In an era when marketers are drowning in traffic data but struggling to turn clicks into customers, White Peak Marketing thinks it has the fix. The Reno-based agency will debut MaximizeOS™, a fully managed marketing service designed to convert more traffic into revenue, at the upcoming B2B Marketing Expo in Las Vegas (Oct. 15–16).

The service aims to help businesses move beyond the outdated “traffic-first” mindset and focus instead on what really matters: maximizing conversions, customer lifetime value, and ROI in a digital world increasingly shaped by AI.

MaximizeOS: Playing Offense in an AI-Driven Market

MaximizeOS isn’t just another marketing dashboard. White Peak bills it as an end-to-end managed service, engineered to:

• Personalize buyer journeys in real time

• Boost conversion rates and average order value

• Cut down time-to-purchase

• Extend customer lifetime value

The timing couldn’t be better. With ad costs climbing and generative AI eating into organic search traffic, marketers face mounting pressure to justify spend. MaximizeOS promises to help businesses squeeze more growth out of every click—without burning through budgets.

A Stage and a Statement

White Peak’s CEO, Tim Woda, will drive home the company’s message during his talk, “#ShiftHappens: Digital Marketing Has Changed. Play Offense While Others Panic,” on Oct. 15 at 1:15 PM in Theater 8.

Woda doesn’t mince words: “The digital marketing landscape has shifted, and most marketers haven’t. While advertising costs skyrocket and AI cannibalizes organic traffic, many businesses are chasing traffic instead of fixing what happens after the click. That’s a fatal mistake.”

His session will offer a blueprint for adapting—personalizing buyer journeys, targeting mid-funnel audiences with SEO, and using AI to create demand before prospects even know they need it.

Why It Matters

MaximizeOS underscores a larger trend in martech: moving from volume metrics (traffic, impressions) toward verified outcomes (conversions, revenue, lifetime value). Competitors like HubSpot, Salesforce, and Adobe have been rolling out AI-powered tools in similar directions, but White Peak’s positioning is more direct: hands-off for clients, all-in on ROI.

With its launch at the Expo, White Peak is betting that businesses are ready to stop panicking over AI-driven disruption and start using it to their advantage.

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B2B marketers are drowning in intent signals and SaaS dashboards, but confidence in pipeline delivery has never been shakier. DemandScience, a global player in performance marketing, is trying to fix that with the launch of Ionic and Labs, two offerings designed to puncture what it calls the “Marketing Data Mirage.”

That mirage? The false confidence created when marketing teams lean on dubious signals, scattered platforms, and content that doesn’t land—burning budget on activity that doesn’t actually convert.

A Unified System for Real Buyers

At the heart of this rollout is Central, DemandScience’s new intelligence and insights hub. Instead of marketers stitching together data vendors, orchestration platforms, and content syndicators, Central brings it all under one roof.

The system is anchored by three core components:

• Ionic: the intelligence and orchestration layer that blends verified buyer data, real-time behavior signals, and AI-driven orchestration into one closed-loop system. It’s fully transparent, showing where signals come from and how campaigns adapt in real time. Importantly, it’s embedded directly into every DemandScience program—no extra platform to buy.

• Labs: a services arm staffed with “demand scientists.” Labs combines human expertise, AI, and Ionic’s intelligence to run always-on campaigns across paid media, email, web, syndication, and events.

• Central: the hub where marketers monitor audiences, track performance, and tap AI-powered recommendations for their “next best move.”

Together, the trio aims to replace vague intent scores, cut through AI-fueled content fatigue, and collapse siloed orchestration into a streamlined cycle where each campaign improves on the last.

Industry Voices

“Marketers don’t need another intent score they can’t trust or another platform to manage,” said Derek Schoettle, CEO of DemandScience. “They need confidence that every signal represents a real buyer, that campaigns execute across channels without added complexity, and that content connects. Ionic and Labs deliver all three.”

That sentiment resonated with early users. Manoj Jasra, CMO at Emids, noted that too many teams are “chasing intent signals we can’t verify” while juggling rising complexity. The appeal of DemandScience’s system, he said, is that it simplifies the entire process: verified data in, meaningful growth out.

Why It Matters

The B2B marketing stack has grown bloated, with intent data vendors, orchestration tools, and content platforms fighting for budget. Yet pipeline confidence is at a low. By folding intelligence, services, and optimization into one system, DemandScience is positioning itself as an alternative to the patchwork approach dominated by players like Bombora, 6sense, and TechTarget.

If the system delivers on its promise—verified signals, better orchestration, and content that actually resonates—it could help marketers shift from chasing phantom intent to building predictable, compounding pipeline.

Ionic, Labs, and Central are available globally now.

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Retail media is booming—and so is the competition. With McKinsey projecting commerce media to claim 20% of global ad spend by next year, brands and retailers are scrambling to build their own high-margin ad networks. But data silos, clunky workflows, and legacy tech have slowed many enterprise efforts.

Enter GrowthLoop, the AI-driven marketing innovator that today unveiled its Compound Marketing Engine for Commerce Media Networks. The new solution promises to let enterprises finally put their vast stores of first-party data to work—fast, securely, and at scale.

The timing couldn’t be sharper. GrowthLoop has already landed Costco as a strategic partner to expand its retail media operations, signaling serious market traction.

Unlocking the First-Party Goldmine

“Enterprises sit on a goldmine of customer data in the cloud, but legacy systems keep it locked away,” said Chris O’Neill, CEO of GrowthLoop. “The future of commerce media belongs to enterprises that can instantly activate that data. With GrowthLoop, we’re unlocking it and putting AI directly into the hands of marketers.”

That’s the bet: empower marketers to move at the speed of advertising demand without endless engineering cycles. GrowthLoop’s AI agents build high-precision audience segments, generate campaign recommendations in natural language, and deliver real-time measurement—all while keeping data inside the enterprise’s cloud for compliance and security.

What’s Inside the Engine

The new commerce media solution sits on GrowthLoop’s composable architecture, meaning it plugs into data clouds like BigQuery, Snowflake, and Databricks with ease. Features include:

• Self-service audience building: Create hyper-granular segments in minutes, enriched with device IDs, purchase history, and household-level insights.

• Agentic AI support: Always-on intelligence suggests new audiences and brand segments to accelerate campaign setup.

• Multi-brand management: Role-based access and permissions for enterprises managing multiple networks under one roof.

• Ad-tech flexibility: Integrations with 70+ destinations, from onsite networks to DSPs and ID graphs, plus one-click “multi-export” deployment.

• LiveRamp onboarding: Boost match rates and extend advertiser reach across channels.

• On-demand measurement: Move from sluggish reporting to near real-time results in the cloud.

• Enterprise-grade security: SOC 2 Type II compliance, clean-room integrations, and full audit trails.

Why It Matters

Commerce media networks are the new cash cow for retailers, but building them has been messy. Traditional vendors like Criteo, The Trade Desk, and CitrusAd have carved out footholds, but many enterprises have struggled to operationalize their own data.

GrowthLoop’s pitch is that it combines compliance-grade governance with the speed and intelligence of AI, creating a scalable path for retailers to monetize audiences and for advertisers to access high-intent shoppers.

For an industry sprinting toward a trillion-dollar ad future, that’s no small promise.

GrowthLoop’s Compound Marketing Engine for Commerce Media Networks is available now.

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When law firms talk about “digital transformation,” it often sounds like consultant-speak. But in the case of UK-based Howes Percival, the move is concrete: the award-winning firm is doubling down on its partnership with NetDocuments, the cloud-first document management system (DMS) widely regarded as a leader in the legal tech space.

The expanded agreement is part of a broader business transformation strategy that leans heavily on workflow automation and secure collaboration. For a firm recognized for its “world-class” workplace engagement, it’s not just about keeping up with digital change—it’s about freeing up lawyers to do more actual lawyering.

From Three Hours to 30 Minutes

The firm plans to apply NetDocuments’ document automation across its legal templates and processes, promising speed gains that matter in the trenches. For example, drafting power of attorney documents—a task that previously took three hours—will soon take just 30 minutes. In the world of billable hours, that’s not just an efficiency boost; it’s a competitive edge.

And it’s not all behind the firewall. With NetDocuments’ integration into Microsoft Teams, client and third-party collaboration gets a security-first upgrade—crucial in an era where breaches and compliance headaches haunt law firms.

A Tighter Tech Stack, Not a Bigger One

Lee Killner, IT Director at Howes Percival, summed up the firm’s approach bluntly: “Too often, IT teams default to buying new software, creating complexity and distracting from client service.” Instead, the firm is paring back to a tighter set of core apps, with NetDocuments at the center.

That mindset—fewer, smarter tools rather than endless add-ons—is gaining traction across industries. It reflects a broader trend in legal tech, where the focus has shifted from adopting flashy solutions to making core systems smarter and more user-friendly.

Why This Matters

NetDocuments isn’t the only player in the DMS space—rivals like iManage and Worldox have long vied for dominance—but its cloud-first, automation-driven positioning seems well-timed. As more firms confront client demands for faster turnaround and cost transparency, shaving hours off routine tasks isn’t just operational efficiency; it’s survival strategy.

Kerri Dearing, VP of International Business at NetDocuments, put it more diplomatically: “By driving innovation through the apps legal professionals use every day, law firms can be confident they are empowering their teams to do their best work.” Translation: this is as much about retention and morale as it is about efficiency.

The Bigger Picture

For Howes Percival, with more than 250 partners and fee earners on the roster, scaling automation could mark a pivotal moment in its modernization journey. But the ripple effects extend beyond one firm. If document drafting can be slashed from hours to minutes without compromising compliance, it resets expectations for clients—and puts pressure on competitors still relying on manual-heavy workflows.

The broader takeaway: legal tech’s “boring” tools—document management systems, automation engines, collaboration integrations—are quickly becoming the real battleground for differentiation. And in that fight, NetDocuments just secured another loyal ally.

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The creator economy may be booming, but brand partnerships can be a minefield. From mismatched values to reputational risks, one wrong collaboration can undo years of careful marketing. That’s the challenge Later—the platform powering creator commerce—says it’s tackling with its newly launched AI-Powered Brand Suitability Insights.

Billed as an enterprise-ready solution, the tool helps marketers vet creators with more nuance than the usual red-flag checks. Instead of stopping at risk detection, Later promises a dual view: spotting potential pitfalls while highlighting which creators are most likely to deliver performance and ROI.

Beyond “Brand Safety”

Most existing brand safety tools focus on negatives—flagging profanity, controversial topics, or conflicts of interest. Later’s pitch is that this approach only tells half the story. By layering AI-driven analysis over publicly available creator data, the platform produces a comprehensive report that combines risk assessment with performance potential.

Marketers receive:

• Executive Summary: Key risk levels, metrics, and a recommendation.

• Brand Suitability Score: A straightforward fit rating.

• Risk Matrix: Category-by-category scoring across 12 risk areas, from misinformation to brand conflicts.

• Audience Intelligence: Insights into follower quality and engagement.

• Performance Analytics: Benchmarks across platforms.

• Transparent Data Sources: Clear sourcing so teams know exactly where the numbers come from.

The idea: make creator partnerships both safer and smarter.

Context: Why This Matters Now

As influencer marketing grows more sophisticated, so do the risks. Brands are increasingly wary of controversies spilling over from creators’ personal content. At the same time, pressure for measurable ROI is rising—especially in an era where ad budgets face scrutiny.

By fusing risk and performance metrics, Later is positioning its platform as a way to future-proof brand investments. As CEO Scott Sutton put it, “Marketers shouldn’t have to choose between protecting their brand and achieving performance outcomes.”

The Competitive Angle

Later isn’t alone in this space. Companies like CreatorIQ, Captiv8, and Tagger have all rolled out tools for vetting influencers, often with a heavy emphasis on brand safety. But Later’s differentiator is its dual-sided scoring system: protect brand equity while also spotlighting creators most likely to drive growth.

Chief Customer Officer Phoebe Maclachlan summed up the appeal: the feature “reduces the risks of mismatched collaborations while unlocking the upside of the right ones.” In other words, it’s not just about avoiding disasters—it’s about finding the partnerships that actually move the needle.

The Bottom Line

Later’s AI-powered Brand Suitability Insights reflects a broader trend: the shift from blunt risk-avoidance to precision brand-creator matching. For marketers, that means less guesswork, fewer PR headaches, and a clearer case for ROI. And in a noisy creator economy, clarity may be the most valuable insight of all.

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AI has already transformed how marketers generate content, but what if the AI could actually think like a marketer? That’s the bold promise behind Markethinking, a new reasoning model from Marketeam.ai that bills itself as the world’s first autonomous intelligence engine purpose-built for marketing.

Rather than just spitting out copy on command, Markethinking is designed to research, analyze, strategize, and execute marketing campaigns with minimal human intervention. In other words, it’s not just a writing tool—it’s a full-blown marketing strategist in code.

Moving Beyond Prompt-Driven AI

Most large language models are built for general-purpose tasks. Markethinking flips the script with a narrow but deep focus: marketing. The 8-billion-parameter model, post-trained on Qwen3 with more than 10 billion tokens of curated marketing data, is engineered to work natively with marketing platforms, CRM systems, and SaaS tools.

This specialization allows it to:

• Continuously monitor competitors, sentiment, and campaign performance.

• Brainstorm strategic opportunities in real time.

• Draft and execute multi-channel campaigns.

• Optimize results dynamically, all while keeping brand voice and customer psychology in check.

That’s a tall order, but if it works as advertised, it could redefine what “autonomous marketing” really means.

Outperforming the Giants

Marketeam.ai claims Markethinking outpaces leading models—including DeepSeek, Qwen, Gemma, and LLaMA—on domain-specific benchmarks. Internal tests reportedly showed stronger brand alignment, more consistent tone, and higher factual reliability. Even under budget constraints, the model delivered higher engagement and conversion rates compared to rivals.

CTO and co-founder Sahar Millis framed the difference bluntly: “The industry has been focused on content generation. We built an LLM that has brand understanding and context engineering baked into its reasoning.”

Open-Source, But With Boundaries

In a notable move, Marketeam.ai has made a research checkpoint available on Hugging Face, where it’s already been downloaded over 10,000 times. Developers are plugging it into their own marketing workflows, testing the boundaries of autonomous brand intelligence.

But there are caveats. The model was purpose-built for marketing—step outside that lane, and performance falls off quickly. Unlike GPT-4 or Gemini, you won’t be using this to code apps or solve math proofs. It’s laser-focused on campaign strategy, planning, and execution.

A Continuous Intelligence Loop

The architecture is designed for integration: feeding data from CRMs, analytics platforms, and market signals into a continuous intelligence loop. This lets agents not just monitor the landscape but adjust campaigns on the fly—something most human teams struggle to do at scale.

VP of R&D Coby Benveniste emphasized the technical leap: “Traditional models struggle with real-time marketing data. We’ve built reasoning chains that can track multiple tasks while keeping context coherent.”

Why It Matters

Marketing AI is maturing fast. First came generic content tools, then audience insights platforms. With Markethinking, Marketeam.ai is trying to carve out a new category: reasoning models purpose-built for marketing ecosystems.

If the approach sticks, it could push the industry away from AI “assistants” toward truly autonomous agents—ones that don’t just follow prompts but proactively run campaigns. Competitors like Jasper and Copy.ai will likely need to respond, either by deepening their domain intelligence or risk looking like glorified text editors.

Looking Ahead

Commercial implementations of Markethinking are set to roll out in Q3 and Q4 2025 as the core of Marketeam.ai’s Integrated Marketing Environment (IME). For marketers under pressure to do more with leaner teams and tighter budgets, an autonomous agent that can think strategically could be a game-changer—or at least a powerful copilot.

The catch? Trust. Brands will need confidence that an autonomous AI can not only execute campaigns but also uphold brand equity, manage risks, and make judgment calls marketers usually guard closely.

If Marketeam.ai can clear that hurdle, “autonomous marketing intelligence” may become the next big buzzword—and this time, maybe one worth believing.

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SEO used to be about ranking first on Google. Now, the real prize may be showing up in AI-generated answers. AdLift, the global SEO and digital marketing firm (now part of Liqvd Asia), is aiming to solve that problem with a new feature for its AI visibility platform, Tesseract.

The feature, called Brand Share of Voice (SOV), gives marketers a way to see which sources large language models (LLMs) cite when referencing their brand—and how often. In plain English: it’s a way to measure whether AI assistants like ChatGPT, Gemini, Perplexity, and Google’s AI Overviews think your brand is worth mentioning.

From Rankings to References

In the old SEO playbook, a first-page ranking was the holy grail. But with the rise of AI-driven search, traditional SERPs are being replaced by synthesized answers, often with no click-through at all. That shift has left CMOs scrambling to understand how their brand appears—or disappears—in AI outputs.

“AI models are now gatekeepers of information,” said AdLift CEO and co-founder Prashant Puri. “If your brand isn’t being cited by authoritative sources, you risk invisibility in tomorrow’s search landscape. Brand SOV is about giving digital leaders the clarity they need to influence those AI outputs.”

What’s Inside Brand SOV

The new dashboards offer:

• Citation Tracking: Which sources are citing a brand and how often.

• Source Frequency Breakdown: Identifying which publications or domains influence AI responses most.

• Export Tools: Actionable data to strengthen brand trust signals in the places LLMs are listening.

By surfacing this data, AdLift positions Tesseract as one of the first platforms globally to make AI citation tracking available at scale—a capability that could reshape enterprise SEO strategies for the “zero-click” era.

Why It Matters

The launch lands at a pivotal moment for marketers. AI-generated answers are already siphoning traffic from traditional search, with some estimates suggesting double-digit drops in organic clicks. For brands, the question is no longer just “Where do we rank?” but “Whose sources do the AIs trust?”

Competitors in the SEO tool space—think Semrush, Ahrefs, and BrightEdge—are experimenting with AI visibility metrics. But AdLift’s move to formalize “Brand Share of Voice” could give it a head start in carving out a new category: AI-era authority measurement.

The Bottom Line

For marketers, Brand SOV reframes SEO around influence rather than position. If Google once cared about backlinks, tomorrow’s AI engines care about citations. And if AdLift is right, the brands that master those signals now will be the ones AI models surface later.

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Digital teams are under pressure to do more with less—publish accessible, compliant content that ranks in search, performs across channels, and adapts to AI-driven discovery. That’s the challenge Siteimprove is trying to tackle with three new capabilities added to its recently launched Agentic Content Intelligence Platform, Siteimprove.ai: Content Blueprint AI, Mobile Solutions Suite, and Digital Experience Analytics (DXA).

The upgrades are designed to break down silos between SEO, content, accessibility, and analytics, turning fragmented workflows into a single ecosystem that prioritizes performance and compliance.

From Insights to Execution

Traditional SEO platforms often stop at insights, leaving teams to guess how to act. Content Blueprint AI goes further. Using agentic AI, it translates search data, cluster analysis, and performance signals into prioritized content actions. Instead of telling marketers “what happened,” it points to what should be built, why it matters, and what business impact to expect.

The human-in-the-loop design keeps marketers in control—whether fine-tuning strategy, ensuring compliance, or aligning outputs with brand voice—while giving teams the ability to scale strategies efficiently.

Mobile Accessibility Meets Analytics

Mobile experiences are still a blind spot for many enterprises. Accessibility checks often come late in the app lifecycle, and analytics tools rarely speak to each other. Siteimprove’s new Mobile Solutions Suite aims to fix that by combining mobile accessibility testing with in-app analytics.

This unified approach means product, QA, and marketing teams can spot accessibility issues earlier, share insights more easily, and speed up fixes—all while gaining a clearer picture of how users interact with apps.

Analytics With Context, Not Just Numbers

Standard analytics tools tell you what users did—clicked, scrolled, bounced—but rarely why. Digital Experience Analytics (DXA) layers in session replay and struggle detection to show where users get frustrated. Think “rage clicks,” endless scrolling, or stalled interactions.

Crucially, DXA is built for non-technical teams. Content managers, demand gen specialists, and UX designers can watch real sessions and diagnose issues without relying on developers, helping enterprises improve digital journeys faster.

A Unified Push Toward Accessible, High-Performing Content

Kalvin Brite, SVP of Products at Siteimprove, positioned the launch as part of a bigger mission: “Our goal is to transform access to the digital world. These new capabilities give customers the edge in winning with AI search and accessibility experiences by pairing agentic AI with deeper analytics.”

The bigger story here is less about shiny new features and more about integration. Where most enterprise teams juggle a patchwork of SEO tools, accessibility checkers, and analytics dashboards, Siteimprove is betting on an all-in-one, AI-first platform that merges them.

The Bottom Line

With AI transforming how users discover and engage with content, brands can’t afford siloed strategies. Siteimprove’s latest release underscores a clear industry shift: from static measurement to agentic, integrated systems that not only surface problems but guide solutions.

For enterprises struggling with accessibility, SEO, and user experience at once, Siteimprove’s bet is that a unified platform will mean faster fixes, smarter content, and fewer missed opportunities in the AI era of search.

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