Connected TV has officially taken the lead—and it’s rewriting the rules of media buying. As streaming surpassed broadcast and cable combined for the first time in 2025, advertisers are facing a tougher challenge than ever: how to reach audiences whose attention is fragmented across apps, screens, and formats.

Nexxen (NASDAQ: NEXN) and independent agency H/L believe they have an answer. By pairing Nexxen’s demand-side platform (DSP) and advanced data insights with H/L’s performance-driven media strategy, the partners report up to a 14x lift in conversion outcomes for clients across multiple verticals. The results highlight a broader shift underway in CTV—from reach-first buying to signal-backed, outcome-oriented execution.

Streaming Wins, Attention Fragments

The backdrop to this partnership is a historic inflection point. In 2025, streaming accounted for 44.8% of total TV usage, overtaking broadcast and cable combined for the first time. At the same time, free ad-supported streaming TV (FAST) channels are surging, with monthly viewership up roughly 12% year over year and session lengths continuing to grow.

For advertisers, that growth is a double-edged sword. CTV now offers access to highly engaged audiences—but those audiences are scattered across platforms, apps, and content types. Add in second-screen behavior, and the old playbook of broad, undifferentiated media buys starts to fall apart.

The implication is clear: attention, not impressions, is the scarce resource.

From CPMs to Cost-Per-Unique Reach

H/L’s approach with Nexxen reflects this reality. Instead of optimizing around traditional CPMs, the agency has shifted focus to cost-per-unique reach, blended frequency management by app, and optimization tied directly to down-funnel business outcomes.

“At H/L, we’ve strategically embraced this evolving CTV landscape,” said Jeremy Cobb, Vice President of Digital Platforms at H/L. “By tapping into Nexxen’s advanced insights, we’ve crafted a strategy that blends premium inventories and custom placements for initial viewer activation, with cost-effective long-tail.”

That balance matters. Premium placements help capture attention early, while long-tail inventory extends reach efficiently—without oversaturating the same viewers. The result is frequency discipline in a medium where overexposure is increasingly easy and increasingly expensive.

Measurable Results, Not Just Promising Signals

The payoff has been tangible. For H/L’s clients in sectors like automotive and insurance, these signal-backed strategies have driven up to fourteen times higher conversion outcomes compared with more traditional CTV programs.

Crucially, those gains weren’t self-attributed. They were validated by Marketing Mix Modeling (MMM) partners, giving advertisers greater confidence that CTV isn’t just delivering awareness—but measurable performance.

This kind of validation is becoming table stakes as CFOs scrutinize media spend more closely and demand proof that CTV can compete with, or complement, lower-funnel digital channels.

Nexxen’s Bet: Know Who’s Actually Watching

Nexxen’s role in this equation centers on insight density and execution speed. Its DSP combines buying capabilities with supply-side intelligence, allowing advertisers to understand not just where ads appear, but what content viewers are actively engaged with.

“Navigating the new CTV landscape requires knowing who’s truly paying attention and managing ad frequency with precision,” said Kara Puccinelli, Chief Customer Officer at Nexxen. “That’s why agencies are leaning into advanced measurement, balancing high-attention placements with cost-efficient reach.”

Rather than treating CTV inventory as interchangeable, Nexxen emphasizes contextual and engagement signals—an approach that aligns with how advertisers now evaluate performance in a multi-screen world.

Publishers Lean In With Smarter Supply

The push toward signal-backed buying isn’t limited to DSPs and agencies. Media owners are also adapting, surfacing richer data and more flexible formats to help buyers transact more intelligently.

Platforms like Philo and DIRECTV Advertising are working with Nexxen to expose high-value inventory—particularly in premium and live content—paired with granular audience and contextual signals.

“CTV remains one of the most impactful ways to connect with audiences, particularly while watching content they’re passionate about,” said Aulden Kaye Yi, Head of Advertising Partnerships at Philo. “Working with Nexxen allows us to surface our inventory with granular audience and contextual signaling.”

That capability becomes even more important as live sports continues its migration to CTV, a trend DIRECTV Advertising is actively capitalizing on.

“As live sports programming continues to shift to CTV, Nexxen allows us to surface and package this high-value ad inventory with contextual and audience data signals,” said Edmund Jules, Senior Director of Ad Sales Partnerships at DIRECTV Advertising.

Why This Matters for Advertisers Now

The Nexxen–H/L results point to a broader industry lesson: CTV performance hinges less on scale and more on signal quality.

As streaming dominates viewing time, advertisers can no longer afford to treat CTV as a blunt instrument. Success depends on:

• Understanding where attention is concentrated

• Managing frequency with discipline across apps

• Optimizing toward outcomes, not just exposure

In that sense, CTV is starting to look less like traditional TV and more like performance media—with all the accountability that implies.

The Bigger Takeaway

CTV’s growth story is no longer about adoption—it’s about execution. As the market matures, the winners will be those who can navigate fragmentation with precision, not those who simply buy more impressions.

The partnership between Nexxen and H/L shows what’s possible when advanced data, flexible buying, and outcome-driven strategy converge. In a world where attention is splintered and budgets are scrutinized, a reported 14x lift in conversions is more than a case study—it’s a signpost for where CTV buying is headed next.

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Artificial intelligence is now deeply embedded in everyday marketing workflows—but new research suggests accuracy hasn’t kept pace with adoption.

According to NP Digital’s AI Hallucinations and Accuracy Report, AI-generated errors are not only common, they’re increasingly slipping into live campaigns. Nearly half of marketers (47.1%) encounter AI inaccuracies several times per week, and 36.5% report that hallucinated or incorrect AI content has already gone public.

The findings underscore a growing tension in modern marketing: AI delivers speed and scale, but without sufficient oversight, that efficiency can introduce serious brand risk.

AI Errors Are Frequent—and Time-Consuming

The report combines two data sources:

• An accuracy analysis of 600 prompts tested across six major large language models (LLMs), including ChatGPT, Claude, and Gemini

• A survey of 565 U.S.-based digital marketers

Together, the data paints a picture of widespread friction between AI output and real-world accuracy.

More than 70% of marketers say they spend one to five hours each week fact-checking AI-generated content, eroding some of the productivity gains AI is supposed to deliver. Despite this effort, errors still escape into production.

“AI has become an incredible tool to accelerate efficiencies, but speed without accuracy creates real risk,” said Chad Gilbert, Vice President of Content at NP Digital. “What makes AI hallucinations especially dangerous is that many of them look believable at first glance.”

When AI Mistakes Go Live

Among marketers who reported publishing inaccurate AI-generated content, the most common issues included:

• False or fabricated facts

• Broken or nonexistent citations

• Brand-unsafe or misleading language

These errors often appear polished and confident, making them harder to detect without careful review. Once published, they can damage credibility, confuse audiences, or expose brands to compliance and reputational risks.

Yet despite these dangers, 23% of marketers say they are comfortable using AI output without human review, a gap between awareness and behavior that the report flags as particularly concerning.

No Model Is Error-Free

NP Digital’s accuracy testing also evaluated how different LLMs perform under scrutiny.

• ChatGPT delivered the highest rate of fully correct responses at 59.7%

• No model consistently avoided hallucinations

• Error rates increased sharply for:

  • Multi-part questions

  • Niche or specialized topics

  • Real-time or time-sensitive queries

The most common hallucination types across all models included:

• Omissions

• Outdated information

• Fabrication

• Misclassification

Crucially, these errors were often delivered with high confidence—making them more persuasive and more dangerous.

Where AI Breaks Down Most Often

The report found that AI struggles most with tasks requiring precision, structure, or technical rigor, including:

• HTML or schema creation

• Full long-form content development

• Reporting and data-driven summaries

These are also the areas where marketers are most likely to trust AI to “just handle it,” increasing the likelihood of mistakes slipping through.

The Real Takeaway: AI Needs Guardrails

The data points to a clear conclusion: AI works best as an assistant, not an authority.

Strong prompts, defined review processes, and human oversight consistently reduce risk. With no single LLM emerging as reliably accurate across use cases, marketers can’t solve the hallucination problem by switching tools alone.

Instead, the report reinforces a mindset shift:

• Treat AI output as a draft, not a final answer

• Match AI tasks to its strengths, not its hype

• Keep humans accountable for what goes live

As AI becomes standard infrastructure in marketing, accuracy—not speed—may be the new competitive advantage.

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The Shelf, a performance-first influencer marketing agency, has earned multiple top industry honors in 2025, reinforcing its position at the intersection of creator-led storytelling and measurable growth.

The agency was named Best Activation in Support of Sustainability at the Adweek Experiential Awards for its work with Natura, and received finalist recognition at the Drum Awards in Retail & Consumer Products for its campaign with Weekday, as well as for Micro-Influencer Campaigns with Gregory Mountain Products. The Shelf also earned a Platinum MarCom Award for its work with Self Financial.

Together, these accolades reflect more than creative excellence. They point to a structural shift underway in performance marketing—one in which creative has become the primary driver of optimization, learning, and scale.

When Targeting Fades, Creative Becomes the Signal

Major platform changes over the past year have fundamentally altered how performance is generated. With automated campaign structures expanding and granular targeting controls shrinking, platforms increasingly rely on creative behavior signals—how content is watched, saved, shared, and engaged with—to determine delivery and scale.

Updates like Meta’s Andromeda have accelerated this shift. As deterministic targeting weakens, platforms can only optimize against what creative reveals in real time. In this environment, creative is no longer just a message—it is the feedback loop.

Many brands have responded by increasing content volume, assuming scale would offset the loss of control. But results have often remained inconsistent. According to The Shelf, the issue isn’t quantity—it’s structure.

Without systems designed to test, interpret, and compound creative insight quickly, content fails to generate durable performance signals.

A System Built for Signal, Not Just Output

The Shelf’s operating model was designed for this reality before platforms forced the shift.

Rather than starting with creators or deliverables, the agency begins with social listening and market intelligence, mapping interest clusters that reveal how audiences actually think, speak, and make decisions. These insights shape creator selection, briefing, and narrative design—aligning brands with creators embedded in relevant, interest-based communities.

From there, creative variations are tested rapidly to surface early engagement signals—such as saves, shares, and watch time—that indicate downstream performance potential. Winning narratives are scaled, while underperforming ones are iterated or retired.

Creative is treated as a source of intelligence, not just an output.

Repeatable Performance at Scale

That systemized approach has delivered consistent results across categories and regions.

Over the past year, The Shelf reports:

• Sustained ROAS across multiple U.S. and European markets for fashion and retail brands

• More than 40 million organic impressions driven by creator-led campaigns at retail scale

• Performance lifts through iterative optimization, including ROAS up to 23x during peak seasonal windows, with efficiency sustained in the weeks that followed

Early engagement signals proved to be reliable predictors of downstream efficiency, allowing platforms to learn faster and scale more effectively.

“These platform changes didn’t make marketing harder, they made weak systems visible,” said Atul Singh, Co-Founder and CEO of The Shelf. “When targeting control fades, the only thing platforms can optimize against is signal. If your creative can’t generate meaningful signal, the platform can’t learn from you. We built our model to turn creative into intelligence long before platforms forced that shift.”

Structure Becomes the Advantage

As performance marketing becomes creative-led by design, the competitive advantage is no longer who produces the most content—but who learns the fastest.

In an environment where platforms optimize behavior, the brands that win will be those with systems built to:

• Identify the right creators

• Pair them with insight-driven narratives

• Interpret performance signals in motion

In that future, scale follows structure—not the other way around.

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Marketing AI is everywhere right now—but in healthcare and life sciences, “everywhere” often means “nowhere useful.” Between regulatory hurdles, fragmented data, and long approval cycles, most off-the-shelf AI tools struggle to move beyond surface-level productivity gains.

Supreme Group thinks it has an answer.

Today, the healthcare-focused marketing and communications agency announced Supreme Intelligence, a proprietary Artificial Intelligence Platform (AIP) purpose-built for the commercial realities of life sciences and healthcare companies. Rather than bolting AI onto existing workflows, Supreme Intelligence aims to rewire how campaigns are planned, created, approved, and optimized—without breaking compliance.

It’s a bold claim in a crowded AI market. But Supreme Group is betting that deep domain expertise—and not just better models—will be the real differentiator.

A New Kind of AI Platform, Not Another Chatbot

Supreme Intelligence is positioned as an end-to-end platform rather than a collection of AI features. The company says it unifies proprietary data, analytics, and healthcare-specific insights into a single, secure environment that agency teams and clients can use across the entire marketing lifecycle.

That lifecycle spans everything from early strategy and messaging development to medical, legal, and regulatory (MLR) review, activation, and performance measurement.

Unlike general-purpose AI tools that excel at narrow tasks—copywriting, summarization, or data analysis—Supreme Intelligence is designed to operate as a connected system. The idea is to reduce friction between steps that are traditionally siloed and slow, especially in regulated industries.

“We built Supreme Intelligence leveraging our life sciences and healthcare domain expertise to drive maximum commercial impact,” said Sheldon Zhai, Founder and Chief AI Officer at Supreme Group. According to Zhai, that domain-first approach is what makes the platform adaptable enough to be considered “a fundamentally new class of AI platforms.”

Supreme Group claims early deployments are already delivering 10x improvements in campaign speed, quality, and performance outcomes, powered by adoption across more than 350 subject matter experts, including over 55 PhDs.

Why Healthcare Marketing Is Ripe for Specialized AI

Healthcare and life sciences marketing sits at the intersection of high stakes and high friction. Campaigns must be accurate, compliant, and evidence-based—while still competing for attention in an increasingly digital-first world.

This tension has created a gap between what modern AI can do and what regulated organizations feel safe deploying. Many companies experiment with AI in isolated pilots, but few scale it across strategy, production, and measurement.

Supreme Intelligence is clearly designed to close that gap.

By embedding regulatory considerations, approval workflows, and privacy protections directly into the platform, Supreme Group is positioning AI not as a risk—but as infrastructure.

“Our fundamental promise to our clients is to solve complex business problems,” said Tom Donnelly, CEO of Supreme Group. “We developed Supreme Intelligence to fulfill that promise more effectively.”

That framing matters. In healthcare marketing, speed alone isn’t enough; trust and auditability are equally critical.

Persona-Driven Strategy: Testing Before You Launch

One of the platform’s standout capabilities is persona-driven strategy simulation. Instead of relying solely on static personas or historical assumptions, teams can deploy trained AI personas—such as a “Director of Clinical Development” or “Head of Cardiology”—to test how messaging might land before a campaign goes live.

These personas are grounded in Supreme Group’s proprietary research and industry data, allowing marketers to simulate reactions, objections, and preferences in a controlled environment.

This approach reflects a broader industry shift toward pre-launch experimentation. As budgets tighten and timelines compress, brands are looking for ways to de-risk campaigns earlier in the process. AI-powered persona testing could offer a faster, cheaper alternative to traditional market research—especially for early-stage messaging decisions.

If it works as advertised, it could change how healthcare marketers think about validation and iteration.

From “Chat” to Production-Ready Content

Content generation is where most marketers first encounter AI—but it’s also where regulated industries hit the hardest limits. Generating compliant, brand-safe, production-ready assets is a very different challenge from drafting a clever headline.

Supreme Intelligence aims to bridge that gap.

The platform supports custom workflow applications that generate assets at scale—ranging from regionalized digital campaigns to email templates—while enforcing brand guidelines, regulatory constraints, and approval requirements.

Rather than producing raw text that still needs heavy human cleanup, Supreme Group says the system is designed to output content that’s ready for real-world deployment.

That’s a significant promise. In healthcare marketing, even small compliance errors can delay campaigns by weeks. Automating guardrails, rather than relying on post-hoc review, could materially change throughput.

Dynamic Orchestration Under the Hood

A quieter—but potentially more important—feature of Supreme Intelligence is its dynamic orchestration layer.

Instead of locking teams into a single AI model or vendor, the platform automatically curates and integrates the best-performing models for each task. That could mean one model for real-time data analysis, another for content generation, and a different one for regulatory checks.

This model-agnostic approach reflects a growing realization in enterprise AI: the fastest-moving innovation isn’t in platforms, but in models. By abstracting model selection away from end users, Supreme Intelligence aims to future-proof itself as the AI ecosystem evolves.

For clients, that means less concern about betting on the “wrong” AI stack—and more focus on outcomes.

Continuous Optimization, Not Quarterly Postmortems

Measurement is another area where Supreme Intelligence pushes beyond traditional dashboards.

Rather than presenting static reports, the platform interprets live performance data to surface actionable insights in real time. Teams can adjust messaging, targeting, or spend based on immediate feedback—rather than waiting for quarterly reviews.

This aligns with broader trends in marketing analytics, where the emphasis is shifting from retrospective analysis to continuous optimization. In fast-moving therapeutic areas, the ability to pivot quickly can translate directly into competitive advantage.

For healthcare marketers used to long feedback loops, this could be one of the platform’s most disruptive features.

Built for Compliance—and Customization

Supreme Group emphasizes that Supreme Intelligence was built with regulatory rigor from day one. The platform supports privacy protections, approval workflows, and audit trails designed for healthcare and life sciences environments.

At the same time, its agentic architecture allows for deep customization. Supreme Intelligence isn’t limited to a fixed feature set; it can be configured to address specific challenges across the marketing lifecycle.

That flexibility matters as clients’ needs evolve. Supreme Group says it is actively expanding the platform with new workflows and applications in response to customer demand.

“We are rapidly building new AI workflows and applications, expanding alongside our customer’s needs,” Donnelly said.

How It Compares to the Rest of the Market

Supreme Intelligence enters a competitive—but fragmented—AI landscape.

On one end are general-purpose AI tools that offer broad capabilities but limited industry specificity. On the other are point solutions focused on narrow use cases like content generation or analytics.

Supreme Group is aiming for the middle ground: a verticalized AI platform that combines breadth with deep domain expertise. That strategy mirrors what’s happening in other regulated sectors, where vertical AI platforms are gaining traction over horizontal tools.

If successful, Supreme Intelligence could set a template for how agencies—and not just software vendors—build and deploy AI at scale.

What It Means for Healthcare Marketing

The launch of Supreme Intelligence signals a broader shift in the agency-client relationship. AI is no longer just a productivity layer; it’s becoming a shared operating system for strategy, execution, and measurement.

For healthcare and life sciences companies, that could mean faster launches, more confident experimentation, and better alignment between creativity and compliance.

For agencies, it raises the bar. As proprietary AI platforms become differentiators, the value of domain expertise—and the ability to operationalize AI responsibly—will matter more than ever.

Supreme Group is betting that its investment in a purpose-built AIP will pay off as clients demand more speed, transparency, and measurable impact from their marketing partners.

Whether Supreme Intelligence becomes a model for the industry remains to be seen. But one thing is clear: in regulated marketing, AI is finally moving from novelty to infrastructure.

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Formula E may race on a closed circuit, but for the 2026 Miami E-Prix, its presence won’t be confined to the track. OUTFRONT Media, one of the largest out-of-home (OOH) companies in the U.S., has been named the Official Out-of-Home Advertising Partner of the 2026 ABB FIA Formula E Miami E-Prix, alongside serving as Associate Partner of Change. Accelerated. Live: Miami.

The one-year partnership makes OUTFRONT a core media extension of Formula E, using Miami itself as the canvas. With access to Formula E intellectual property, OUTFRONT can deploy official branding across marketing campaigns, creative executions, and client activations—starting immediately with the recently held Miami E-Prix.

For Formula E, the move reinforces a growing focus on meeting fans beyond broadcast and digital channels. For OUTFRONT, it’s another signal that IRL media is becoming central to how major sporting events scale attention in dense urban environments.

Turning a Race Weekend into a Citywide Moment

The partnership centers on amplification. OUTFRONT’s OOH network is designed to push the energy of race weekend into everyday routines—commutes, neighborhoods, and public spaces—well beyond the Miami International Autodrome.

“Our entire Formula E team is excited to welcome OUTFRONT Media as the Official Out-of-Home Advertising Partner for the 2026 Miami E-Prix,” said Lee Zohlman, Partnerships Director at Formula E. “OUTFRONT has been instrumental in capturing the spirit of Formula E… ensuring that the energy of the Miami E-Prix reaches fans exactly where they live, work, and play.”

That philosophy is reflected in a citywide campaign launched around Hard Rock Stadium and throughout South Florida. The activation includes digital signage, fan village banners, media backdrops, high-impact digital billboards, and transit placements—formats designed to reach fans and non-fans alike as they move through the city.

The creative was designed and produced by OUTFRONT STUDIOS, the company’s in-house agency, underscoring a broader industry trend: OOH providers increasingly acting not just as media owners, but as full-service creative and experiential partners.

IRL Media’s Growing Role in Sports Marketing

OUTFRONT describes itself as an “in-real-life” (IRL) media company—a framing that’s gaining traction as brands look to complement digital reach with physical presence. In a media landscape dominated by screens, live sports remain one of the few reliably mass, culturally relevant moments. OOH, by design, intersects directly with those moments.

“IRL media is a force multiplier for fan engagement,” said Chris Mallen, Senior Director of Sports Marketing & Partnerships at OUTFRONT. “This partnership with Formula E represents a meaningful evolution in how live sports and IRL come together to connect brands to fans.”

That evolution is visible across OUTFRONT’s recent dealmaking. Late last year, the company announced partnerships with the Bay Area Host Committee and the Los Angeles Sports & Entertainment Commission, adding to a portfolio that already spans tentpole events like the Super Bowl and World Cup. Formula E slots neatly into that strategy, particularly as global motorsports continue to attract younger, sustainability-conscious audiences.

Formula E, Sustainability, and Brand Alignment

Formula E’s all-electric racing series has long positioned sustainability as a core differentiator, not a side narrative. OUTFRONT is leaning into that alignment.

The company highlighted its own sustainability initiatives as part of the announcement, including converting more than 75,000 lighting fixtures to LEDs—cutting energy usage per fixture by roughly 70%—recycling or repurposing nearly all vinyl canvases, installing solar panels at major office locations, and supporting public transit systems that reduce single-occupancy vehicle use.

For marketers, that alignment matters. As brands increasingly scrutinize the environmental impact of their media investments, partnerships that combine reach, cultural relevance, and sustainability credentials are becoming easier to justify—and harder to ignore.

What This Means for Brands and Cities

The OUTFRONT–Formula E partnership highlights a broader shift in how large-scale events think about media. Instead of treating OOH as a supporting channel, it’s being used as connective tissue—linking the event, the city, sponsors, and everyday audiences.

For brands activating around Formula E, the deal opens access to official IP and high-visibility placements that operate before, during, and after race weekend. For Miami, it reinforces the city’s growing role as a global sports and entertainment hub capable of hosting—and amplifying—international events.

And for the OOH industry, it’s another reminder that physical media isn’t retreating in the digital era; it’s evolving. When paired with live sports, experiential design, and social amplification, IRL media can turn a single race into a citywide cultural moment.

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The job description for a CMO has quietly—but radically—changed. Today’s top marketing leaders are expected to move at the speed of culture, understand creators as media ecosystems, deploy AI responsibly, and still deliver commercial growth under relentless scrutiny. The pipeline for that kind of leader, however, hasn’t always kept pace.

VaynerX and The Marketing Academy (TMA) are betting that changes now.

The modern integrated advertising company founded by Gary Vaynerchuk and the global marketing leadership organization led by Sherilyn Shackell have announced a shared commitment to accelerating the development of the next generation of marketing leaders worldwide. The collaboration brings together VaynerX’s culture-first, execution-driven approach with TMA’s long-standing focus on leadership development at the highest levels of marketing.

The partnership isn’t just symbolic. It’s designed to influence how future CMOs are identified, trained, and supported—well before they reach the top job.

The Future CMO Takes Center Stage

That shared vision was put into practice at VaynerX’s Future CMO Summit (FCMO), held at The Ranch at Rock Creek in Montana. The two-day, invite-only gathering brought together 20 high-potential marketers, each nominated by senior brand leaders, for an immersive professional development experience.

Rather than a traditional conference format, the summit emphasized candid conversation, real-time learning, and reflection. The focus was less on slides and more on the realities of leading in a world shaped by culture, creators, and AI.

At the core of the event—and the broader partnership—is a belief shared by both organizations: the most important person in the room is the future CMO. And the industry, they argue, has a responsibility to invest in that talent early, not after the title arrives.

A New Definition of Marketing Leadership

“Marketing is in the middle of a massive shift,” said Gary Vaynerchuk, Chairman of VaynerX. “Tomorrow’s CMOs must be fluent in culture, creators, AI, and speed, and most importantly, lead with empathy and accountability. Nurturing that talent early is essential for the future of our industry.”

That framing reflects a broader recalibration of what marketing leadership means. The modern CMO is no longer just the steward of brand and demand generation. They’re increasingly expected to be:

• A cultural translator who understands internet-native behavior

• A partner to creators and communities, not just media buyers

• A strategic operator who can apply AI without losing human judgment

• A leader capable of navigating organizational complexity and public scrutiny

This expanded remit has made the CMO role more powerful—and more fragile. Turnover remains high across many industries, often because the role evolves faster than leaders are prepared for.

VaynerX and TMA are positioning their collaboration as a way to close that readiness gap.

Why The Marketing Academy Fits This Moment

The Marketing Academy has spent years building a global network of senior marketers and future leaders, with a strong emphasis on confidence, capability, and values-based leadership. Its alumni network now includes more than 1,400 marketing leaders across the U.S., EMEA, and APAC.

“Our mission is to develop extraordinary leadership in exceptional talent,” said Sherilyn Shackell, Founder and Global CEO of The Marketing Academy. “By aligning with VaynerX around this shared ambition, we can help rising CMOs build the confidence, capability, and modern skillsets required to thrive in an increasingly complex world.”

The alignment makes strategic sense. TMA brings structure, mentorship, and long-term leadership development. VaynerX brings real-time exposure to how brands, platforms, and culture actually operate today.

Together, they’re aiming to blend theory with practice—something many leadership programs struggle to do in fast-changing digital environments.

From Summit Insights to Scaled Impact

The Montana summit wasn’t meant to be a one-off experience. Insights from the Future CMO Summit will directly inform programming throughout 2025 and 2026, shaping how both organizations approach leadership development.

Key themes emerging from the gathering include:

• Cultural fluency as a core executive skill, not a soft one

• Community-centric leadership, where audiences are participants, not targets

• Content ecosystem thinking, replacing campaign-first mental models

• AI enablement, with a focus on judgment, governance, and speed

These ideas reflect where marketing is heading, not where it’s been. As platforms fragment and attention becomes more contextual, CMOs are expected to orchestrate ecosystems rather than manage channels.

What’s Coming Next

Following the Future CMO Summit, VaynerX and TMA plan to roll out a series of coordinated initiatives aimed at emerging marketing leaders across regions. These include:

• Curated leadership development sessions and modern skill-building experiences

• Intimate roundtables and peer gatherings for future CMOs

• Cross-regional mentorship and connections with senior VaynerX and TMA leaders

• Ongoing thought leadership focused on the evolving role of the CMO

By spanning the U.S., EMEA, and APAC, the partnership also acknowledges that marketing leadership is no longer geographically uniform. Cultural context matters—and global CMOs must learn to operate across markets without defaulting to one-size-fits-all thinking.

Why This Matters to the Industry

At a time when AI is rewriting workflows and creators are reshaping media economics, marketing leadership development hasn’t always kept pace. Many organizations still rely on outdated playbooks or assume that experience alone will prepare leaders for what’s next.

This collaboration signals a different approach: proactive, intentional, and grounded in modern realities.

For brands, it suggests a future talent pool better equipped to handle complexity. For agencies, it reinforces the idea that leadership development is a shared responsibility, not just an internal HR function. And for rising marketers, it offers something increasingly rare—space to think, learn, and prepare before the pressure peaks.

The goal, as VaynerX and The Marketing Academy describe it, is simple but ambitious: to equip future CMOs with the tools, perspective, and community they need to shape the next era of global brand-building.

In an industry obsessed with what’s new, this partnership is a reminder that the most valuable investment may still be people.

Get in touch with our MarTech Experts.

Enterprise marketing rarely fails because of a lack of data, talent, or ambition. It fails in the messy middle—where dozens of specialized teams, brands, and regions collide inside tools that weren’t built for that kind of complexity.

MessageGears wants to fix that.

The warehouse-native data activation and engagement platform today announced a significant product expansion aimed squarely at one of enterprise marketing’s most persistent problems: coordinating large, distributed teams across many brands without sacrificing speed, control, or governance. The update introduces multi-brand experiences and a rearchitected user role framework, all delivered within a single, secure MessageGears instance.

It’s not a flashy launch built around generative AI headlines—but for enterprises running hundreds of campaigns across fragmented brand portfolios, it may be far more consequential.

Why Multi-Brand Marketing Breaks at Scale

Modern enterprise marketing is a team sport. Data engineers manage pipelines. Segment builders define audiences. Content authors craft messages. Campaign operators execute sends. Analysts measure outcomes. All of them touch the same systems—but not in the same way.

Most marketing platforms, however, still assume a one-size-fits-all user. Everyone gets roughly the same interface, the same permissions, and access to the same assets. At small scale, that’s manageable. At enterprise scale, it’s a liability.

The result is familiar: cluttered workspaces, risky over-permissioning, manual workarounds, duplicated assets, slow approvals, and brittle governance models that break under audit.

MessageGears’ latest expansion is built around a simple premise: enterprises don’t need more tools—they need clearer separation of roles, brands, and responsibilities inside the tools they already use.

Multi-Brand Workspaces Inside a Single Instance

At the center of the update is support for multi-brand experiences that allow large organizations to operate dozens—or hundreds—of brands within one MessageGears environment.

Instead of spinning up separate instances or relying on fragile permission hacks, teams can now create custom user groups by brand, sub-brand, department, or function, using a flexible tagging system. Every audience, template, campaign, sending profile, and data connection can be explicitly associated with one or more brands.

That tagging approach enables three things enterprise teams have historically struggled to balance:

• Autonomy, so individual brands can move quickly without stepping on each other

• Efficiency, so teams can reuse assets intentionally instead of duplicating work

• Governance, so access is controlled, auditable, and compliant by default

Each group operates independently, but within a shared platform and shared infrastructure—removing the cost and complexity of managing multiple disconnected environments.

“Teams with large brand portfolios have long struggled to balance autonomy with efficiency,” said Kevin Freeman, Product Lead at MessageGears. “These new capabilities make it dramatically easier for enterprise organizations to centralize their customer engagement strategy while still giving each brand the freedom, control, and safeguards they need.”

Less Clutter, Faster Execution

Beyond governance, the new workspace model also tackles a quieter productivity killer: irrelevant noise.

In many enterprise platforms, users see everything—even assets and brands they’ll never touch. MessageGears’ updated UI surfaces only the brands and assets relevant to each user, reducing cognitive load and making it easier to work confidently at speed.

That matters when campaign velocity is a competitive advantage. Fewer mistakes, fewer approvals bounced back for the wrong brand, and fewer hours wasted hunting through irrelevant assets all translate directly into faster execution.

A default “global brand” tag also gives admins a clean way to grant universal access to shared datasets, templates, or content—without blowing open permissions across the entire system.

Rethinking Roles and Permissions from the Ground Up

Multi-brand execution only works if roles are just as clearly defined as brands. To support that, MessageGears has significantly expanded and redesigned its user role framework.

Rather than generic roles with vague access levels, the new system reflects how enterprise marketing teams actually operate. Out-of-the-box roles now include:

• Data Engineer

• Segment Builder

• Content Author

• Global Content Author

• Campaign Author

• External Campaign Author

• Customer Profiler

• Integration Engineer

• Data Preview

• System Admin

Each role can be assigned with read-only, manager, or admin-level access for specific capabilities, allowing organizations to create precise separation of duties.

That separation reduces risk in two ways: it limits access to sensitive assets users don’t need, and it makes governance far easier to audit and maintain over time.

“Roles and permissions aren’t exciting on their own—but what they enable absolutely is,” Freeman said. “By streamlining governance across brands, our customers can execute more campaigns more confidently with less operational overhead.”

A Platform Built for How Enterprises Actually Work

MessageGears’ expansion reflects months of research into how large organizations collaborate across data, content, and execution—particularly in environments with strict governance and legacy system constraints.

“Enterprise marketing doesn’t break because teams lack talent or data,” said Eugene Yukin, VP of Product at MessageGears. “It breaks when specialized teams are forced into tools that weren’t designed for how those teams actually work.”

Yukin points to role clarity and UI alignment as critical success factors. When interfaces are designed around specific goals—rather than generic personas—teams move faster and make fewer mistakes.

These updates, he says, represent “a platform rebuilt around role clarity, brand separation, and governance—so enterprise teams can finally move fast together.”

How This Compares to the Broader MarTech Landscape

While many martech vendors are racing to add AI-driven features, fewer are tackling the unglamorous—but essential—operational foundations of enterprise marketing.

Multi-instance architectures, manual permissioning, and bolt-on governance tools are still common across large marketing stacks. They work, but at high cost and risk.

MessageGears is taking a different approach: centralize execution in one secure instance, then design the platform to respect brand boundaries and role specialization natively. It’s a strategy that aligns with broader enterprise IT trends toward shared infrastructure with strict logical separation.

For organizations managing complex brand hierarchies, that design choice could reduce cost, simplify audits, and unlock faster collaboration without compromising control.

Why It Matters Now

As enterprises push toward more personalized, data-driven engagement, the number of campaigns—and the teams required to support them—continues to grow. At the same time, regulatory scrutiny and data governance expectations are only increasing.

Platforms that can’t scale organizational complexity alongside campaign complexity become bottlenecks.

MessageGears’ latest release doesn’t promise magic. What it offers instead is something many enterprise marketers value more: clarity. Clear brands. Clear roles. Clear boundaries. And a cleaner path to executing more campaigns with less friction.

In enterprise marketing, that may be the upgrade that matters most.

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360.Agency is making a clear statement about where it believes automotive marketing and retail technology are headed—and how it plans to compete there.

The company announced two senior leadership appointments that mark a strategic inflection point: Daniel Martin has been named Chief Executive Officer, while Colin Danielson joins as Chief Revenue Officer. Together, the hires position 360.Agency for its next phase of growth, centered on AI-driven execution, cleaner data foundations, and tighter alignment between product, sales, and customer outcomes.

In an automotive market defined by margin pressure, fragmented consumer journeys, and rising expectations from both dealers and OEMs, leadership changes like these are less about titles—and more about operating models.

A CEO Mandate Focused on Execution, Not Experimentation

Daniel Martin steps into the CEO role with more than 25 years of experience spanning technology platforms, digital transformation, and enterprise-scale operations. His mandate is explicit: retool 360.Agency around an AI-first operating model that delivers measurable results, not just technical sophistication.

“This transition is about focus and execution,” Martin said. “We are retooling our platform and embedding AI where it creates real operational and commercial value for our partners.”

That framing reflects a broader shift underway in automotive martech. After years of experimentation with analytics, personalization, and automation, dealers and OEMs are now demanding systems that simplify workflows, reduce operational friction, and directly impact sales and retention.

Martin’s priorities—simplified execution, stronger data foundations, and outcome-driven AI—suggest a move away from feature sprawl toward disciplined platform design. In a category where many vendors promise transformation but deliver complexity, that restraint could be a competitive advantage.

Why AI-First Means More Than Adding Features

360.Agency’s emphasis on “AI-first” isn’t about chasing hype cycles. For automotive retailers, AI only matters if it improves day-to-day decision-making across inventory, marketing spend, lead management, and customer engagement.

Under Martin’s leadership, the company is focused on embedding intelligence directly into its technology stack and operating model—using AI to automate repetitive tasks, surface actionable insights, and support faster execution across dealer networks.

This approach aligns with a growing industry realization: AI works best when it’s invisible. The most valuable systems don’t require users to “use AI”; they quietly make workflows smarter and outcomes more predictable.

A CRO Built for Go-to-Market Discipline

Complementing the CEO appointment is the arrival of Colin Danielson as Chief Revenue Officer. Danielson brings more than 20 years of experience at the intersection of product innovation and revenue execution within automotive technology—a critical combination in a market where misalignment between sales promises and product reality can quickly erode trust.

As CRO, Danielson will lead sales strategy and go-to-market execution, with a specific focus on ensuring that customer needs inform product priorities, not the other way around.

“Technology only matters if it drives outcomes,” Danielson said. “Our role is to align teams, sharpen execution, and help dealers and OEMs succeed as the market moves faster.”

That emphasis on alignment is notable. Many automotive tech companies struggle with siloed functions—sales chasing growth, product chasing innovation, and customers caught in between. Danielson’s role is designed to close that gap, turning customer feedback into actionable product direction and more effective market delivery.

Why These Roles Matter Together

Individually, the CEO and CRO appointments make sense. Together, they signal a deeper organizational shift.

Martin’s focus on platform clarity and AI-enabled execution pairs naturally with Danielson’s mandate to translate customer needs into revenue strategy. The combination suggests 360.Agency is prioritizing operational discipline over expansion for expansion’s sake—a timely stance as automotive retail navigates economic uncertainty and accelerating digital change.

This tandem leadership model reflects a broader trend across B2B technology: growth increasingly depends on tight coordination between product, data, and go-to-market execution. AI amplifies that need by raising expectations for speed, relevance, and measurable ROI.

Context: Automotive Retail at a Crossroads

The automotive industry is undergoing structural change. Inventory dynamics are shifting. Consumer expectations are shaped by digital-first experiences outside the auto sector. OEMs are rethinking dealer relationships, data ownership, and brand control.

In this environment, marketing and retail technology platforms are under pressure to do more with less—less complexity, less manual effort, and less guesswork.

360.Agency’s leadership changes reflect an understanding that technology alone won’t solve these challenges. Execution, governance, and clarity matter just as much as innovation.

By emphasizing intelligent automation and disciplined operating models, the company is positioning itself as a long-term technology partner, not just a vendor of tools

What to Watch in 2026

Looking ahead, 360.Agency has signaled three clear priorities for 2026:

• Operational clarity, reducing friction across dealer and OEM workflows

• Intelligent automation, embedding AI where it improves speed and accuracy

• Disciplined execution, ensuring strategy translates into real-world results

For dealers and OEMs, the real test will be whether these changes result in simpler systems, better insights, and stronger performance across the retail lifecycle.

For the broader martech and automotive tech ecosystem, the move underscores a growing consensus: the next phase of growth won’t be defined by who adopts AI fastest—but by who operationalizes it most effectively.

The Bigger Picture

Leadership transitions often promise transformation. Fewer deliver it.

360.Agency’s appointments of Daniel Martin and Colin Danielson suggest a company recalibrating around fundamentals—data, execution, and customer outcomes—while using AI as an enabler rather than a distraction.

In an industry where complexity has long been accepted as the cost of doing business, that focus on simplification may prove to be the most disruptive move of all.

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