In an era when local television is under pressure from streaming giants and shrinking ad budgets, Hemisphere Media Group and Entravision are making a confident—and highly targeted—broadcast play. The two media companies have launched WAPA Orlando, a new full-power television station designed specifically for Central Florida’s Latino audience, with a sharp focus on the region’s rapidly growing Puerto Rican community.

WAPA Orlando officially began broadcasting on February 2, 2026, airing on Entravision-owned WOTF-TV (Channel 26) and reaching viewers across the Orlando–Daytona Beach–Melbourne DMA. The station carries programming from WAPA-TV, Puerto Rico’s top-rated television network for 16 consecutive years, while layering in locally produced news and digital-first distribution strategies.

The move reflects a broader recalibration in Spanish-language and Latino-focused media: go deeper locally, serve specific communities better, and blend legacy broadcast strength with modern digital execution.

A Local Station Built for a Distinct Latino Audience

Unlike many Spanish-language stations that aim for a broad pan-Latino appeal, WAPA Orlando is deliberately narrow in its focus. The station is tailored to Central Florida’s Puerto Rican population, which has surged over the past decade and now represents the second-largest Puerto Rican community in the continental United States.

Orlando is often referred to as Puerto Rico’s “79th municipality,” a cultural shorthand that underscores how deeply intertwined the island and Central Florida have become. That demographic reality creates an opportunity for programming that feels culturally specific rather than generically Hispanic.

WAPA Orlando is positioned as the first broadcast television station dedicated specifically to Orlando’s Puerto Rican community, combining island-produced content with local reporting that reflects the lived experiences of Puerto Rican families in Florida.

Leveraging WAPA’s Content Engine

At the heart of the new station is WAPA-TV’s production infrastructure, one of the most prolific news and entertainment operations in Puerto Rico. WAPA currently produces more than 80 hours per week of original programming, spanning news, entertainment, and cultural content.

That content pipeline gives WAPA Orlando an immediate advantage: a deep bench of proven programming without the startup friction that typically plagues new stations. Viewers will see familiar formats, trusted anchors, and established franchises—elements that matter in communities where media trust is earned over time.

For Hemisphere Media, this expansion extends WAPA’s brand beyond Puerto Rico in a meaningful way, transforming it from a dominant island network into a cross-market platform serving Puerto Rican audiences on the mainland.

Local News, Built with Entravision’s Infrastructure

While WAPA supplies the content muscle, Entravision brings the local-market expertise. The station’s local newscasts will be produced by Entravision and branded as NotiCentro Orlando, drawing on Entravision’s award-winning news organization.

At launch, WAPA Orlando will air two daily locally produced newscasts, in the morning and midday. Evening and late-night editions are planned as the station scales.

More importantly, the partnership establishes a collaborative national news framework, led by Entravision, that taps into reporting resources from 24 U.S. markets. That structure allows WAPA Orlando to cover local Central Florida stories while also contextualizing national issues affecting Latino and Puerto Rican communities across the country.

In practical terms, this means broader editorial reach without sacrificing local relevance—a balance many local stations struggle to achieve.

Why This Launch Matters Now

The timing of WAPA Orlando’s launch is notable. Local broadcast television has faced years of disruption, but it remains uniquely powerful in specific demographic niches—especially when paired with culturally relevant content.

At the same time, Puerto Rican audiences in the U.S. mainland have often been underserved by media that fully reflects their identity, language, and political concerns. WAPA Orlando steps into that gap with a clear value proposition: trusted Puerto Rican journalism, localized for Central Florida.

“This is a completely unique local service custom made for the Orlando Hispanic community,” said Alan J. Sokol, President and CEO of Hemisphere Media Group, emphasizing the blend of WAPA’s journalism with Entravision’s market expertise.

For advertisers, the appeal is equally clear. A focused, engaged audience with strong cultural ties is often more valuable than a larger but less defined viewership—particularly in categories like retail, healthcare, financial services, and political advertising.

Digital Strategy as a Core Pillar, Not an Add-On

Unlike traditional station launches of the past, WAPA Orlando is not treating digital as secondary. Entravision will develop and manage the station’s full digital strategy, including a dedicated website and standalone digital platform aimed at Orlando’s Latino audience.

Entravision will also handle all sales operations, supported by a dedicated local sales and production team. Beyond traditional TV spots, advertisers will have access to creative services, talent-driven integrations, turnkey video production, and combined commercial and digital buys.

This integrated approach reflects a growing industry reality: local TV stations increasingly function as multi-platform media hubs, not just linear broadcasters.

A Strategic Expansion for Both Companies

For Hemisphere Media Group, WAPA Orlando extends its footprint in the continental U.S. while reinforcing its leadership in Puerto Rican-focused media. The company already operates a wide portfolio that includes broadcast, radio, cable networks, FAST channels, and digital platforms targeting Hispanic and Latin American audiences.

For Entravision, the partnership strengthens its position in a key Florida market while aligning with a premium content brand that already commands loyalty. The collaboration also underscores Entravision’s continued investment in community-focused media, even as many broadcasters consolidate or pull back from local news.

Jeffery Liberman, President and COO of Entravision, described the launch as a way to better serve audiences, distributors, and advertisers by combining trusted brands with complementary strengths.

The Bigger Picture: Local Media, Reimagined

WAPA Orlando is more than a new channel—it’s a case study in how local broadcast media can evolve. By anchoring itself in a specific cultural community, leveraging high-volume content production, and integrating digital from day one, the station challenges the notion that broadcast TV is in irreversible decline.

Instead, it suggests a more nuanced future: fewer generic stations, more targeted ones—and partnerships that marry scale with specificity.

For Central Florida’s Puerto Rican community, WAPA Orlando promises something rare in today’s media landscape: coverage that feels both local and familiar, informed by a shared cultural lens.

Get in touch with our MarTech Experts.

Digital signage has quietly become one of the most influential—and demanding—channels in modern marketing. From retail stores and restaurants to corporate offices and healthcare facilities, screens are everywhere. The problem isn’t distribution anymore; it’s content. Keeping thousands of displays fresh, relevant, localized, and on-brand has become a full-time job—often without the headcount or budget to match.

Mvix, a long-time player in turnkey digital signage for mid-market and enterprise organizations, thinks it has a solution. The company has launched AI Suite, a new set of AI-powered capabilities built directly into the Mvix platform, aimed at helping marketing teams and retail media operators produce rich signage content faster, cheaper, and at far greater scale.

Available now as part of Mvix’s Signature 360 platform, AI Suite positions itself not as a novelty feature, but as a practical production layer for real-world signage operations.

Why Digital Signage Content Is Hitting a Wall

Over the past decade, digital signage has evolved from static slide shows to a primary communication channel. Screens now handle:

• In-store promotions and retail media ads

• Menu boards and dynamic pricing

• Employee communications and safety updates

• Brand storytelling and experiential content

Yet many mid-market organizations still rely on the same limited workflows: static templates, overworked designers, or external agencies that slow everything down.

The result is a familiar bottleneck. Content calendars fall behind. Screens go stale. Localization suffers. And teams spend more time managing production than thinking strategically.

Mvix’s AI Suite is designed to attack that bottleneck head-on by collapsing ideation, creation, and publishing into a single workflow—without requiring creative agencies or specialized tools.

What AI Suite Actually Does (and Why It’s Different)

AI features are showing up everywhere in martech, but many are bolted-on or narrowly scoped. Mvix is making a bigger claim: that AI Suite is one of the most comprehensive AI implementations in the digital signage industry, purpose-built for signage use cases rather than generic content creation.

Instead of offering a single AI image generator or text assistant, AI Suite supports multiple content formats in one unified workflow, including:

• Branded images

• Short-form promotional videos

• Spokesperson-style announcements

• Product-focused retail ads

• Music-driven creative elements

That breadth matters. Digital signage networks rarely rely on just one format. A single location might need promotional ads, informational messaging, and branded storytelling—all optimized for different screen sizes and contexts.

By supporting these formats natively, AI Suite aims to keep content varied and engaging without forcing teams to juggle multiple tools or vendors.

Built for Marketers, Not AI Specialists

One of the more notable aspects of AI Suite is its target audience. This isn’t positioned for designers, developers, or data scientists. It’s built for marketing managers, content strategists, and retail media operators—the people already responsible for keeping screens updated.

According to Mvix Executive VP Mike Kilian, that focus reflects reality.

“Marketers and content owners need to publish more, across more screens, in more locations, with less time,” Kilian said. “AI Suite removes friction from content production and helps teams deliver better experiences at scale.”

The emphasis here is on speed and consistency, not experimental creativity. AI Suite is designed to help teams:

• Generate content quickly without starting from scratch

• Maintain brand standards across locations

• Produce variations for different regions, promotions, or advertisers

• Keep content calendars full without adding staff

In other words, it’s about operationalizing creativity, not replacing it.

The Mid-Market Angle: Where AI Actually Matters

Enterprise brands often have agencies, studios, and budgets to brute-force content production. Mid-market organizations don’t. That’s where AI Suite is most likely to resonate.

Mvix highlights several concrete impacts for mid-market teams:

• Higher content velocity: Faster ideation, production, and publishing

• Brand consistency: Repeatable, on-brand outputs across screen types

• Retail media enablement: Rapid creation of ad variants for advertisers

• Operational agility: Quick responses to seasonal or real-time changes

• Richer formats: Moving beyond static templates into video and audio

This aligns with a broader industry shift. As retail media networks expand beyond ecommerce into physical spaces, the ability to produce and rotate ad creative quickly becomes a competitive advantage. Screens are inventory—but only if there’s content to fill them.

Beyond Content: AI for Signage Operations

While AI Suite’s headline feature is content creation, Mvix is also signaling where it’s heading next: infrastructure intelligence.

The company says it’s leveraging its device-level KPIs to develop predictive large language models aimed at improving endpoint performance. In practical terms, that means using historical device data—CPU usage, disk health, memory, network traffic—to anticipate problems before screens go dark.

Anomaly detection algorithms are being developed to forecast:

• Playback bottlenecks

• Network blocks

• Hardware or resource failures

For organizations running large signage networks, downtime isn’t just a technical issue—it’s lost revenue, missed promotions, and damaged brand perception. If Mvix can make predictive maintenance a reality, it would push AI Suite beyond marketing into operations, an area where AI often delivers clearer ROI.

How Mvix Stacks Up Against the Market

Many digital signage platforms now tout “AI-powered” features, but they’re often limited to single-use tools or experimental add-ons. Mvix’s approach is notable for its end-to-end ambition.

Rather than asking teams to adopt AI piecemeal, AI Suite integrates directly into the existing Mvix workflow. That lowers the barrier to adoption—an important factor for mid-market customers who may be skeptical of AI hype but eager for tangible productivity gains.

It also reflects a growing trend in B2B tech: AI as embedded infrastructure, not a standalone product. The tools that win aren’t the flashiest; they’re the ones that quietly remove friction from everyday work.

Why This Launch Matters

AI Suite arrives at a moment when digital signage is evolving from a display channel into a performance-driven medium. Screens are no longer just about visibility—they’re about engagement, monetization, and measurable outcomes.

By focusing on scalable content creation and predictive operations, Mvix is positioning itself not just as a signage vendor, but as a platform for always-on physical media.

For marketing teams drowning in content demands, that promise is compelling. The real test will be how well AI Suite balances speed with quality—and whether it truly reduces dependence on agencies and manual workflows.

If it does, Mvix may have found one of the more practical uses of AI in martech: not replacing people, but finally giving them room to breathe.

Get in touch with our MarTech Experts.

As AI-powered search engines increasingly reshape how information is discovered, marketers are running into a new problem: they can’t see what’s actually influencing AI-generated answers. Today, Stacker believes it has a fix.

The earned media distribution platform announced a strategic partnership with Scrunch that brings AI search visibility and citation reporting directly into the Stacker platform. The integration aims to help brands understand how third-party placements—news articles, syndicated content, and other earned mentions—affect their visibility and authority inside AI search tools.

That’s a growing concern as tools like ChatGPT, Google’s AI Overviews, and Perplexity pull from a mix of owned, earned, and third-party sources to generate responses. While marketers have plenty of data on how their own websites perform, what happens off-site has largely remained a black box.

Why earned media matters more in AI search

Traditional SEO rewards well-structured owned content. AI search, however, plays by different rules. Large language models tend to favor signals of credibility—citations, brand mentions, and authoritative third-party sources—often outside a brand’s direct control.

Most AI visibility platforms today focus on owned content discovery: whether a brand’s site is cited, summarized, or referenced in AI-generated responses. That approach misses a key piece of the puzzle: earned media.

Stacker’s core value proposition has always been earned reach—distributing brand stories across trusted publishers to generate third-party credibility. Scrunch, meanwhile, tracks how brands appear in AI search prompts, responses, and citations. Together, the companies are attempting to connect those dots.

The result is a unified view of how distributed stories and earned placements influence AI-driven discovery.

What the Stacker–Scrunch integration actually does

Once integrated, Scrunch’s AI search analytics will be embedded inside the Stacker platform. Customers will be able to track:

• AI prompt responses where their brand appears

• Brand mentions and citations in AI-generated answers

• The role third-party URLs play in AI visibility

• How earned placements compare to owned channels in shaping AI authority

Unlike standalone AI search tools, the Stacker integration adds context—linking AI visibility data directly to specific earned media placements and distribution campaigns.

For marketers trying to justify earned media spend, that connection is critical.

“AI search rewards credibility, and credibility is increasingly built outside your owned channels,” said Noah Greenberg, CEO of Stacker. “We’ve seen anecdotally how distributing owned content across third-party publications can directly impact AI search visibility, but nothing provided a comprehensive reporting solution for isolating the impact of earned media.”

In other words, this turns gut instinct into measurable insight.

Closing a major measurement gap

The partnership highlights a broader industry shift. As AI-generated answers replace traditional blue-link search results, marketers are being forced to rethink what “visibility” even means.

Clicks are declining. Attribution is fuzzier. And influence increasingly comes from being cited, summarized, or referenced—sometimes without a user ever visiting a brand’s site.

Scrunch CEO Chris Andrew framed the problem bluntly.

“If you are not showing up in AI search, it’s because there’s a gap between knowing which sources impact visibility and the ability to grow your brand presence in said sources at scale,” he said.

By pairing Scrunch’s AI monitoring with Stacker’s earned distribution engine, the companies aim to close that loop—showing not just where brands appear, but why they appear there.

How this compares to other AI visibility tools

The AI search analytics space is crowded but fragmented. Tools like Profound, BrandRank, and other emerging platforms track brand mentions in AI outputs, but most stop short of tying that visibility back to specific marketing activities.

Stacker’s approach stands out because it starts with distribution. Rather than treating AI visibility as an abstract metric, it ties performance to concrete earned placements—news articles, data-driven stories, and publisher syndication.

That could give communications and content teams a clearer path from action to outcome, especially as budgets tighten and leadership demands proof of impact.

Implications for PR, content, and SEO teams

This integration also blurs the traditional lines between PR, content marketing, and SEO.

AI search doesn’t care which team produced a piece of content—it cares about authority, context, and credibility. Earned media, long treated as a brand awareness play, is becoming a direct input into search visibility.

For PR teams, that elevates the strategic value of third-party placements. For SEO teams, it signals that optimizing owned pages alone is no longer enough. And for content teams, it reinforces the importance of stories designed to travel beyond a brand’s website.

Rollout timeline and availability

The Scrunch-powered AI Search Insights integration is scheduled to begin rolling out to Stacker customers in March 2026. While pricing and packaging details haven’t been disclosed, the feature will be embedded within the existing Stacker platform rather than offered as a standalone add-on.

That positioning suggests Stacker sees AI visibility not as a bolt-on metric, but as a core part of earned media strategy going forward.

The bigger picture

As AI search becomes the default interface for information discovery, marketers face an uncomfortable truth: influence is increasingly earned elsewhere.

The Stacker–Scrunch partnership reflects a broader recalibration happening across MarTech. Measurement frameworks built for websites and clicks are giving way to systems that track authority, citations, and presence across the wider information ecosystem.

For brands navigating that transition, visibility into earned media’s role in AI search may soon be less of a nice-to-have—and more of a survival skill.

Get in touch with our MarTech Experts.

Rocket Doctor AI Inc., a physician-built digital health company operating at the intersection of artificial intelligence and virtual care, is stepping up its market visibility.

The company (CSE: AIDR; OTC: AIRDF; Frankfurt: 939) announced it has engaged Vancouver-based Danayi Capital Corp. to provide digital marketing services over a two-month period starting February 9, 2026. The agreement comes with an upfront payment of USD $125,000 and is focused on online investor outreach and digital advertising via WallStreetLogic.com.

While short in duration, the move signals a broader push by Rocket Doctor AI to sharpen its narrative with investors and the market—particularly as competition intensifies across AI-enabled healthcare platforms.

A targeted marketing push, not a speculative play

According to the company, Danayi will operate strictly as a third-party service provider. The firm holds no direct or indirect ownership in Rocket Doctor AI or its securities, and all parties are described as operating at arm’s length.

That distinction matters. In today’s small-cap and emerging-tech markets, marketing engagements often attract scrutiny from regulators and investors alike. Rocket Doctor’s disclosure—covering Danayi’s compensation, scope of work, and lack of equity interest—reads like a preemptive move to reinforce transparency.

The marketing effort will focus on digital campaigns and online advertising, an increasingly common tactic among health-tech firms looking to stand out in crowded capital markets without resorting to splashy product announcements.

Equity incentives signal continued reliance on external expertise

Alongside the marketing engagement, Rocket Doctor AI also disclosed new equity compensation grants to consultants.

The company issued:

• 33,353 stock options, exercisable at $0.77 per share, with a three-year term

• 205,065 restricted share units (RSUs), also valid for three years

Both the options and RSUs vest over one year and were granted under the company’s existing share compensation plans.

While modest in size, the grants point to Rocket Doctor’s ongoing reliance on external consultants—a common approach among growth-stage AI and healthcare firms balancing speed, specialization, and cost control. Rather than expanding headcount aggressively, many companies in this space are opting for flexible, incentive-aligned expertise.

Why this matters in the AI health market

Digital health is no longer just about virtual visits. The sector is shifting toward AI-powered decision support, automation, and scalable care delivery—areas where Rocket Doctor AI is positioning itself aggressively.

At the center of the company’s technology stack is its Global Library of Medicine (GLM), a clinically validated AI decision-support system developed with input from hundreds of physicians worldwide. Unlike consumer-facing symptom checkers, GLM is positioned as a professional-grade tool designed to support clinical judgment rather than replace it.

That physician-first framing is increasingly important. As regulators and healthcare systems scrutinize AI tools for safety and bias, platforms built with direct clinician involvement are gaining credibility over black-box alternatives.

Beyond AI: a full-stack virtual care platform

Rocket Doctor AI’s ambitions extend beyond algorithms. Through Rocket Doctor Inc., the company operates an AI-powered digital health platform and marketplace designed to help physicians launch and manage independent virtual or hybrid practices.

To date, the platform has supported:

• 300+ licensed physicians

• 700,000+ patient visits

The value proposition is straightforward but timely: reduce administrative burden, restore physician autonomy, and expand patient access—particularly in underserved regions.

In Canada, that means rural and remote communities with limited access to family doctors. In the U.S., it includes patients covered by Medicaid and Medicare, where provider shortages and reimbursement complexity often limit care options.

Marketing meets mission

The decision to invest in digital marketing comes as healthcare AI companies face a dual challenge: proving clinical value while also communicating that value clearly to investors, partners, and regulators.

Rocket Doctor AI’s technology story—AI decision support, large language models, connected medical devices—sits squarely within some of the most hyped (and scrutinized) areas of modern healthcare. Cutting through the noise requires not just innovation, but disciplined messaging.

By engaging Danayi Capital for a defined, short-term campaign, Rocket Doctor appears to be testing how targeted digital outreach can amplify its story without overcommitting resources.

A crowded field with rising stakes

Rocket Doctor AI is far from alone in this race. Teladoc, Amwell, and a wave of AI-native startups are all vying to define the next generation of virtual care. Meanwhile, Big Tech continues to circle healthcare with AI-powered tools, raising the bar for differentiation.

In that context, visibility matters. Not just with patients or providers, but with capital markets increasingly selective about which AI narratives they believe.

The company’s recent disclosures suggest a strategy focused on incremental execution rather than headline-grabbing moves—tight marketing windows, measured equity incentives, and a steady emphasis on physician-led design.

The takeaway

Rocket Doctor AI’s engagement of Danayi Capital may not be transformative on its own, but it reflects a broader reality of the AI healthcare market in 2026: innovation alone isn’t enough. Companies must also prove credibility, transparency, and momentum.

As AI continues to reshape healthcare delivery, the winners are likely to be those that balance technical ambition with disciplined growth—and know how to tell that story clearly.

Get in touch with our MarTech Experts.

Attentive is doubling down on a simple but increasingly critical idea: in modern marketing, identity starts on mobile—even when shopping doesn’t.

The omnichannel marketing platform announced a major expansion of its patented two-tap™ technology, extending it from mobile-only flows to desktop shopping experiences for mobile subscribers. At the same time, Attentive rolled out a slate of new tools designed to help brands navigate tightening platform rules, shifting inbox behavior, and rising expectations for personalization across SMS, email, and beyond.

Together, the updates signal a clear strategic bet: as inbox filtering, privacy controls, and AI-driven experiences reshape digital marketing, brands that own durable, mobile-first customer relationships will have a structural advantage.

Why two-tap on desktop matters now

Two-tap™ has long been one of Attentive’s signature differentiators. The patented technology lets consumers subscribe to SMS marketing with minimal friction—typically two quick taps on their phone—dramatically increasing opt-in rates compared to traditional forms.

Until now, that experience lived primarily on mobile. But consumer behavior has changed. Shoppers increasingly browse on desktop at work or at home, then complete purchases—or engage with brands—on mobile.

By extending two-tap™ to desktop via a QR-based opt-in flow, Attentive is targeting a common blind spot in ecommerce: high-intent web traffic that never converts into a lasting, owned relationship.

Instead of asking desktop shoppers to fill out forms or remember to opt in later, brands can now prompt them to scan a QR code and instantly subscribe on their phone. The result is a cleaner handoff between devices—and a higher-quality subscriber entering the brand’s mobile ecosystem.

“Expanding two-tap™ to desktop increases the surface area for list growth and strengthens the long-term value of brands’ owned audiences,” said Nakul Narayan, Attentive’s Chief Product Officer.

Mobile identity over channel-first marketing

The two-tap expansion reflects a broader shift in how Attentive sees the market. Rather than treating SMS, email, push, and ads as separate channels, the company is positioning mobile identity—the phone number and its associated signals—as the connective tissue across the customer journey.

“Platform changes and shifting consumer habits are forcing marketing into a new era that favors mobile-first identity,” said Eric Miao, Attentive’s Chief Strategy Officer.

That framing is notable. As cookies fade, inbox algorithms tighten, and paid acquisition costs rise, first-party data has become the most valuable asset a brand can own. Attentive’s pitch is that mobile—specifically SMS—offers the most direct, resilient path to capturing and activating that data.

iOS inbox filtering raises the stakes

The timing of these updates is no accident. Apple’s continued evolution of iOS inbox behavior has made message visibility less predictable, particularly for promotional content.

According to Attentive’s internal data, messages routed into filtered inbox experiences can suffer 30–40% lower clickthrough and conversion rates. Combine that with the reality that 81% of consumers ignore irrelevant messages, and the margin for error gets thin fast.

To address this, Attentive introduced new inbox visibility tools that help brands identify messages at risk of filtering and apply proactive mitigations before performance drops. While the company hasn’t disclosed the exact mechanics, the focus is on preserving deliverability without resorting to volume-driven tactics that erode trust.

This aligns with a broader industry trend: inbox providers are increasingly rewarding relevance, consistency, and compliance over raw send frequency.

Compliance without the operational headache

Alongside visibility, compliance is becoming more complex—especially for brands operating across regions with different quiet-hour rules and consent requirements.

Attentive’s new capabilities aim to reduce that burden through automation rather than manual configuration. Key additions include:

• Automated state-level quiet hours, reducing the risk of sending messages at non-compliant times

• Improved location detection, minimizing operational lift for distributed audiences

• Audience size controls, helping marketers balance reach, budget, and performance

These features reflect a reality many teams face: compliance failures are rarely strategic—they’re operational. Automating guardrails allows marketers to move faster without increasing risk.

AI shifts from novelty to workflow engine

AI also plays a larger role in Attentive’s latest updates, but with a practical tilt. Rather than positioning AI as a creative replacement, the platform is using it to compress time-to-value.

New AI-driven features include:

• AI email template generation for faster, on-brand creation

• AI-powered campaign and journey enhancements to test, learn, and optimize with less manual effort

• Workflow intelligence that adapts messaging across SMS, email, push, ads, and loyalty integrations like Yotpo

The emphasis here is efficiency. As marketing teams are asked to do more with fewer resources, AI that reduces setup and iteration time is becoming table stakes.

Bridging online and offline experiences

Attentive also introduced barcode generation for email, allowing brands to connect digital campaigns to in-store experiences without custom HTML. While not flashy, it addresses a persistent challenge for omnichannel retailers: tying online engagement to physical-world behavior.

In an era where attribution is increasingly probabilistic, even small improvements in online-to-offline linkage can unlock more confident decision-making.

Proof points from the field

For brands already using two-tap™, the expansion to desktop builds on proven results. TeePublic and Redbubble report that Attentive’s approach has driven roughly 2x higher opt-in rates, a meaningful lift as inbox filtering and sender trust become stricter.

That kind of performance matters less for vanity metrics and more for durability. High-intent subscribers are more likely to engage, convert, and stick around—exactly the signals platforms reward.

The bigger MarTech picture

Attentive’s announcement highlights a broader recalibration underway in MarTech. Growth is no longer about adding more channels; it’s about owning fewer, stronger relationships and activating them intelligently.

As platform rules harden and consumers become more selective, frictionless consent, inbox visibility, and relevance aren’t optimizations—they’re prerequisites.

By extending two-tap™ beyond mobile screens and reinforcing its platform with compliance and AI-driven workflows, Attentive is betting that the future of personalization isn’t louder marketing. It’s smarter, more respectful, and rooted in identity brands truly own.

For marketers navigating mobile’s next era, that distinction may define who keeps their reach—and who slowly loses it.

Get in touch with our MarTech Experts.

As B2B buying journeys become longer, messier, and more group-driven, Forrester is sending a clear message to vendors: revenue marketing platforms must evolve—or risk irrelevance.

In its newly released The Forrester Wave™: Revenue Marketing Platforms for B2B, Q1 2026, Forrester Research named 6sense® a Leader, recognizing the company’s agent-powered Revenue Intelligence platform for its depth, data sophistication, and ability to operationalize how modern buying decisions actually happen.

The recognition reinforces 6sense’s positioning as a go-to platform for large B2B enterprises navigating a reality where buyers form preferences early, engage anonymously, and expect highly personalized interactions long before they ever talk to sales.

Why this Wave matters now

Revenue marketing platforms have moved beyond lead scoring and campaign tracking. According to Forrester, today’s systems must reflect how B2B buyers really behave: researching independently, acting as buying groups rather than individuals, and shifting signals constantly across channels.

The Wave evaluated vendors that offer unified revenue marketing platforms, generate meaningful market revenue, and are frequently cited by Forrester’s enterprise clients. In other words, this wasn’t a checklist exercise—it was a test of who can actually support enterprise go-to-market teams under real-world conditions.

Forrester’s conclusion: 6sense stands out for organizations looking to unify marketing and sales engagement around predictive, AI-driven workflows.

What Forrester highlighted about 6sense

In the report, Forrester states that 6sense “best fits B2B enterprises seeking a data-rich, AI-powered platform to unify marketing and sales engagement and operationalize predictive, orchestrated revenue workflows.”

That’s not faint praise. It reflects a shift away from siloed marketing automation and CRM add-ons toward platforms that act as a connective layer across the entire revenue engine.

Forrester also described 6sense’s offering as “among the most complete” in the evaluation, calling out its Intelligent Workflows as a key differentiator. These workflows unify data, intent signals, and orchestration inside what Forrester describes as an adaptive, AI-driven canvas.

In practical terms, that means teams can move from insight to action without jumping between systems—or relying on static rules that quickly go stale.

Perfect scores where it counts

6sense received the highest possible score in 14 evaluation criteria, including:

• Data capabilities

• Anonymous audience segmentation

• Adaptive workflow and journey orchestration

Those areas are increasingly critical as buying activity shifts earlier and becomes harder to observe. Anonymous research, once treated as a blind spot, is now one of the most valuable signal sources for revenue teams—if they can act on it.

By scoring highly across data and orchestration, 6sense is positioning itself not just as an analytics layer, but as an execution engine for modern GTM teams.

Customer feedback reinforces the narrative

Beyond product capabilities, 6sense also received above-average customer feedback in the evaluation. Customers described the platform as “strategic, responsive, and deeply integrated,” with particular praise for data accuracy, predictive modeling, and measurable pipeline impact.

That emphasis on outcomes matters. As CFOs scrutinize MarTech spend more closely, platforms that can directly tie activity to pipeline quality and revenue velocity have a clear advantage.

According to 6sense, customers use the platform to uncover in-market accounts earlier, engage buying groups more effectively, and improve conversion rates—ultimately winning larger deals and closing them faster.

The broader competitive landscape

The revenue marketing platform category has become increasingly crowded, with vendors racing to layer AI onto legacy ABM, MAP, and CRM stacks. Many promise intelligence; fewer deliver orchestration that scales across enterprise complexity.

What sets 6sense apart, according to Forrester’s analysis, is the tight coupling of data, prediction, and action. Rather than treating AI as an add-on, the platform uses it to continuously adapt workflows based on changing buyer behavior.

That approach aligns with where the market is heading. Static journeys and rigid funnels are giving way to systems that respond in real time—because buyers do.

A signal for enterprise GTM teams

For enterprise B2B organizations reevaluating their revenue tech stacks in 2026, this Wave offers a clear signal. Platforms built for yesterday’s linear buying models are struggling to keep up with today’s reality of distributed decision-making and early-stage intent.

“B2B buying has fundamentally changed, and go-to-market teams need systems built for how decisions are made today,” said Chris Ball, CEO of 6sense.

The Forrester recognition suggests that 6sense is resonating with that need—particularly among enterprises looking to unify marketing and sales around shared, actionable intelligence.

The takeaway

Being named a Leader in Forrester’s Revenue Marketing Platforms Wave isn’t just about feature depth. It reflects alignment with how B2B growth actually happens in 2026: anonymously, collaboratively, and long before a demo request.

For 6sense, the recognition reinforces its strategy of building an agent-powered platform that doesn’t just surface insights, but helps teams act on them—faster and with greater confidence.

For the market, it’s another sign that revenue marketing is no longer about managing campaigns. It’s about orchestrating decisions.

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The Data+AI security company announced a new AI-powered classification taxonomy designed to unify how enterprises identify, categorize, and protect sensitive data across modern data stacks and AI-driven environments. Alongside it, Symmetry introduced expanded “Bring Your Own AI” (BYOAI) capabilities, giving large organizations more control over how and where AI-powered classification runs.

Together, the announcements mark a strategic shift away from proprietary, vendor-specific classification models toward something the industry has largely lacked: a shared, extensible standard for data and AI security.

A single taxonomy for a fragmented security landscape

At the heart of Symmetry’s announcement is a comprehensive classification framework that serves as the backbone of its DataGuard platform. The taxonomy supports:

• 400+ sensitive data identifiers, spanning PII, PHI, PCI, financial data, credentials, and intellectual property

• 500+ semantic data types, including contracts, board documents, healthcare records, financial filings, and legal documents

• Regulatory mappings across GDPR, CCPA, HIPAA, PCI DSS, SOC 2, and emerging AI governance frameworks

• Privacy data elements, unified into a single model

The goal is straightforward but ambitious: replace the patchwork of incompatible taxonomies that force enterprises to translate policies across multiple tools, clouds, and vendors.

For security and privacy teams, that translation work has become a hidden tax—consuming time and increasing risk as data sprawls across SaaS apps, data lakes, warehouses, and AI pipelines.

Moving toward open standards, not closed ecosystems

Symmetry isn’t just introducing a new taxonomy—it plans to open source it, along with supporting datasets, to encourage industry-wide standardization and benchmarking.

In a notable step toward collaboration, the company has already integrated the Fides privacy-by-code taxonomy into its broader model. The combined taxonomy and corpus of test data will be released as an open-source project, with governance and benchmarking details expected in the coming weeks.

That approach directly challenges the status quo, where most data security vendors maintain proprietary classification schemes that don’t interoperate.

“Vendor-specific taxonomies force organizations to maintain multiple overlapping frameworks and create unnecessary friction,” said Sameer Sait, Senior Director of Information Security at Stanley 1913. “An open, standards-based taxonomy addresses a fundamental problem the entire industry faces.”

Why classification matters more in the AI era

Classification has always been foundational to data security—but AI has raised the stakes.

Large language models, analytics pipelines, and agent-based systems consume vast amounts of enterprise data. Without consistent classification, organizations struggle to answer basic questions: What data is sensitive? Where does it live? Who—or what—can access it?

Symmetry CEO Dr. Mohit Tiwari framed the issue bluntly.

“The data security industry has a taxonomy problem. Organizations waste resources translating between incompatible approaches instead of securing data.”

His comparison is telling. Tiwari likens Symmetry’s vision to a “PyTorch moment for data security”—a compact specification layer that abstracts complexity while enabling portability.

Just as PyTorch allows AI practitioners to define models once and deploy them across GPUs or TPUs, an open data security taxonomy would let privacy and security teams define policies once and enforce them everywhere—from Databricks Unity Catalog and Snowflake to AWS IAM, Kubernetes OPA rules, and DLP systems.

From policy statements to technical enforcement

One of the most compelling implications of the taxonomy is its role in bridging human policy and machine enforcement.

Today, high-level directives—such as “vendors cannot access customer data”—require manual translation into dozens of disconnected systems. That process is slow, error-prone, and difficult to audit.

Symmetry’s approach aims to turn those directives into policy-as-code, automatically generating permissions, access controls, network rules, and audit configurations across the stack.

This isn’t just about compliance speed. It’s about making governance scalable in environments where data and AI systems change faster than humans can document them.

Benchmarking data security like AI models

By releasing evaluation datasets alongside the taxonomy, Symmetry is also pushing for something rare in security: reproducible benchmarking.

In AI, shared benchmarks drove rapid improvement by making performance measurable and comparable. Data security classification, by contrast, has largely operated without standardized testing.

“Data security needs the same approach,” said Tiwari. “Open benchmarks allow the community to test, compare, and continuously improve classification accuracy.”

If adopted broadly, that could pressure vendors to compete on measurable outcomes rather than opaque claims.

“Bring Your Own AI” to avoid lock-in

Complementing the taxonomy is Symmetry’s expanded BYOAI support, which allows customers to run classification using their own AI infrastructure—whether that’s Azure OpenAI, AWS Bedrock, Google Vertex AI, or private GPU environments.

This matters for two reasons: data sovereignty and control.

Many enterprises are reluctant to send sensitive data through third-party cloud pipelines. Symmetry’s architecture brings AI-powered classification to where the data already lives, rather than forcing data to move.

That stands in contrast to cloud-dependent Data Security Posture Management tools that rely on centralized vendor infrastructure—an approach that can introduce compliance and trust concerns.

A differentiated position in a crowded market

The data security market is crowded with DSPM, DLP, and AI governance tools, many of which promise visibility but stop short of standardization.

Symmetry is carving out a distinct position: comprehensive classification, infrastructure flexibility, and an open standard designed to outlive any single vendor.

Whether the industry rallies around this taxonomy remains to be seen. But the problem it addresses—fragmented classification in a world of exploding data and AI usage—is real and growing.

The takeaway

Symmetry Systems isn’t just shipping a feature. It’s challenging a deeply entrenched model of proprietary data classification at a moment when AI is forcing enterprises to rethink governance from the ground up.

If its open taxonomy gains traction, it could do for data security what shared frameworks did for AI development: turn fragmented experimentation into a more measurable, interoperable discipline.

For enterprises grappling with AI-driven data sprawl, that shift can’t come soon enough.

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Consensus, the Demo Automation platform best known for letting buyers explore products on their own terms, is betting that gap can’t be closed by software alone. The company announced a strategic partnership with NewEdge Growth, a RevOps and go-to-market consulting firm that works with B2B and private equity–backed companies to design and scale modern revenue engines.

The partnership aims to make demo automation a structural part of RevOps, not just a sales enablement add-on—connecting buyer intent signals directly to GTM workflows across CRM, sales engagement, and analytics systems.

Why demos are still a bottleneck in modern B2B sales

Despite years of investment in automation, the product demo remains one of the most resource-intensive steps in the B2B funnel. Presales teams are stretched thin, sales cycles stall waiting for availability, and buyers increasingly want to self-educate before talking to a rep.

Consensus has built its business around that tension. Its platform automates product demos so buyers can explore asynchronously, while sales teams gain visibility into who engaged, what they viewed, and how intent is forming across stakeholders.

What’s been missing, however, is tight integration into RevOps strategy—how those signals are operationalized across forecasting, prioritization, and pipeline management.

That’s where NewEdge Growth comes in.

Bridging RevOps design and execution

NewEdge Growth specializes in architecting and integrating RevOps systems across complex B2B tech stacks, including CRM, sales engagement platforms, and analytics tools. Through the partnership, joint customers get a more unified approach: RevOps frameworks designed with demo automation baked in from the start.

Rather than treating demos as a one-off sales activity, the combined offering positions them as a data-generating asset inside the revenue engine.

Consensus’s Demolytics plays a central role here. The engagement data—who watched, for how long, and which features mattered—can be fed into RevOps workflows to help teams:

• Identify real buying groups earlier

• Prioritize deals based on demonstrated intent

• Reduce time spent on low-probability opportunities

• Scale presales without adding headcount

In a market where efficiency matters more than raw growth, that signal-driven approach is becoming essential.

Making demo automation operational, not optional

“We’re seeing too many teams invest in great technology without the strategy to fully leverage it,” said Adam Freeman, SVP of Global Partnerships & Strategic Alliances at Consensus. “This partnership is about making demo automation a core part of the revenue engine—not a disconnected tool.”

That distinction is subtle but important. Many B2B organizations already use demo automation in pockets, often driven by sales or marketing teams independently. The result is fragmented adoption and underutilized data.

By embedding Consensus into NewEdge Growth’s Tech Stack Services and RevOps as a Service offerings, demo automation becomes part of the system design—not an afterthought.

Why this matters for PE-backed and high-growth companies

The partnership also reflects broader pressure coming from private equity and boards. PE-backed companies are increasingly focused on revenue efficiency, predictability, and scalability, especially as hiring slows and CAC remains elevated.

Presales-heavy models don’t scale well under those constraints. Demo automation, when properly integrated, offers a way to support more pipeline without linearly increasing cost.

For Consensus, the partnership creates a strategic channel into organizations already investing in RevOps transformation. For NewEdge Growth, it adds a proven automation layer to help clients modernize sales execution faster.

Buyer control meets revenue signal

At a philosophical level, the partnership aligns with how B2B buying has changed.

“Modern buyers want control. Revenue teams need signal,” said Blake Brock, Founder & COO of NewEdge Growth.

Asynchronous demos give buyers autonomy, while Demolytics provides sellers with behavioral insight that’s often more reliable than form fills or surface-level engagement metrics.

When those insights are tied directly into RevOps workflows—routing, scoring, forecasting—the “next best action” becomes clearer, and deals move with less friction.

Competitive context: RevOps is consolidating

The RevOps ecosystem is consolidating around platforms that do more than collect data—they need to orchestrate action. CRM alone isn’t enough. Neither is a standalone enablement tool.

Consensus’s move mirrors a broader trend where point solutions are being pulled deeper into the revenue stack, either through partnerships or platform expansion. Vendors that can prove they influence cycle time, win rates, and pipeline quality—not just activity—are the ones gaining traction.

By aligning with a RevOps consultancy rather than another software vendor, Consensus is signaling that adoption and execution matter as much as features.

The takeaway

The Consensus–NewEdge Growth partnership isn’t about adding another integration. It’s about redefining where demo automation belongs in the B2B revenue model.

As buying becomes more self-directed and revenue teams are asked to do more with less, demos can no longer sit on the edge of the funnel. When automated demos are designed into RevOps from day one, they become a source of signal, scale, and speed.

For B2B organizations struggling to align strategy with execution, that shift may be exactly what the revenue engine needs.

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