of AI in 2026 will define the role of marketing within their organizations for years to come.
While teams should absolutely use AI for efficiency-related gains like faster campaign execution and lower production costs, emphasizing its impact on efficiency alone can inadvertently play into the notion that marketing is merely a cost center that should be trimmed to the bone, rather than a strategic asset that can fuel effectiveness and multiply revenues. This, in turn, can reduce departmental resources and weaken marketing’s role in the larger organization.
Instead, marketers should embrace AI’s ability to drive sustainable growth through smarter targeting, better creative, and real-time optimization. This can look like implementing enterprise AI tools to augment or automate the media planning process, leveraging AI-powered software to improve and scale creative ideation and testing, exploring AI-powered optimization for real-time performance enhancement across campaigns, or creating AI synthetic audiences—AI-generated, data-driven models of real people—that simulate how specific customer groups might respond to creative variations.
This value-driven approach can have transformative impacts: When AI is used to enhance marketing effectiveness rather than just to improve efficiency, companies can more than double marketing-driven profitability.
Critically, this work goes beyond using AI to drive long-term growth. Marketing teams must also demonstrate how their teams’ use of AI impacts business outcomes, and earn executive buy-in for reinvesting productivity gains into long-term growth rather than settling for short-term wins.
Differentiated AI results require proprietary solutions fueled by large volumes of clean, unified first-party data. And with 58% of industry professionals citing data quality and accessibility issues as critical challenges to adopting AI, marketers must prioritize data readiness to realize these maximal business-level gains.
A lack of data readiness appears to be the norm among marketing teams: Just 17.9% of marketing and advertising professionals describe their first-party data as extensive and well-structured, and a whopping one-third of those professionals say that first-party data plays little-to-no role in their businesses’ current AI initiatives. Even more, nearly half of marketers and advertisers report that their organizations don’t currently use any custom AI solutions or have any imminent plans to develop them.
Personalized, company-specific instances of AI solutions are critical to driving the business-level outcomes that can position marketing as an indispensable revenue driver, but they require quality data for training and rigorous planning to ensure that any desired use cases align with specific, measurable outcomes. As such, organizations that prioritize data readiness—and use that infrastructure to power custom AI solutions—stand to substantially outperform their competitors.
Marketers who frame AI as a driver of business growth rather than solely operational efficiency will be better positioned to secure ongoing investment and strategic influence.
This starts with building business cases that connect specific AI capabilities directly to revenue and brand outcomes. Demonstrating marketing's contribution to enterprise value creates the foundation for budget expansion rather than contraction.
Realizing these outcomes requires prioritizing first-party data infrastructure. Quality, accessible data differentiates AI outputs—without it, even sophisticated tools produce generic results competitors can replicate. Once that data infrastructure is in place, it should fuel custom AI solutions built to amplify growth. Proprietary (and/or semi-custom) models trained on brand-specific data reflect unique market positioning and audience understanding, enabling organizations to establish competitive advantages that strengthen marketing's strategic position over time.
Ultimately, the choices marketing leaders make about AI positioning today will determine whether their teams are properly perceived as growth drivers—or unfairly maligned as cost centers—for years to come.
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Want more insights into how AI is reshaping marketing strategy? We surveyed marketing and advertising professionals from top agencies and brands to gather data on AI adoption trends, performance improvements, and implementation challenges. Check out AI and the Future of Marketing for a deeper dive into the opportunities and obstacles shaping marketing’s AI future.
Ad curation has evolved from a niche programmatic tactic to a strategic necessity for many advertisers navigating quality concerns, budget scrutiny, and supply chain opacity. As spending on curated deals climbs and transparency becomes non-negotiable, marketing leaders need to understand what's driving this shift and how to leverage curation effectively.
Key Takeaways:
Ad curation isn’t a new concept, but in 2026, advertisers are embracing it with renewed urgency.
From widespread bot traffic and heightened brand safety concerns to the proliferation of made-for-advertising (MFA) sites, industry challenges are creating considerable stress for marketing teams. CMOs are under pressure to do more with less budget. Agency leaders are caught between rising operational costs and shrinking profit margins while trying to prove value to clients. Meanwhile, media buyers must deliver results in a digital ecosystem that’s seemingly growing more complex and fragmented by the day.
In this context, it’s no wonder ad curation is gaining momentum. As advertisers seek control, efficiency, and transparency, spending on curated inventory is rising fast, with programmatic advertisers expected to spend more than twice as much on private marketplaces (PMPs)—a common format for curated deals—as on the open exchange this year. By enabling advertisers to access pre-vetted inventory enriched with data signals like first-party data, strategic curation allows teams to invest in quality, avoid waste, and connect with target audiences in key moments of impact. And for leaders, it can offer a way to bring clarity to complexity: streamlining media strategies, prioritizing brand safety, and delivering performance that’s easier to measure and defend.
By understanding what’s driving the current momentum behind ad curation and applying it intentionally, advertisers can drive stronger outcomes, reach people in trusted environments, and prove the ROI of their media investments to key stakeholders.
Intentional media buying has become a strategic necessity. In a digital landscape plagued by quality concerns and growing performance pressure, advertisers are becoming far more discerning in where they invest.
Concerns around waste, brand safety, and personalization are at the forefront for most marketers. One recent report found that roughly $701 million—representing 10% of global open programmatic ad spend on websites—went to MFA sites in Q1 of 2025 alone. Bot traffic is on the rise, now accounting for 37% of all internet traffic. For the first time in a decade, automated traffic has overtaken human traffic, a trend largely driven by the explosion of low-quality, AI-generated content. At the same time, signal loss and rising privacy expectations are making it harder to reach target audiences using traditional identifiers.
Economic volatility only intensifies these pressures. As budgets tighten, scrutiny on media investments increases. Every dollar must work harder, and leaders are expected to prove ROI faster and more rigorously than before.
Curation can offer a powerful response to these many challenges. When implemented strategically, curated deals, often powered by first-party data and contextual targeting, can enable advertisers to deliver more relevant messaging in trusted environments—while also respecting user privacy. By bundling premium, brand-safe inventory with privacy-friendly data signals, well-executed curated deals can help advertisers reach audiences in the right moments, minimize waste, and drive measurable performance.
The growing emphasis on investment reflects a deeper recognition: In today’s media landscape, quality and performance are no longer separate considerations.
Low-cost media placements might require less investment, but they often underperform. Campaigns run on unvetted sites can suffer from low viewability, weak engagement, or poor conversion rates. These hidden costs—from wasted impressions to brand safety risks—can easily outweigh any initial savings.
In contrast, curated deals can allow advertisers to focus on inventory that’s prepackaged for relevance and engagement. For example, a baby and toddler brand running holiday promotions might use a curated deal built around parenting lifestyle content with high engagement from millennial parents. Or, a financial services company could activate a curated PMP featuring premium business publications, reaching high-intent readers in trusted, high-attention environments.
These kinds of curated activations allow advertisers to align messaging with contextually relevant content, avoid fraudulent or wasted impressions, and reach audiences in environments that drive stronger outcomes. In an economic environment where every dollar is under increased scrutiny, this kind of precision is critical. While curated media may not always offer the lowest upfront cost, it can often deliver stronger value by reducing waste and supporting more focused, results-oriented investment.
In addition to quality concerns, the conversation around programmatic transparency has reached a tipping point. For years, advertisers accepted opacity in the supply chain as an unavoidable cost of doing business. But in 2026, that indifference carries a price few organizations can afford.
Analysis by the ANA shows that only 36 cents of every programmatic dollar actually reaches publishers. The remaining funds are absorbed by intermediaries, platform fees, and layers of technical infrastructure that often provide little visibility or tangible value to advertisers. The scale of this inefficiency makes it difficult to ignore: In 2025, waste in programmatic spend was estimated to total about $26.8 billion globally.
Such inefficiencies directly erode campaign performance, weaken publisher sustainability, and undermine the business case for media investments. When nearly two-thirds of every dollar spent vanishes before reaching working media, leaders face an uphill battle defending budgets.
Curation can help close that gap. By providing tighter, verifiable supply paths, curated deals can give advertisers clearer visibility into where ads appear and how budgets are deployed. While curation does add another layer to the supply chain, it can also streamline the path between advertiser and publisher by consolidating spend with trusted partners and delivering greater transparency. And when used in conjunction with open inventory, curation can enhance programmatic scale, allowing advertisers to balance broad reach with verified quality and maintain flexibility across different campaign objectives.
The urgency around transparency reflects a practical challenge: Proving ROI is incredibly difficult when most of the budget disappears into the nebulous unknown. Without verified, contextually aligned impressions served to real people, performance metrics themselves become unreliable. Advertisers who treat transparency as a strategic function (rather than an afterthought) gain a measurable advantage: 41% of marketers see curated deals as a path to higher ROI, driven by reduced waste and stronger performance in trusted environments.
As media buying becomes more complex, efficiency and precision are growing increasingly important. For advertisers facing quality and transparency challenges, curated deals can support both goals—not by replacing DSPs, but by working in tandem with them.
By filtering inventory based on performance criteria, brand safety, and contextual relevance, curation simplifies the early stages of the media buying process. By the time this inventory enters a DSP, it is already optimized for different campaign goals, allowing buyers to focus on optimizing bids and managing campaign performance in real time.
This can help improve operations across the board. When incorporating curation within a holistic media strategy, teams spend less time fixing inventory issues and more time refining strategy. And when curated inventory is available within a unified platform that also includes search, social, and open marketplace programmatic, the benefits are even greater. Rather than managing multiple point solutions and reconciling data across different dashboards, teams gain a more streamlined workflow, cross-channel optimization, and unified reporting.
Together, these capabilities help advertisers to reduce waste, improve outcomes, and respond more confidently to performance expectations. And for CMOs and agency leaders, they provide better visibility into campaign performance, which is key for building compelling business cases for media investments.
To get the most from curated media, advertisers need to take a thoughtful approach. Teams should look for partners and integrations that are clear about how inventory is curated—including the data used, the filtering logic applied, and the deal structures or fee arrangements behind it. Transparency is essential, especially as more solutions in the market begin labeling themselves as “curated” without meaningful differentiation. As curation gains momentum, advertisers should be wary of vendors repackaging standard programmatic inventory under the “curated” label without implementing rigorous quality controls or supply path optimization. This risks teams paying premium prices for deals that don’t deliver measurably better performance or transparency than open exchange alternatives.
Additionally, given that curation adds another layer to the supply chain, advertisers should evaluate whether the performance lift justifies both the additional cost and complexity. Structured testing that measures incremental value against these trade-offs can help determine when curation delivers meaningful returns.
Taking a holistic approach is also critical. Curated media shouldn’t operate in isolation. The most effective strategies embed curation into broader omnichannel campaigns—and ideally within platforms that support unified workflows across multiple channels. This ensures that curated media supports larger business goals and works alongside other channels and strategies.
Finally, performance measurement is key. Advertisers should track how curated media performs compared to non-curated environments, with attention to both engagement and cost efficiency. Premium pricing may be justified if the results are there, but it takes intentional measurement to know when and why that’s true.
The momentum behind ad curation reflects a fundamental shift in how advertisers approach programmatic investment. It signals that advertisers are moving away from purely volume-driven tactics and instead prioritizing inventory that delivers measurable impact while maintaining brand safety standards.
For agency and brand leaders, this shift presents both an opportunity and a strategic imperative. The open exchange remains an important source of reach, but in 2026, it’s increasingly paired with curated strategies that bring added control. Together, they enable advertisers to pursue growth without compromising accountability.
As generative AI and advanced data signals continue to evolve, curation will grow even more sophisticated, enabling more precise contextual targeting while maintaining privacy standards. Those who integrate curated approaches in a thoughtful way now—combining them with data-driven strategies and cross-channel optimization—will be better positioned to demonstrate clear ROI, defend investments to key stakeholders, and gain a competitive advantage in the increasingly complex digital media landscape.
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Want deeper insights into the trends shaping advertising this year? Our 2026 Trends Report: Rewinding to Fast Forward explores the forces shaping media quality, transparency, and performance—including how to turn the industry’s quality quandary into a strategic advantage.
Key Takeaways
Advertisers’ ultimate goal is to drive effectiveness by identifying the optimal media mix for specific campaigns to drive key business outcomes. Equally important, though, is proving out that effectiveness: Connecting media investments to results through compelling, cohesive narratives that build stakeholder confidence and secure continued investment.
Yet media fragmentation creates significant barriers to achieving both goals. When performance signals are scattered across platforms and channels, each with its own reporting methodology, omnichannel campaign evaluation—and the ability to make real-time adjustments—is often painfully slow at best.
This matters enormously: In the pursuit of advertising effectiveness, omnichannel campaign evaluation is the holy grail, empowering teams to both drive results and demonstrate impact. As such, it’s essential for marketing teams to strategize around how to achieve holistic campaign assessment amidst fragmentation. The most successful approaches include systems and frameworks that allow teams to streamline performance signals across channels and evaluate effectiveness in both the short- and long-term.
Today’s consumers demand advertising experiences that seamlessly span the many digital spaces where they spend time. At the same time, diversifying media spend across channels delivers greater returns in revenue and brand performance.
But as marketers split their efforts across a growing number of platforms and channels, the resulting tech stack sprawl—over half of agency marketers’ stacks consist of eight or more tools, and 40% are using 10 or more—presents a variety of problems. In fact, 45% of agency leaders cite siloed or disconnected systems as a top challenge.
Data fragmentation from these disconnected systems underlies a host of marketing leaders’ biggest pain points. Most fundamentally, manually consolidating data from multiple sources is both time-consuming and error-prone, which prevents the agile and strategic decision making necessary to drive effectiveness. Consequently, only 21% of senior marketers report receiving actionable data in real time.
Fragmentation also curbs teams’ ability to demonstrate the impact of their work, which strains client partnerships for agencies and impacts budgets and stakeholder confidence for brands. Marketing leaders at brands identify connecting marketing activities to revenue outcomes as their most pressing challenge—a particularly urgent issue as CMOs face heightened pressure to prove ROI.
To succeed in this fragmented landscape, marketing teams must develop dedicated strategies for holistically measuring performance across both the short- and long-term.
The baseline for short-term cross-channel measurement is tracking performance on each individual platform and channel. Advertisers must examine each source of truth across their media mix and assess platform-level performance using attribution and KPIs like immediate sales, cost of acquisition, or ROAS.
Because of the lack of interoperability among walled gardens and the open web, advertisers typically won't know if a consumer saw the same ad on, say, both Facebook and Pinterest. While this can result in double-counting conversions, it doesn't hinder platform-level optimization, which remains essential for driving and demonstrating effectiveness.
The disconnection between walled gardens and the open web creates significant limitations, but marketing leaders can help their teams manage the complexity. The key is streamlining performance signals across channels to understand how they work together to drive short-term outcomes. Advertising platforms that automatically aggregate data from multiple sources across walled gardens and the open web—eliminating time-consuming manual work—provide teams with a comprehensive view and a significant competitive advantage.
However, to fully achieve holistic measurement, marketing teams must look beyond immediate, platform-level performance metrics and find ways to take a broader view of their investments.
To truly drive and demonstrate effectiveness, omnichannel campaign evaluation can’t end with short-term strategies. When assessing how successfully your advertising is driving business outcomes, it’s critical to take a long-term perspective.
Assessing long-term effectiveness holistically is all about finding ways to gather every available signal into one place and extract bigger learnings about their impact. To that end, integrated campaigns across the open web and walled gardens can be evaluated over a longer term against key metrics that can’t be properly attributed to a single source, such as brand health, sales growth, and profitability.
Marketing mix modeling (MMM) and experiments are two tools marketing teams can use to assess these bigger metrics.
With MMM, advertisers can model how their investments across multiple platforms drive business outcomes over time. For instance, by analyzing historical data, MMM can predict that investing X amount of money across digital marketing contributed to Y% of overall sales, led by Facebook, Google, and programmatic tactics.
Experiments, meanwhile, allow advertisers to test hypotheses about long-term effectiveness through controlled tests. In a geo lift study, advertisers can run an omnichannel campaign at different intensities across similar geographic markets and measure the differential impact on sales growth or brand awareness. Market studies can compare regions with varied media strategies to understand which combinations drive better long-term outcomes.
These modes of long-term measurement have often been underused by marketers, although they’re gaining steam as the industry grapples with measurement challenges: Between 2024 and 2025, the share of marketers using experiments to measure effectiveness doubled from 18% to 36%.
However, in 2024, only 2% of marketers were using a combination of MMM, experiments, and attribution to assess advertising effectiveness. The underutilization of this multi-pronged approach to long-term omnichannel campaign evaluation presents a major opportunity for advertisers seeking to both drive and demonstrate advertising effectiveness better than their competitors.
There's no getting around the fact that omnichannel campaign measurement remains a challenge for marketing teams of all sizes. However, precisely because of this challenge, teams who strategize around it more successfully than their peers stand to gain major competitive advantages.
Success depends on streamlining performance signals and implementing diverse strategies for both short-term and long-term measurement. Ultimately, the teams that dedicate the necessary resources to achieving omnichannel campaign evaluation amidst fragmentation will also be the most successful when it comes to driving and demonstrating effectiveness.
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Looking for more insights into how to navigate the biggest challenges and opportunities facing marketers? Check out Rewinding to Fast Forward: The 2026 Digital Advertising Trends Report for a breakdown of four key trends set to define the industry this year.
Programmatic advertising continues to command the lion’s share of digital budgets, but entering 2026, the forces shaping it point to a more disciplined phase of growth. Rising scrutiny around media quality, shifting consumer discovery patterns, and the deepening role of AI are pushing advertising leaders to rethink how programmatic delivers true value—not just scale.
Key Takeaways:
These trends underscore a broader shift in programmatic advertising, and success in 2026 will depend less on maximizing volume and more on managing complexity with intention, structure, and accountability.
As global ad spending is set to surpass $1 trillion for the first time, programmatic advertising continues to play a central role.
In 2025, programmatic digital display ad spending in the US grew 13.6%, surpassing $180.4 billion and accounting for nearly 92% of all digital display ad spend. That momentum shows no signs of slowing. In 2026, US programmatic display spending is expected to exceed $203 billion, representing year-over-year growth of 12.5%. Globally, programmatic is projected to account for roughly 90% of display ad budgets and nearly all incremental growth in display for the foreseeable future. With major events like the Winter Olympics, FIFA World Cup, and key midterm elections set to fuel the media landscape in 2026, the scale and stakes of advertisers’ programmatic investments will be especially high.
This growth is occurring against a backdrop of both challenge and opportunity. Privacy expectations continue to rise, data signals remain inconsistent, and long-standing assumptions about addressability and measurement are being tested.
While Google reversed its plans to fully deprecate third-party cookies in Chrome, the decision did little to resolve the broader challenges associated with signal loss. For many advertisers, declining data quality and shrinking addressable audiences remain daily realities, regardless of browser policy changes. Yet these same pressures are driving innovation in inventory curation, first-party data strategies, and privacy-conscious targeting approaches that promise more effective, sustainable advertising.
Artificial intelligence is further reshaping the programmatic ecosystem. AI is now embedded across the advertising workflow—from campaign planning and optimization to creative development and analytics—but its most alarming impact may be the flood of AI-generated content entering the programmatic supply chain. The rapid proliferation of generative AI is raising the stakes for brand safety and media quality, as low-quality synthetic content becomes harder to distinguish from legitimate inventory. While AI is also powering many of the tools to combat these challenges, the race between synthetic content creation and detection will be a defining feature of programmatic quality in 2026.
Meanwhile, consumer attention continues to splinter across channels and formats. Retail media networks are expanding quickly, short-form video is commanding a growing share of budgets, and ad-supported streaming is evolving with new formats and placements. At the same time, discovery itself is changing, as zero-click search experiences and AI-generated summaries reduce traditional paths to traffic and engagement (not to mention attribution).
Taken together, these forces have made programmatic advertising all the more powerful…and all the more demanding. The year ahead will test how well advertisers can manage AI-driven risks and opportunities, consolidate data foundations, adapt to new discovery patterns, and execute across evolving video and commerce environments.
Simply put, AI is reshaping the programmatic landscape.
While the technology has improved efficiency, the rapid spread of AI-generated content has increased the volume of low-quality inventory that can slip into campaigns, making it harder to separate genuine human interest from surface-level impressions.
AI-generated sites and content farms can deliver high impression counts and engagement signals that look legitimate in reporting but don’t translate to brand recall or purchase intent. This dynamic has elevated brand safety from a reputational concern to a performance issue. With 54% of advertisers believing generative AI has contributed to a decline in overall media quality, teams must rethink how they evaluate inventory and interpret campaign results to ensure optimization is grounded in authentic engagement.
Advertising leaders are responding by layering smarter controls into their buying strategies. Pre-bid protections, contextual intelligence, curated supply, and ongoing delivery analysis can help advertisers identify patterns associated with low-value or synthetic content before spend accumulates. These approaches reduce waste and ensure optimization decisions are based on reliable signals rather than volume that masks low-quality environments.
In 2026, advertisers must find ways to reliably and consistently apply these guardrails systemically across their programmatic strategies, leveraging AI for routine monitoring while reserving human expertise for strategic oversight and decision-making.
As consumer concerns around data privacy remain high and signal loss continues to reshape addressability, first-party data has become central to programmatic strategy.
In 2025, 40% of US marketers relied on first-party data as their primary privacy-centric targeting approach. Meanwhile, the usefulness of third-party cookies has continued to decline, this despite Google’s U-turn on deprecation in Chrome. As audiences move fluidly across platforms and formats, the signals cookies provide are increasingly partial, limiting their effectiveness as a foundation for long-term planning.
Yet as powerful a tool as first-party can be, data alone is not enough. Without strong organization and consolidation, even high-quality data struggles to deliver impact, particularly as AI becomes more deeply embedded in planning, activation, and optimization.
Fragmented data remains a major barrier for marketers: Fewer than one in five industry professionals say their first-party data is extensive and well-structured, while 34% describe it as limited or disconnected. Much of this stems from tech stack sprawl, with more than half of agency professionals reported to use eight or more tools to manage campaigns and 40% juggling 10 or more. These gaps make it harder to respect consumer choice, apply consistent governance, and generate reliable insights, while simultaneously undermining AI performance by limiting data-powered optimizations and increasing the likelihood of flawed recommendations driven by incomplete or inconsistent inputs.
Without data consolidation, these challenges compound. Unifying data across systems enables privacy-conscious targeting, clearer measurement, and more responsible use of AI—allowing advertisers to do more with less signal while maintaining trust and performance.
With the emergence of zero-click search environments, advertisers must also adapt to how consumers discover and evaluate brands.
As AI-generated summaries, AI Overviews, and AI agents increasingly resolve queries directly within a search or chatbot interface, fewer users are clicking through to websites. Recent research shows that only about 8% of users click links from Google’s AI summaries, signaling a meaningful shift in how discovery happens. More broadly, a growing share of searches conclude within the results pages themselves, with many users finding the information they need without clicking through to another destination.
This evolution challenges long-standing assumptions about search performance and attribution. When answers are delivered without a click, traditional KPIs like CTR and last-touch conversions become less reliable indicators of impact.
In this new context, brand exposure, contextual relevance, and repeated presence across channels increasingly shape consideration throughout the customer journey, with audiences visiting websites later and later in the process…if they visit at all. In parallel, brands must also account for how they appear within AI-driven search results and large language model (LLM) outputs, where summaries, recommendations, and cited sources can shape perception without any direct interaction. Visibility now extends beyond links and placements to include how—and whether—a brand is represented in these emerging information environments.
For programmatic advertisers, this shift elevates the role of display, video, and contextual placements in the awareness and consideration process. These channels help establish familiarity and preference in moments when consumers are forming opinions, even if they never leave the search or AI interface. Measurement frameworks and media strategies must evolve to reflect a world where visibility still drives value—just not always traffic—and where influence is distributed across a broader, more decentralized ecosystem.
As measurement and attribution models evolve to account for zero-click influence, programmatic budgets continue flowing toward environments that connect media to transaction data.
Commerce media has been one of the fastest-growing areas within programmatic advertising, reshaping how brands connect media exposure to purchase behavior. In 2025, retail media programmatic display spending grew more than twice as fast as total programmatic display, reflecting advertisers’ appetite for environments tied closely to transaction data and retail signals. WPP’s end-of-year forecast highlighted just how quickly the category has scaled, projecting that commerce media would surpass television in total spend by the end of 2025.
As the category matures, however, the focus is shifting from rapid expansion to execution and integration. Growth may not continue at the same pace, and leaders are increasingly grappling with inconsistency across retail media networks, misaligned measurement frameworks, and rising operational demands. At the same time, early signs of agent-driven commerce are beginning to influence how value is created within these environments. Industry forecasts suggest that by 2028, a meaningful share of digital storefront interactions could be handled by automated “machine customers.” As these systems play a larger role in product discovery, comparison, and purchase decisions, the quality and consistency of product data, pricing signals, and promotions are becoming just as important as media placement itself.
Today, commerce media demands integration, not just investment. Advertisers that treat commerce media as a core component of their programmatic strategies—supported by disciplined measurement, strong data foundations, and intelligent automation—will be better positioned as retail media evolves from a breakout growth channel into a more machine-mediated, long-term pillar of the media mix.
Programmatic video is increasingly concentrating around short-form, mobile-first formats. As audiences turn to quick, scroll-based video for entertainment, inspiration, and product research, ad budgets are following in kind.
In 2025, social video accounted for 53.7% of programmatic video ad spending, reflecting how budgets have followed audience behavior. Engagement patterns reinforce this shift, with a majority of consumers interacting with short-form video multiple times per day and using it as a source for product discovery and recommendations.
This dynamic is especially pronounced among younger audiences: Gen Z—whose spending power is projected to reach $12 trillion by 2030—engages with short-form video at a higher frequency than older cohorts and relies on it as a primary source of entertainment, inspiration, and discovery. As a result, short-form video ads are influencing consideration earlier and compressing the path from exposure to action faster than traditional video formats.
In 2026, the challenge for advertisers will be less about whether to invest in short-form video and more about how deliberately they do so. Creative must be built for the format and paired with strong brand safety guardrails and deliberate KPIs that account for how quickly short-form video can drive movement from awareness to action. As short-form video continues to absorb both attention and budgets, advertisers that integrate it thoughtfully within broader omnichannel strategies will be better positioned to convert fleeting moments into durable impact.
Subscription fatigue is driving viewers toward ad-supported streaming—and turning CTV into a laboratory for format innovation. The experimentation is pushing CTV beyond standard pre-roll and mid-roll placements toward formats designed to complement the viewing experience rather than interrupt it. Pause ads, interactive units, content hubs, and contextual sponsorships are gaining traction as advertisers look for ways to capture attention without increasing ad load.
Audience behavior is reinforcing this shift, with viewers increasingly multitasking while streaming, thereby creating demand for formats that invite engagement rather than passive exposure. Interactive CTV ads are emerging as one response: More than 40% of US marketers already use interactive features across social and CTV, and over half expect interactive elements to account for at least a quarter of their ads. Early performance signals suggest these formats can deliver meaningful lift, including higher unaided recall and stronger brand affinity, when aligned with content and context.
As CTV inventory continues to fragment across platforms and environments, new formats have in turn created new operational challenges. The absence of universal CTV standards has created significant variability in how ads are served, measured, and experienced, increasing the need for structure and visibility as experimentation accelerates. Programmatic activation—supported by a unified, omnichannel platform—provides a framework for testing emerging formats with guardrails, allowing advertisers to compare performance, manage frequency, and maintain consistency across placements. In 2026, advertisers that pair creative experimentation with programmatic discipline will be better positioned as CTV shifts from a reach-first channel to a more interactive, performance-aware component of the media mix.
Across all these channels and formats, a common thread emerges: the need for greater control over where ads appear and how budgets are deployed.
Programmatic advertising has long been synonymous with scale. Yet as programmatic investment continues to climb, so does scrutiny around media quality and working spend. Leaders are increasingly expected to defend not just performance, but also the transparency and quality of the media supply chain. In 2025, inefficiencies and waste in programmatic spend were estimated to total about $26.8 billion globally, underscoring the gap between dollars invested and working media outcomes.
Curated inventory packages give advertisers more visibility into where ads appear and how supply paths function, helping reduce inefficiencies and improve confidence in campaign outcomes. Curation has gained traction as marketers seek stronger alignment between media quality and performance, with 41% citing curated deals as a path to higher ROI. DSPs and SSPs are responding by expanding tools that support flexible deal structures and clearer supply chain insight.
The open exchange remains an important source of reach, but in 2026, it is increasingly paired with curated strategies that bring added control. Together, they enable advertisers to pursue growth without compromising trust.
The trends shaping programmatic advertising in 2026 reflect a steady recalibration (rather than a dramatic reset). As budgets continue to grow and scrutiny intensifies, advertisers are moving away from volume-driven approaches and toward strategies that prioritize quality, accountability, and adaptability. The shift is visible across the programmatic ecosystem—from consolidated data foundations and stronger media quality guardrails to evolving commerce media, changing discovery and video environments, and curated supply paths.
What connects these shifts is the rising importance of integration. Disconnected channels, formats, and signals require systems and operating models that support consistent decision-making across planning, activation, and measurement. As automation becomes more embedded in programmatic workflows, human oversight will become less focused on manual execution and more centered on governance, interpretation, and long-term value creation.
In 2026, advertisers that pair thoughtful experimentation with clear guardrails, maintain transparency as strategies evolve, and combine automation with human expertise will be best positioned to evaluate performance, defend investment decisions, and sustain growth amidst ongoing change.
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Looking for more insights into the major innovations and opportunities to watch this year? Our 2026 Trends Report: Rewinding to Fast Forward provides real perspective on the key trends that are poised to shape the year ahead.
Do marketing leaders ever really get a winter break? You’re supposed to be relaxing, but your brain won’t cooperate. You’re thinking about Q1 budgets while waiting for your flight. Mentally drafting your board presentation while the family watches a holiday movie. Lying awake in the wee hours of the morning running through 2026 talent considerations.
We’ve curated this reading list specifically for the realities of the holidays, matching key resources to those moments when you might have a few minutes to yourself. Whether you’re feeling inspired or just need a break from that one relative (you know the one…), these reads can help you start the new year informed and energized.
And if you only get through a couple of paragraphs before you’re called away to a snowball fight? We’ll call that a win.
Ah, the joys of holiday travel. You’ve been gifted a couple of extra hours in everyone’s favorite place: A crowded airport. Instead of spending it all on retail therapy at the duty-free shop, why not invest a few of those minutes in building up your industry smarts? This article provides an in-depth look at how the CMO role is transforming, how CMOs can set themselves up for success, and why brands that embrace these changes are best positioned to unlock their full potential.
The house is finally quiet, everyone’s asleep, and you’re wide awake staring at the ceiling. When work anxiety strikes in the middle of the night, it helps to know that many of your biggest challenges share a common denominator (address it, and you can alleviate multiple problems at once!). This article connects major challenges around proving ROI, AI adoption, talent efficiency and retention, and more back to data problems, and outlines practical steps marketing leaders can take to address them at their source.
Your aunt has had a bit too much eggnog, and she’s finally revealed the secret to everyone’s favorite holiday cookies: Real, high-quality vanilla extract. It has you thinking about other things that require quality inputs to generate quality outputs—AI, for instance. This article explores how marketing teams can get around barriers to AI adoption and drive ROI by improving their data readiness. While holiday cookies can still taste decent with artificial vanilla, AI tools simply can’t function without clean, unified, high-quality data.
Everyone has an opinion about AI, and when the topic comes up at the holiday party, you know that you’ll be expected to offer an authoritative take. This report provides the exclusive, data-based insights you need to sound like an expert, even if holiday brain fog has temporarily eclipsed your expertise. More importantly, you’ll gain a deeper understanding of how your peers are approaching AI adoption, the efficiency gains they’re seeing, the risks they’re most concerned about, and more.
You’re driving home from the holiday party, and that AI conversation is still rattling around in your mind. Have you done enough to optimize your team for an increasingly AI-driven future? This report provides exclusive data and actionable recommendations for navigating the AI revolution from a talent perspective in 2026. It’ll transform those anxious questions into ideas to fuel your tech and talent strategies next year.
Sometimes, sitting alone at the local pizza place waiting for your order provides the greatest holiday gift of all: A few precious minutes alone. This brief read offers expert guidance around one of marketing’s biggest debates—how to strike the right balance between performance and brand investments—with a particular focus on achieving that balance amidst economic uncertainty. You’ll arrive home not only with dinner, but with fresh insights for leading your business through volatility.
With the stress of Q4 2025 still fresh in your mind, you may be resolving to do things a bit differently in 2026—if only for the sake of your future self’s blood pressure. It’s a good call, as earning executive buy-in during budget season is considerably easier when you’ve been nurturing cross-departmental alignment and goodwill throughout the year. This article, written by Basis CMO Katie McAdams, outlines how marketing leaders can find more success securing C-suite backing by working to build trust with executives year-round. Her recommendations work in any economic climate, but are especially valuable when budgets are tight.
Well, there you have it: You just made smart use of the odd pockets of solitude that winter break provides. Made it through everything? Great. Only got through half of one article? Still counts. Either way, you’re heading into 2026 sharper and more informed than you were before.
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Looking for one more resource to round out your winter break reading? Check out Rewinding to Fast Forward: The 2026 Digital Advertising Trends Report for an in-depth look at four key forces shaping the year ahead for brands.
Three industry veterans discuss the trends every advertiser should understand heading into 2026, including the crisis of programmatic waste, the rise of agentic AI, and the growing importance of consumer trust.
Key Takeaways:
1. Media quality must become a strategic priority: With only 36 cents of every programmatic dollar reaching publishers, it’s critical for advertisers to invest in verification tools and transparent supply paths to deliver real effectiveness.
2. CTV "premium" inventory requires scrutiny and validation: CTV inventory quality often falls short of advertiser expectations, requiring more rigorous evaluation and ongoing monitoring throughout campaigns.
3. Agentic AI adoption demands careful experimentation: As AI evolves from assistive to autonomous, marketers should start with small pilots, invest in their teams’ prompting skills, and prioritize enterprise tools that protect intellectual property.
4. Trust-building requires continuous strategic investment: With trust now as important as price and quality in purchase decisions, brands must leverage customer evangelists, maintain authentic creative, place ads in trusted environments, and use diverse measurement approaches to track results.
From AI breakthroughs to the proliferation of retail media networks to significant industry consolidation through M&A activity, 2025 brought transformative shifts that forced advertisers to rethink their strategies.
To explore how these shifts may impact brands and agencies in 2026, we brought together three industry veterans to share their insights and predictions. Their discussion spanned the challenges of supply chain transparency, the complexities of CTV inventory quality, the practical implications of agentic AI adoption, and the strategies brands are using to build authentic consumer trust—all critical trends that every advertiser should understand heading into 2026.
Editor’s note: This conversation has been edited for length and clarity.
Programmatic advertising waste has reached crisis levels, with only 36 cents of every dollar reaching consumers while the rest disappears into opaque fees and intermediaries. What does it look like when advertisers treat media quality as a strategic imperative rather than a nice-to-have?
April Weeks | Chief Investment & Media Officer, Basis: First, it looks like advertisers safeguarding the media quality of their buys by partnering with media quality and brand safety verification vendors like Peer39, DoubleVerify, and IAS. It’s easy for brands to avoid paying for those when they sound like they’re “extras.” But when they’re not included, low value inventory seeps in.
Like most things in life, you get what you pay for. When advertisers don’t take measures to protect their spend, they’re trading efficiency for effectiveness. Personally, I place less value on how efficient a buy was—I care about how effective it was. When you chase the efficiency game with low CPMs, you sacrifice high-quality inventory and the effectiveness needed to drive real outcomes.
Grace Briscoe | EVP of Client Development, Basis: This is one of those areas where advertisers can make the mistake of valuing and measuring the wrong metrics. If you focus on maintaining low CPMs or a low cost per click rather than on the outcomes your media plan is driving, you’re going to end up spending on lower quality, cheaper inventory.
Katie McAdams | Chief Marketing Officer, Basis: Those short-term vanity metrics can look really good from an efficiency standpoint. But in the long term, you’re trading effectiveness for efficiency.
GB: I also think it’s important for advertisers to get really clear about what they consider to be premium inventory. I’ve grown to kind of hate the word “premium”, because if you ask five different advertisers to define it, you’re going to get five different answers. It’s not an objective standardized term. It’s an opinion.
Take, for example, some brands avoiding news content. There’s this knee-jerk reaction to block all news because advertisers don’t want to show up near anything negative. But I would consider journalistic news content to be premium, and when advertisers avoid it, I think it continues a cycle of defunding quality content. And that hurts the whole ecosystem in the long run.
AW: I completely agree. Gaming is another great example of both a channel and content that’s easy to stereotype. There’s this idea that gaming only reaches teenage boys sitting in their basements, but that’s not the case at all. If you look at the research and the audience data, a lot of women and high-income households are engaging with gaming content and platforms regularly. So another essential part of the story here is the importance of taking an informed and data-driven approach to how you’re defining inventory, rather than making assumptions.
KM: I think similar assumptions can lead advertisers down the wrong path when it comes to connecting with diverse audiences. Buyers tend to assume that general audience inventory is going to give them spillover into diverse audiences, but that’s often not the case. They need to tap into the supply networks that truly represent the publishers where those audiences spend time.
AW: That’s right, and it's a critical point at a time when the economic impact of diverse audiences continues to increase. The best way to reach diverse audiences is to take an authentic community approach, tapping into specific inventory sources that curate high-quality content that actually resonates and is specific to those audiences.
Speaking of “premium,” that label has largely lost its meaning across CTV, as advertisers paying for inventory on major streaming platforms often end up with ads running on long-tail apps and user-generated content. Considering that “premium” no longer guarantees quality in CTV, how are leading advertisers adapting their CTV strategies?
GB: Again, I think it’s important to note that premium is in the eye of the beholder. When it comes to streaming TV, does inventory qualify as “premium” because of its production value? Because it’s sold by a major streaming service? Or is it about the ad load of how many ads are shown within that content?
I do think we’re seeing brands demand more transparency—particularly in the CTV space— because there are a lot of players in the marketplace operating as black boxes and offering opaque bundles. Often when you start to unpack those bundles, you realize that the “CTV inventory” you purchased actually had a lot of mobile video or other online video mixed in.
There are ways to tell when inventory isn’t premium, though. If the CPM seems too good to be true, then it probably is—you’re not getting ESPN for a sub-$30 CPM. So it’s important for advertisers to evaluate those kinds of signals critically.
KM: It’s also critical for advertisers to check in on their campaigns midstream. That’s when you can validate if your ads are really landing where you placed them and make changes if needed.
GB: Right. Some of that also has to do with how clean the supply path is and maximizing how much of your spend is going as directly as possible to publishers with as few middlemen as possible. The more you tap into aggregators and resellers, the less transparency you have, and the quality starts to go downhill as well.
AW: That ties into the dialogue around the value of curation. With curation, you’re adding another middleman to the supply chain. Curation partners are supposed to filter, bundle, and curate high-quality inventory that delivers access to valuable audiences in premium environments. But is that worth the additional cut they take? These are the questions advertisers have to ask themselves: what’s the value, and is it worth the additional cost and supply chain complexity? The best way to know is to test and learn—understand the potential lift in performance vs. the cost trade-offs by implementing curation.
I would also note that the inclusion of ACR (or automatic content recognition) data, and overlaying ACR data from a reporting standpoint, provides an additional level of granularity around placements, which can help validate you’re getting the quality you want.
GB: ACR also gives you a lot more visibility—for example, frequency of ads per household and the incremental reach. If you’re buying, say, linear TV as well as CTV, then ACR allows you to see how much of the audience is unique versus overlap and duplication. You might see that certain viewers were exposed to an ad on NBC news on linear TV, but also got impressions from Tubi on CTV. Then you can start to optimize on that information— perhaps reallocating budget because it might be a much more effective CPM to reach those viewers on Tubi than it is on primetime linear TV.
AW: And ACR can also help by showing when you’re burning impressions against the same audience.
There are some other important considerations when it comes to targeting and addressability as well. We know there’s often a high, high degree of inaccuracy with IP-based targeting. Considering that, using first-party data and deterministic data layered into buys is a good strategy to increase the integrity of your TV targeting.
Deterministic data—which could be something like user verified login data—is the most precise data advertisers can use for targeting. Probabilistic data, on the other hand, is modeled data inferred from deterministic data, which means that it’s less accurate. It's really important for advertisers to understand these different types of data, because many platforms claim that they can offer addressability, but the accuracy of that addressability varies significantly based on the kind of data powering it.
Agentic AI is poised to fundamentally transform marketing operations, evolving AI from assistive technology into autonomous systems capable of executing complex, multi-step tasks independently. What lessons from the rise of generative AI and the industry’s approach to adopting those AI tools can help marketers more effectively adopt agentic AI?
AW: One thing I would say is that many of the use cases for both gen AI and agentic AI are undefined. Because of that, it’s important for marketers to be open and curious about exploring different possible use cases.
Additionally, my belief is that AI—whether it be generative or agentic—is becoming an overused and almost abused term. You have to ask questions, because there are a lot of companies claiming to have AI solutions where, when you pull back the layers, the tools are actually very clunky, not well developed, and may not be true AI tools.
KM: That all rings very true with my team’s experience as well. As advertisers start testing agentic AI, I’d recommend starting with very small pilots. It takes time to build confidence and trust that an agentic AI tool is going to be able to, for example, capably represent your brand or market it in the same way that you’d expect an employee to. That trust is only going to come with time and testing and learning. That's why it's best to start with a small, controlled test where you're comfortable with some margin of error.
GB: I’d also recommend that advertisers keep in mind that generative AI and agentic AI are both tools that are still very much people-powered, and the outputs are only as good as the inputs. I think of these AI tools as interfaces between human thinking and computational superpower.
KM: Yes—to build upon what Grace is saying, humans should be questioning all the responses they receive from AI tools. You need to continually question and test the narrative they’re creating for you. And, to Grace’s point about AI tools being people-powered, that drives home the importance of having skilled prompters. It’s really important to invest in those skills among your team.
Personally, I’ve also seen a lot of progression and improvement in enterprise AI tools like Copilot. I think we’re going to see those enterprise tools grow to be more on par with the other major tools, and we may see companies mandating that their employees only use those pre-approved enterprise tools as they seek to protect their IP.
AW: Agreed. The way these enterprise tools can store and process so much of a company’s data and information really unlocks a lot of use cases that people may have previously been hesitant about, because they were concerned with data privacy and security.
GB: That brings to mind some of the concerns I've heard from several brands and marketers: If we're all using the same generative or agentic AI tools for creative purposes, are all our ads going to look the same? How do you ensure that your brand's identity and integrity and data stay yours and don't get diluted or distributed? Enterprise tools offer solutions for some of those concerns, but there are still a lot of unanswered questions.
New studies show that trust has emerged as equally important to price and quality in consumer purchase decisions. At the same time, in an era marked by cultural volatility, social fragmentation, and widespread consumer distrust, earning trust represents a significant challenge for many brands. How are brands incorporating trust into their marketing strategies and assessing the success of their efforts?
AW: One thought I have is around the role of influencers within marketing. Research shows that recommendations from family, friends, and trusted influencers can have a greater influence in terms of building trust for the brand than traditional advertising. That impact varies among categories, but for many brands, a strategy around building trust may look like reevaluating how they leverage brand ambassadors and influencer marketing.
KM: I agree. To extend that into the world of B2B, brands really need to invest in things like customer marketing and look at their customer evangelists as their best marketing tool. Ultimately, people are going to have more trust in a brand if they are hearing good things from someone who’s actually a customer. That’s always going to feel more authentic than what a brand says about themselves. The goal is to build a system where word of mouth is consistently generating leads.
Another critical piece of trust-building is authenticity when it comes to your ads and your creative. Going back to AI, brands need to use generative AI in a way where they’re still creating things that look and feel authentic to their brand.
And then, lastly, this also connects back to our conversation around media quality. When consumers see ads in trusted environments, in context of trusted content, that’s going to further brand trust. On the flip side, seeing the same ad run on an MFA site creates a poor user experience, which impacts how people perceive and feel about the brand.
AW: Yes, 100%. When it comes to measuring trust in a certain brand, social listening comes to mind as one good way for advertisers to get a baseline of consumer sentiment around a brand. Brand studies are another solid option.
GB: There’s no silver bullet that’s going to give you a full picture, so advertisers need to leverage a variety of different approaches to get an accurate read on consumer sentiment—a combination of social listening, customer reviews, customer surveys, brand lift studies, maybe a brand index study, et cetera. Using only one of those lenses to assess consumer trust will likely give advertisers a skewed view, so it’s important to embrace a healthy mix of approaches.
KM: It's really about identifying all the touchpoints where customers interact with or talk about your brand, then figuring out how to collect and analyze that information holistically.
AW: I would also add there’s a benefit in widening the aperture and looking not just at your own brand, but what’s happening in your sector more broadly. For example, if there’s a particularly high level of consumer distrust in your sector, what opportunities does that open for your brand to rethink their positioning to gain trust?
GB: One last recommendation: To build brand trust, brand marketing needs to be continuous. As soon as you disinvest in that, your customer base will erode over time.
KM: This all goes back to the effectiveness vs. efficiency play that we were talking about at the beginning.
GB: Full circle.
AW: Full circle!
It's critical for leaders at agencies and brands to nurture a thorough understanding of how these four trends are likely to develop over the next year. Check out Rewinding to Fast Forward: The 2026 Digital Advertising Trends Report for more insights advertisers can use to gain a competitive edge in 2026.
Between holiday travel, endless leftovers, and the annual rite of forgetting what day it is, the end of the year can be a bit of a blur. Yet it can also offer a rare pocket of breathing room, allowing agency leaders to step back from the daily rush and think about the bigger shifts shaping the future of the advertising industry. With AI accelerating, data fragmenting, and client expectations rising, leaders are heading into 2026 with more complexity to manage—but more opportunity to capture as well.
This winter break reading list highlights many of the themes defining the next chapter of agency work: operational clarity, AI readiness, unified data, and stronger strategic partnerships. For your convenience, we've grouped the reads by the moments that tend to emerge during winter break—planned or otherwise. When you find a few minutes to yourself, this list is ready for you. And if you need a reason to hide in the guest room for twenty minutes, you’re welcome.
You’ve heard, “So what exactly is it you do again?” one too many times and need a few minutes to yourself. Instead of scrolling mindlessly, why not escape into the world of strategy, leadership, and the future of agency work?
Agencies are being asked to do more with less while navigating shifting client demands, agentic AI, and an increasingly complex media environment. Here, gain expert perspectives on the pressures driving change and the strategic choices leaders must make in response. Topics include how to balance profitability with investment in talent, how to integrate AI without losing the human touch, and how to sharpen strategic focus instead of trying to do everything for everyone. Consider it your guide to what will separate future-ready agencies from the rest.
With budgets tightening and client expectations rising, agencies are navigating an increasingly challenging landscape. This piece outlines how tech-driven efficiency can help stabilize teams, strengthen client relationships, and protect margins amidst economic pressure. It also highlights why integrated systems and automation are becoming essential for agency resilience and provides practical guidance on using technology to maintain performance and drive long-term growth.
If the departures board has betrayed you, dive into the pieces that show how consolidation and smarter systems can restore a sense of order—at least to your data.
With more tools, more channels, and more platforms, advertisers are struggling to achieve a holistic view of performance. This presents a major barrier to agency teams, especially in the context of the rising pressure to prove impact. This article breaks down how disconnected data and tech sprawl fuel operational inefficiencies and limit teams’ ability to adapt quickly. It also explores how consolidating data into one source of truth strengthens reporting, improves optimization, and unlocks the full value of AI-driven tools. For leaders navigating complexity, it offers a clear case for why consolidation is both a strategic and operational imperative.
From media fragmentation to revenue pressure to stalled AI initiatives, many of marketing leaders’ toughest challenges share a common source: poor data foundations. This article unpacks how inconsistent, siloed, or overwhelming amounts of data complicate decision-making, weaken storytelling, strain teams, and limit the impact of new technology. It also outlines practical steps leaders can take to consolidate insights, strengthen visibility, and unlock more strategic value across operations.
Perfect for a quiet morning with coffee or a rare uninterrupted afternoon, these pieces zoom out to help you see the industry with a fresh perspective.
This year’s Advertising Agency Report captures a sector in transition, with teams grappling with increasingly fragmented workflows, tougher client demands, and heightened brand safety risks. The report uses data to outline the most urgent challenges agencies are facing, as well as the strategic investments leaders plan to make next—especially around AI and operational efficiency. If you’re short on time, catch the executive summary here.
Brand-agency relationships are shifting fast, and the gap between how agencies think they’re performing and how brands grade their performance is significant. This piece breaks down why that gap exists, how tech and media complexity are reshaping expectations, and what agency leaders can do to strengthen client trust and demonstrate their value.
For easing from vacation mode into the new year, these pieces provide a gentle reentry into operational discipline, efficiency, and the systems that help teams thrive.
Pitching remains essential for agency growth, yet it’s become increasingly complex and costly. With clients demanding faster turnarounds and more operational transparency, agencies must show not only strong ideas but the systems that enable them. This piece breaks down how tech maturity, unified data, and AI readiness can ease the burden on teams while strengthening pitch performance. It offers a clear view into how agencies can modernize their approach to win business in a more competitive market.
From privacy shifts to brand safety concerns to a sprawling tech ecosystem, agencies are feeling the weight of growing complexity. This article argues that improving efficiency is the key to cutting through complexity and helping agencies work faster, drive better performance, and strengthen client relationships. It breaks down the risks created by disconnected systems, manual processes, and underutilized AI, and highlights how streamlined systems and automation can simplify operations and strengthen client relationships.
As the year winds down, consider this reading list your invitation to recharge, recalibrate, and head into 2026 with a clearer view of what matters. And if diving into any of these articles gives you an excuse to procrastinate packing your suitcase? Even better.
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Looking for more insights to inform your 2026 planning? Rewinding to Fast Forward: The 2026 Digital Advertising Trends Report provides perspective on four key topics that will influence how advertisers work next year. Get your copy now and uncover the trends and opportunities that will shape 2026 for advertisers.
