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Mutinex Bolsters Its U.S. Presence with the Appointments of Two High‑Profile Leaders; Mike Finnerty Named President, United States, Lou Paskalis Elevated to Senior Advisor

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Mutinex Bolsters Its U.S. Presence with the Appointments of Two High‑Profile Leaders; Mike Finnerty Named President, United States, Lou Paskalis Elevated to Senior Advisor

Mutinex

The moves support the agentic marketing effectiveness leader’s intent to scale in the region and accelerate enterprise customer success

Mutinex, the leading agentic marketing effectiveness platform, announced the appointment of Mike Finnerty as President, United States. Finnerty joins Mutinex from TransUnion, where he played a key leadership role in scaling the company’s measurement and identity capabilities following its acquisition of Neustar. At Mutinex, he will focus on driving growth and ensuring the success of U.S. enterprise customers.

“Mutinex is building what every CMO and CFO has been asking for — a single platform that connects marketing investment to financial outcomes with clarity, speed, and confidence,” said Finnerty. “The shift toward AI‑powered, always‑on marketing effectiveness is already underway, and Mutinex is defining the category. I’m thrilled to help bring this capability to more enterprises across North America.”

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Mutinex also announced that Lou Paskalis, who has already played a pivotal role at the company, has been elevated to Senior Go-to-Market Advisor. Paskalis is a widely respected marketing leader best known for his strategic leadership in investment, governance attribution, and accountability at Bank of America, American Express, and Gallo Wine, where he started his career.

Paskalis’ expanded role will focus on helping CMOs and CFOs lead with confidence and advocate for the standards and governance needed to harness AI ethically and drive growth. His long‑standing commitment to industry advancement is reflected in his work with the ANA, the Media Ratings Council (former board member), MMA North America (former Chairman of the Board, President and COO) and many client advisory councils.

These appointments come amid surging demand for AI‑powered marketing analytics. Recent research from Insider Intelligence, Gartner, and the ANA shows that more than 70% of CMOs plan to increase investment in marketing effectiveness platforms over the next two years.

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“Mike is one of the rare leaders who has seen the entire measurement ecosystem end‑to‑end — from identity and attribution to enterprise analytics and global go‑to‑market,” said Henry Innis, CEO and Co‑Founder of Mutinex. “His decision to join Mutinex is a powerful signal about where the market is heading. Enterprises are moving beyond legacy attribution and toward agentic, financially validated decisioning. Mike will help us scale that future across North America.”

At TransUnion, Finnerty partnered with advertisers, agencies, and publishers to maximize the adoption and growth of the company’s marketing solutions. He previously served in leadership positions at Neustar, where he helped shape the company’s identity‑driven analytics offerings and supported its integration into TransUnion’s global business.

In his new role, Finnerty will lead Mutinex’s U.S. commercial organization, expand strategic partnerships, and support continued investment in enterprise‑grade modeling, data connectivity, and agentic decisioning. Customer success and growth in the U.S. will be his team’s singular priority.

Paskalis added, “Mike’s move to Mutinex is one of the clearest signals yet that the industry is entering a new era of accountability and intelligence. He’s joining a company that is not just improving measurement. It’s reinventing how marketing decisions get made. Mutinex is building the operating system for modern growth, and Mike, with whom I worked closely during my tenure at Bank of America, is exactly the kind of leader who can help scale that vision.”

Finnerty and Paskalis’ appointments follow a year of significant growth for Mutinex, including major platform advancements, expanded global operations, and increased adoption among Fortune 500 brands seeking a modern alternative to traditional attribution and MMM providers.

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MediaCo Appoints Neida Gotay as Vice President, Integrated Sales

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MediaCo Appoints Neida Gotay as Vice President, Integrated Sales

MediaCo Holding Inc. Logo

MediaCo Holding Inc. announced the appointment of Neida Gotay as Vice President, Integrated Sales.

In this role, Gotay will oversee both local and national sales operations in Orlando and Atlanta, while also leading strategic business development efforts across all Florida markets. She will focus on driving integrated, multi-platform revenue growth, strengthening agency and client partnerships, and ensuring local market execution aligns with MediaCo’s expanding national opportunity.

Gotay brings deep experience in media sales leadership and revenue strategy, including 18 years at Hearst Television where she played a key role in building and expanding its network of Spanish-language stations.

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“Neida is a proven leader who understands how to bring together local market expertise with national scale,” said Brian Fisher, Chief Revenue Officer of MediaCo. “As advertisers increasingly look for integrated, multi-platform solutions, Neida’s ability to connect our local teams with national demand will be instrumental in accelerating our growth across Florida and the Southeast.”

Her appointment comes as MediaCo continues to strengthen its integrated sales strategy across TV, audio, digital, and streaming, enabling advertisers to reach multicultural audiences at scale while delivering locally relevant market impact.

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“MediaCo’s portfolio and audience momentum create a powerful opportunity for brands,” said Neida Gotay. “I’m excited to work with our teams across Orlando, Atlanta, and Florida to deepen client partnerships, unlock new growth opportunities, and bring the full strength of MediaCo’s platforms to the market.”

Gotay’s role will be instrumental in expanding MediaCo’s presence across Florida and the Southeast, strengthening local market leadership while delivering national scale for advertising partners. Her appointment comes as MediaCo continues to grow its regional footprint, including the upcoming launch of EstrellaTV Orlando WDYB 14 and HOT TV WDYB 14.2 on March 24th.

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NIQ Launches Beta of New AI-Powered Analytical Capabilities in Ask Arthur

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TruGen AI Launches Enterprise AI Teammates, Redefining How Organizations Work at Scale

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AI-guided analysis helps brands and retailers turn data into decision-ready insights

NIQ , a global leader in consumer intelligence, has launched new AI-powered analytical capabilities in beta within Ask Arthur on the NIQ Discover platform. The expanded experience guides users through end-to-end analysis—helping them identify what matters in the data, understand why trends are occurring, and turn insights into clear, shareable narratives with recommended next steps.

As organizations navigate increasing data complexity, the ability to move quickly from insight to action has become essential. Ask Arthur helps shorten analytical processes that once took days or weeks into minutes by surfacing the key drivers behind performance changes and generating decision-ready insights directly within Discover. By connecting analysis, explanation, and storytelling in a single experience, users can move seamlessly from understanding what is happening in the data to determining what to do next.

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“These new analytical capabilities represent an important step forward in how we bring AI directly into the analytical workflows our clients rely on every day,” said Troy Treangen, Chief Product Officer at NIQ. “Ask Arthur allows organizations to unlock the power of generative AI for analytics—built on NIQ’s trusted data foundation and informed by thousands of real-world analyses. By combining AI with the depth and reliability of NIQ data, we’re enabling brands and retailers to move from insight to confident action faster than ever.”

Combined with NIQ’s trusted global data and deep industry expertise, Ask Arthur brings AI-powered analytics directly into the workflows clients use every day—helping brands and retailers unlock the Full View™ of consumer behavior and translate insights into confident decisions.

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During the beta phase, NIQ will focus on driving client adoption, gathering real-world feedback, and continuing to enhance the experience through incremental feature releases. Insights from client usage will help shape the next phase of Ask Arthur’s development as NIQ expands AI-powered capabilities within Discover.

New capabilities coming in the months ahead will further expand the Ask Arthur portfolio, including the introduction of a chat-based experience. Over time, Ask Arthur will continue evolving toward a more intelligent AI agent—proactively helping users uncover insights faster and navigate complex data with greater clarity.

This beta launch marks the first key milestone in the evolution of Ask Arthur as NIQ continues to expand AI-powered capabilities that help clients move faster from data to decisions.

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Fluent, Inc. Announces Partnership with Squire to Expand Commerce Media Solutions Beyond Traditional Retail Platforms

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Fluent, Inc. Announces Partnership with Squire to Expand Commerce Media Solutions Beyond Traditional Retail Platforms

Partnership with leading all-in-one barbershop management and booking platform represents broader expansion into high-intent transactional environments including services, travel, hospitality

Fluent, Inc., a leading provider of commerce media solutions, announced a partnership with Squire, the leading all-in-one barbershop management and booking platform. This partnership builds on Fluent’s continued momentum outside of traditional retail environments, extending its relevance-first monetization model into appointment-based platforms where high-intent consumer engagement drives measurable performance.

Squire powers booking, payments, marketing, and business management tools for thousands of barbershops nationwide, facilitating millions of appointments each year. As a platform centered on recurring service transactions, Squire represents a differentiated commerce media environment activating confirmed booking moments that occur well beyond the ecommerce checkout. By applying a disciplined, experimentation-led framework across its growing partner network, Fluent enables platforms to maximize monetization while preserving brand integrity and user experience.

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This partnership unlocks expanded placement opportunities across the Squire platform while reinforcing customer loyalty and long-term platform value — ensuring that monetization enhances, rather than disrupts, the booking experience. Building on its existing monetization strategy, Squire is partnering with Fluent to enhance revenue yield from post-booking engagement. By combining Fluent’s large-scale experimentation capabilities and transparent bidding marketplace with Squire’s highly engaged and differentiated audience, the collaboration will deliver timely, contextually aligned offers following appointment confirmations.

Central to this partnership is Squire’s use of Fluent’s Data Clean Room, built in partnership with Databricks, which enables the secure combination of Squire’s rich first-party customer data with Fluent’s proprietary identity graph and AI engine. Unlike session-based targeting that captures only a single moment in time, this integration draws on the full consumer relationship — layering purchase history, behavioral signals, and audience intelligence to deliver offers that are meaningfully relevant to each individual. The result is a smarter, more durable monetization model that compounds in value as the customer relationship deepens over time.

“Our focus has been on expanding commerce media into environments where intent is explicit and recurring,” said PJ Triboletti, SVP, Revenue at Fluent. “Appointment-based platforms like Squire represent a powerful next frontier of our Commerce Media business with deeply engaged audiences, and moments where relevance truly matters. This partnership strengthens our push beyond retail and into service-driven ecosystems.”

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“As we continue to scale the Squire platform, it’s critical that any monetization strategy aligns with the premium experience we deliver to barbers and their clients,” said Dave Salvant, President and Co-founder at Squire. “Fluent’s approach allows us to expand post-booking engagement in a thoughtful, performance-driven way — creating incremental revenue opportunities while maintaining trust with our community.”

As commerce media continues to mature, appointment- and booking-based platforms like Squire demonstrate how Commerce Media Solutions can extend across the real-world economy connecting advertisers with consumers at meaningful moments of confirmed intent.

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Synscribe Launches SEO AI Agent That Autonomously Executes SEO & GEO – Claims to Replace Traditional Agencies

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BrightEdge Data: AI Search is Reaching a Tipping Point – by End of 2026 Most Online Customers will be AI Agents

Singapore Startup Synscribe Upgrades OpenClaw Into a Multi-Tenant AI Agent That Executes Full-Stack SEO and GEO — Cutting 90% of Manual Agency Work

Synscribe, an AI SEO & GEO startup, has launched a multi-tenant SEO & GEO AI agent built on the open-source OpenClaw framework that autonomously performs keyword research, creates landing pages, conducts link building, and generates blog posts — work traditionally handled by full-service SEO agencies.

The company says the system has been running in production for several weeks across its B2B SaaS client base and has reduced manual SEO execution by more than 90%.

An AI Agent That Executes, Not Just Advises

Unlike conventional SEO tools that surface data for humans to act on, or agencies that rely on teams of content strategists and junior writers, Synscribe’s approach assigns each client a dedicated AI agent that independently carries out SEO strategy from research through execution.

“Most SEO agencies are staffed by content strategists, account managers, and junior writers. We’re staffed by engineers,” said Raymond Yeh, founder of Synscribe. “When we look at the challenge of getting a SaaS product to rank on both Google and ChatGPT, we don’t see a content calendar problem. We see a systems engineering problem.”

Each agent is capable of browsing the web, executing code in a sandboxed environment, creating and managing files, and maintaining long-term memory of client context — operating in a manner that the company compares to a human executive assistant, but one that works around the clock and scales across every account simultaneously.

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How It Works: Multi-Tenant Architecture on OpenClaw

The system is built on OpenClaw, an open-source AI agent framework that provides tool access including browsers, code execution, and file management. Synscribe extended the framework with custom infrastructure to support enterprise-grade multi-tenancy.

The architecture includes four key components:

Isolated tenant environments. Every client receives a dedicated agent instance with its own memory, files, skills, organisational context, and preferences. No data crosses between client environments. Synscribe describes it as “a completely different world” when switching between accounts.

Shared institutional knowledge. While client data is siloed, all agents share access to a curated layer of SEO and GEO (Generative Engine Optimization) best practices — playbooks derived from campaigns across multiple clients and thousands of pages. When the team identifies a new tactic that works, the knowledge layer is updated once and immediately available to every agent.

Sandboxed code execution. Each agent operates within its own isolated virtual environment, with the ability to run scripts, launch browser sessions, and perform analysis — but without root access or visibility into other tenants.

Autonomous self-reporting. Agents automatically file structured reports when they encounter tool failures, pipeline bottlenecks, or workflow inefficiencies. According to Yeh, the system has surfaced issues including broken environment variables in new deployments, platform-level browser blocks, and database connection exhaustion — often with suggested workarounds.

“Imagine having AI workers that tell you how to build your system better for them,” Raymond said. “That wasn’t a feature we designed. It emerged from giving agents the right introspection tools.”

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Four Demonstrated Capabilities

In a recent product demo, Synscribe showcased four core workflows the agent handles autonomously:

Deep Company Research

Given only a company’s website URL, the agent conducts multi-step research — browsing the site, running search engine queries, exploring keyword opportunities — and compiles a comprehensive dossier including the company’s product positioning, competitive landscape, adjacent tools, and keyword opportunities. The company says this process, which might take a traditional agency weeks for complex verticals like satellite communications or quantum technology, completes in minutes.

Keyword Planning and Organisation

The agent extracts keyword opportunities from research outputs and meeting transcripts, then categorises and tags them using Synscribe’s proprietary labelling framework. Keywords are classified by intent and relevance, assigned to monthly planning cycles, and bulk-inserted into the company’s keyword management dashboard — a process that previously required hours of manual specialist work.

Programmatic Landing Page Generation

The agent designs landing page structures, generates SERP-informed content, and produces complete page data as structured JSON that can be exported to any tech stack — including Next.js, Webflow, Framer, and WordPress. The company demonstrated generating comparison pages (e.g., “Synscribe vs. [Competitor]”) at scale, with each page individually researched against current search engine results to identify content gaps and ranking opportunities.

According to Synscribe, the system can produce hundreds of conversion-optimised pages from a single strategic conversation, with each page including headlines, body content, comparison tables, FAQs, and calls to action.

Sales Call Preparation

Beyond SEO execution, the agent prepares discovery call plans for the sales team — generating tailored opening scripts, discovery questions, pitch angles based on the prospect’s specific situation, and competitive intelligence. The company says these workflows are then saved as reusable “skills” that improve with each use.

Market Context: The $80B SEO Industry Meets AI Agents

Synscribe’s launch comes as the global SEO services market — valued at approximately $80 billion and projected to double by 2030 — faces increasing pressure from AI-driven disruption.

The rise of AI-powered search engines including ChatGPT, Perplexity, and Google’s AI Overviews has created a new discipline — Generative Engine Optimization (GEO) — that requires companies to optimise not just for traditional search rankings but for AI citations and recommendations.

At the same time, several startups are pursuing the “AI agent for services” model in adjacent markets. Y Combinator has backed companies including Rankai and Relixir in the AI-SEO space, while Kleiner Perkins led a $20 million Series A for Profound, an AI-powered SEO platform. Synscribe differentiates itself as a hybrid — part product company, part growth agency — where the AI agent handles execution and a human team manages strategy and quality control.

“The opportunity isn’t to build a better SEO tool,” Raymond said. “It’s to build the AI-native company that delivers SEO and GEO outcomes at software margins and software speed.”

Codifying Craftsmanship

Raymond frames the core innovation not as automation but as the ability to codify judgment at scale.

“Every successful SEO campaign requires taste — which keywords to prioritise, how to structure a page that converts, what angle will resonate with a specific audience,” he said. “That judgment used to live exclusively in the heads of experienced professionals. We’ve found a way to encode it into skills and playbooks that AI agents can execute consistently, across any industry and any client.”

The company points to its shared knowledge layer as the mechanism: institutional expertise — built from real campaign data — is encoded once and propagated to every agent instantly. When the SEO landscape shifts, one update to the knowledge layer changes how every agent operates.

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EverFast Fiber Networks Taps GOCare to Power Digital Transformation and Customer Engagement Strategy

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EverFast Fiber Networks Taps GOCare to Power Digital Transformation and Customer Engagement Strategy

Logo for GOCare

The growing Kansas City broadband provider introduces digital engagement channels, automated communication, and streamlines operations with integration to MACC, Adtran, and HubSpot platforms

Headquartered in Lenexa, Kansas, EverFast is a rapidly growing, fiber broadband provider committed to delivering a fast, reliable, and future-proof internet experience to residents and businesses in the Kansas City area. As a local provider, EverFast is redefining how fiber broadband is deployed and experienced in its communities.

To further that mission, EverFast has chosen to implement GOCare’s product suite—including GOCare® Messenger, Connect, Pulse, and Reach—integrating seamlessly with EverFast’s existing systems, including MACC’s billing platform, Adtran Mosaic One, and HubSpot.

“EverFast is committed to delivering a world-class customer experience that matches the speed and reliability of our network,” stated Andrew Koelker, Marketing Manager at EverFast Fiber. “GOCare enables us to meet our customers where they are—on their phones and digital channels—and deliver fast, automated service that reduces friction and increases engagement.”

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Unlocking a Modern, Digital CX

By partnering with GOCare, Everest will:

  • Launch modern digital channels such as two-way SMS, web chat, and social media messaging via GOCare Connect, giving customers real-time support on their terms.
  • Automate communications around billing, appointments, and service updates using GOCare Messenger, decreasing call volume and empowering customer self-service.
  • Gather actionable customer insights through GOCare Pulse, a real-time NPS®/CSAT survey solution, enabling EverFast to continuously improve based on direct feedback.
  • Run proactive outreach campaigns with GOCare Reach, targeting segmented audiences to promote service availability, upgrades, and more—all while integrating into the customer journey.

Seamless System Integration

EverFast’s deployment will include robust integration across key platforms, including:

  • MACC and Adtran, leveraging GOCare’s real-time API access to synchronize customer data and automate workflows.
  • HubSpot, enabled through the GOCare Connect plugin, ensures sales and support teams have a complete view of customer interactions.

“MACC is proud to support EverFast’s digital transformation alongside GOCare,” said Brian Thomas, EVP at MACC. “By integrating GOCare’s Digital Experience platform with MACC’s open APIs, EverFast can deliver a more efficient, connected, and customer-centric experience—aligning perfectly with their mission to provide better, faster internet and service.”

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Guided Digital Transformation

GOCare brings a proven track record of reducing operational expenses, improving first contact resolution, and helping broadband providers evolve their digital experience with confidence. With deep experience supporting providers, GOCare’s team is guiding the deployment with a focus on best practices and measurable outcomes.

“We’re thrilled to welcome EverFast Fiber Networks to the GOCare family,” said Mike Roddy, CEO and co-founder at GOCare. “EverFast’s decision to go all-in on digital channels reflects its forward-thinking approach to customer experience. We look forward to helping them reduce call volume, integrate systems, and ultimately deliver a modern experience that sets them apart.”

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Brandlive launches BrandTV™, the Enterprise Streaming Platform Every Company Needs

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Brandlive launches BrandTV™, the Enterprise Streaming Platform Every Company Needs

Brandlive - Wikipedia

The new streaming platform enables enterprises to host live Town Halls and all of a company’s on-demand video content, turning work into must-see TV.

Brandlive, the company bringing the magic of TV to business, announced BrandTV, a new streaming platform designed to help companies and their leaders communicate with video that feels authentic, human and real.

DiGennaro Communications Expands Executive Leadership and Launches Content Studio

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DiGennaro Communications Expands Executive Leadership and Launches Content Studio

Home | DiGennaro Communications | business-to-business public relations agency

  • Award-Winning Journalist Laura Petrecca Named Chief Content Officer

  • MaryLiz Ghanem and Kristen Morquecho Promoted to Co-Managing Directors

  • Kendra Peavy Appointed Fractional Chief Marketing Officer

DiGennaro Communications, LLC announced an expansion of the executive leadership team at its flagship agency, DGC, as well as the launch of a freestanding division, The Authority Studio, a new content strategy and production offering. These moves reinforce DGC’s continued investment in senior talent while expanding its marketing and communications capabilities in service of its client base.

Laura Petrecca, an award-winning journalist, newsroom leader, and former editor at USA Today, New York Post, and Ad Age, joins DGC as Chief Content Officer. She will lead The Authority Studio, which focuses on building distinctive thought leadership and industry authority for clients. Petrecca will oversee content strategy, storytelling, and creation across a wide range of platforms and formats.

The Authority Studio complements DGC’s public relations capabilities, delivering ownable thought leadership and proprietary brand IP, including articles, research reports, LinkedIn programs, podcasts, newsletters, video, and book projects. The studio will also support sales enablement and marketing initiatives produced under DiGennaro Communications’ Marketing2Marketers (M2M) subsidiary.

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Initial clients include mktg.ai, a creative intelligence system for marketers, and Creative Spirit, a nonprofit that DGC helped to launch that connects neurodivergent talent with innovative, inclusive employers.

“In an era defined by AI acceleration, media fragmentation, and information overload, skilled content strategy and creation are more important than ever,” said Samantha DiGennaro, founder and CEO of DiGennaro Communications. “Laura’s well-honed journalist instincts, digital fluency, and leadership experience will enable our clients to create differentiated narratives that support growth and achieve business goals.”

Petrecca will lead a highly curated team of editors, writers, producers, strategists, and digital media professionals. At a time when generic AI-generated content is proliferating, she will ensure all work meets the highest standards of editorial rigor, clarity, and strategic alignment with each client’s goals, helping individuals and organizations build lasting authority. In parallel, she will partner with clients to create content designed for AI-driven discovery through AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization), ensuring their expertise is surfaced and referenced in AI results.

“I’ve long admired DGC’s ability to craft compelling narratives and am excited to join at a time when skilled storytelling matters more than ever,” Petrecca said. “As audiences are inundated with a nonstop stream of content, true engagement and authority come from insights that provide real value.”

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DGC also announced a senior leadership expansion to support the agency’s continued momentum.

  • In recognition of their contributions, DGC Senior Vice Presidents MaryLiz Ghanem and Kristen Morquecho were named Co-Managing Directors, overseeing the agency’s client portfolio and day-to-day operations.
  • Morquecho will lead DGC’s Los Angeles office and West Coast operations, while continuing to head the agency’s technology practice.
  • Ghanem will lead DGC’s New York office and East Coast operations, while continuing to oversee the agency’s Media, Marketing, and Entertainment Practice (formerly Creative Media and Marketing).
  • Kendra Peavy, DGC’s Chief of Staff, took on the additional role of Fractional Chief Marketing Officer, where she’ll partner with DiGennaro to shape the agency’s brand, positioning, and go-to-market strategy.

These four leaders are part of an executive team that includes DiGennaro, Chief Financial Officer Kerry Ernst, and Chief People Officer Jennifer Lazzaro.

“The DGC team’s creativity, operational rigor, and client-first mindset enable us to consistently deliver innovative, effective solutions for our clients,” said DiGennaro. “We’re celebrating our 20th anniversary this year with expansion and momentum, as well as a continued emphasis on exceptional client service.”

The announcements come on the heels of DGC’s successful launch of its Marketing2Marketers (M2M) division in partnership with marketing industry veteran Jon Bond, its recognition as an Inc. 2025 Power Partner, and a gold honor in the PR category of Ad Age’s 2024 Small Agency of the Year awards.

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Amagi Report Finds Applied AI Moving Into Core Media Workflows; FAST Viewing Rises 21%

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Amagi Report Finds Applied AI Moving Into Core Media Workflows; FAST Viewing Rises 21%

Amagi - IABM Member Company Details

March 2026 Airtime Report from Amagi highlights applied AI adoption across media workflows and sustained global FAST momentum

Applied AI is accelerating across media operations, while Global FAST (Free Ad-supported Streaming TV) viewership and ad monetization continued their double-digit growth in Q4 2025, according to the March 2026 edition of the Amagi Airtime Report: Special Edition – AI in Media Operations.

The report finds that global Hours of Viewing (HOV) across FAST grew 21% year-over-year in Q4 2025, while ad impressions rose 27% during the same period. The analysis is based on approximately 4,200 FAST channel deliveries distributed via Amagi’s THUNDERSTORM server-side ad insertion (SSAI) platform. (Overall, Amagi manages 9,000+ channel deliveries as indicated in the FY2025-26 Q3 earnings call).

While FAST continues to scale globally, the report’s central theme focuses on the accelerating adoption of applied AI across media operations. Based on a survey of 50 broadcast and streaming leaders evaluating 20 end-to-end content operations tasks, respondents identified the strongest AI impact potential in high-volume, information-driven workflows such as metadata enrichment, context tagging, subtitling and translation, and social content publishing. The report features exclusive conversations with Brian Briskman, Co-Founder and Consultant at Likewise Media Consultants, and Cam Price, Co-Founder of LeadStory.

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“The industry is entering a phase where AI is no longer just about experimentation — it’s about embedding intelligence directly into operational workflows,” said Srinivasan KA, Co-founder and President – Global Business. “Media companies that integrate applied AI across ingest, localization, scheduling, and monetization will unlock meaningful gains in speed, efficiency, and scalability.”

The report emphasizes that AI’s greatest value emerges when it moves beyond isolated tools and becomes native to content workflows — dynamically flagging QC exceptions, triggering localization, resolving rights compliance, and identifying monetization opportunities in real time.

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According to the report, FAST maintained growth across all major regions in Q4 2025 compared to Q4 2024.

  • LATAM: 66% HOV growth; 77% ad impression growth
  • APAC: 23% HOV growth; 43% ad impression growth
  • EMEA: 22% HOV growth; 43% ad impression growth
  • U.S. & Canada: 17% HOV growth; 22% ad impression growth

The U.S. & Canada continue to account for the largest share of global FAST HOV and ad impressions, though international markets are steadily gaining share. Genre trends remained consistent, with Entertainment and News ranking as the top two categories globally. New channels launched after December 2024 contributed 18% of global HOV and 16% of global ad impressions in the quarter, underscoring continued platform expansion and content diversification.

The report concludes that applied AI may represent the next structural shift in media operations — potentially as transformative as streaming was to distribution.

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Pyler to Take Center Stage at NVIDIA GTC 2026, Advancing Leadership in Video T&S and Brand Suitability

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TwelveLabs Launches Ecosystem Partner Program to Extend Video Intelligence in the Enterprise

Pyler - 팀쿠키 Team Cookie

From the stage to the show floor, Pyler is making its mark at the AI industry’s most anticipated event of the year.

Pyler is set to make a high-profile debut at NVIDIA GTC 2026 this March in San Jose. The video understanding specialist will showcase its technology through a technical talk, a poster reception, and a dedicated exhibition booth.

GTC has evolved into the definitive forum for the global AI industry, far outgrowing its roots as a corporate event. With NVIDIA’s GPUs now the lifeblood of AI development, GTC 2026 is poised to be a massive draw for the sector’s top-tier researchers and investors.

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Pyler’s Presence at GTC 2026

Pyler’s participation begins on March 15, one day before the official conference opening. Pyler Research Lab will lead a poster reception titled “Scene-Aware Summarization for Long-Form and Multi-Video RAG,” pushing the boundaries of how AI interprets and retrieves complex video data.
Throughout the week, Pyler will operate its exhibition booth as a hub for industry dialogue and host a private happy hour for stakeholders. The team is prepared to demo its technical roadmap and real-world impact in Trust & Safety (T&S) and Brand Suitability, areas where Pyler is rapidly setting new benchmarks.
On March 19, the spotlight shifts to CEO Jaeho Oh. Taking the stage at GTC, his talk, “Scaling Trustworthy Multi-Modal Video Intelligence,” will peel back the curtain on how Pyler builds robust AI systems for high-stakes commercial environments.

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Accelerating Video AI Development with NVIDIA

Pyler has accelerated its growth by leveraging NVIDIA’s cutting-edge technology since its founding in 2021. The company made waves in early 2025 as the first in Korea to deploy the NVIDIA Blackwell DGX B200 system. That momentum continued as Pyler secured the grand prize at the 2025 NVIDIA Inception Startup Grand Challenge, beating out a field of over 80 competitive startups.
“GTC is the perfect stage to demonstrate the massive scale of video processing we’ve mastered alongside NVIDIA,” says a Pyler spokesperson. “We aren’t just participating; we’re here to cement our leadership in the video T&S space and scale our partner ecosystem globally.”

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Market Logic Network Launches OpenAPI Integration for Zoho CRM to Deliver Pan-European B2B Company Intelligence

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Market Logic Network Launches OpenAPI Integration for Zoho CRM to Deliver Pan-European B2B Company Intelligence

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New integration enables real-time company data enrichment, AI lead qualification, and cross-border B2B intelligence directly inside Zoho CRM.

Market Logic Network LLC announced the launch of a new business intelligence integration connecting Zoho CRM with the international company data platform OpenAPI.

B2B teams can no longer afford to operate with incomplete data. Our systems provide verified company intelligence directly inside the CRM before the first conversation begins”

— Jordi Argomaniz, Co-Founder

The new integration allows businesses to automatically enrich CRM records with verified company data from official registries across Europe and other global jurisdictions. The system delivers real-time company intelligence directly within Zoho CRM, enabling organizations to automate lead qualification, improve CRM data accuracy, and streamline cross-border B2B sales operations.

Solving the B2B Data Intelligence Gap

Businesses increasingly operate in international markets, yet company data remains fragmented across national registries and government databases.
Sales and marketing teams often spend hours verifying company legitimacy, researching ownership structures, and confirming whether a potential client meets their ideal customer profile.

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Research consistently shows that poor CRM data quality has a measurable impact on revenue performance:

– Nearly 40% of CRM records contain incomplete or outdated information
– Sales professionals can spend up to 30% of their time researching company data
– Inaccurate data reduces conversion rates and inflates pipeline metrics

Market Logic Network’s integration introduces an automated data enrichment layer designed to solve this problem at the infrastructure level.
When a new lead or account is created in Zoho CRM, the system automatically retrieves verified company information and populates the CRM record with standardized business data.

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Multi-Country Business Intelligence Inside Zoho CRM

The OpenAPI platform aggregates business data from official government registries and national financial filing authorities across multiple countries.

Through Market Logic Network’s integration, companies can access structured company intelligence across several European markets including: Italy, Germany, France, the United Kingdom, Spain, Austria, Belgium, Switzerland, Poland, and Portugal.

The platform also includes EU VAT validation capabilities and a global company lookup endpoint capable of retrieving company information across nearly any jurisdiction worldwide. This unified architecture allows businesses to standardize company intelligence across multiple markets without switching between different national data sources.

Key Capabilities of the Integration:

The new integration introduces several capabilities designed to improve CRM performance and operational efficiency for B2B organizations.

– Automated Company Enrichment
CRM records are automatically populated with verified company data such as legal status, tax identifiers, registered addresses, and operational status.

– Financial and Ownership Intelligence
For supported jurisdictions, the platform provides access to financial filing data, shareholder structures, director roles, and Ultimate Beneficial Owner disclosures.

– AI Powered Lead Qualification
Market Logic Network’s custom AI agents can analyze enriched company data to automatically score and prioritize leads based on configurable business criteria.

– Advanced Marketing Segmentation
Marketing automation systems can segment campaigns using verified company attributes such as industry sector, company size, and geographic territory.
Real-Time Business Monitoring

Companies can track changes in ownership structures, legal status, or financial filings and receive automated alerts directly within Zoho CRM.

Enabling Data-Driven B2B Growth

The integration is designed to support organizations that rely heavily on accurate company intelligence, including financial services firms, SaaS companies, consulting firms, exporters, and international B2B sales teams. By embedding company intelligence directly into the CRM infrastructure, organizations can improve sales productivity, strengthen compliance processes, and make faster decisions based on verified data.

Market Logic Network states that the integration is part of a broader initiative to create intelligent automation ecosystems where CRM systems, artificial intelligence, and real-time company data operate as a unified business platform.

Future Development Roadmap

According to the company, the OpenAPI integration represents the first major step in a broader roadmap focused on automation and AI-driven business intelligence. Future development plans include expanded financial intelligence coverage across additional European markets, AI-driven predictive lead scoring models, automated deal-flow workflows triggered by company status changes, and deeper integrations with marketing and advertising platforms.

The company also plans to release pre-built automation templates connecting the system with additional tools used by modern sales and marketing teams.

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aiXplain Introduces aiXplain Studio

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Glow.B Unveils AEO And GEO Solutions for the Generative AI Search Era

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aiXplain Studio is the no-code platform for building production-grade AI agents, designed for speed, built for teams, and never without control.

aiXplain introduces aiXplain Studio. A new way to build intelligent agents. built for speed, built for teams, and built for control.

aiXplain announced aiXplain Studio, a no-code platform that moves AI agent development from a specialized engineering effort to an organization-wide capability.

aiXplain Studio replaces static, pre-wired workflows with intelligent agents that plan, adapt, and orchestrate tasks dynamically at runtime, so teams can collaboratively build and quickly deploy production-grade agents.

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Many agent platforms start with flow diagrams, routers, and switches. aiXplain Studio moves beyond that. It frees builders to focus on outcomes, not wiring. Teams define the objective, attach tools, and set governance rules, then aiXplain Studio adapts in real time as requirements evolve. That is possible because aiXplain’s governance architecture enforces quality and policy at runtime with full traceability, so aiXplain Studio stays built for speed, built for teams, and built for control.

aiXplain Studio is organized around four core experiences: Browse, Build, Validate and Observe.

Browse
Instant access to production-ready assets, including 200+ AI models and 600+ commercial integrations like Snowflake, Slack, Jira, and Google Drive. Bring your own tools and data with secure Python sandboxes, SQL connectors for structured databases, document indexing for RAG knowledge bases, and MCP connections for third-party services.

Build
A no-code workspace for configuring single agents or multi-agent systems. Choose a model, define instructions, and attach tools with granular permissions and action controls. Built-in micro-agents handle planning, orchestration, inspection, and response. Inspectors continuously enforce quality and policy.

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Validate
Real-time debugging and observability. Trace execution step by step, including what ran, which tools were called, what decisions were made, what Inspectors evaluated, what each step cost, and how the full system behaved end to end.

Observe
Continuous operational visibility and control across agent deployments. Teams can monitor runtime behavior, usage, latency, cost, and system health in real time, while managing access to assets, scoping API keys, and enforcing rate limits. This ensures secure, compliant, and observable agent operations at enterprise scale.

From build to production, without friction
Agents created in aiXplain Studio deploy instantly and securely to the cloud. Teams can integrate agents into existing applications through generated integration code, or interact with them directly through aiXplain’s built-in chat experience without additional development work.

“Agentic technology should not live in the engineering department” said Hassan Sawaf, CEO at aiXplain. “aiXplain Studio puts agent-building in the hands of every member of the team, without giving up governance, safety, or visibility. You move faster, you stay in control, and the agents match the way your business actually works.”

“aiXplain Studio reflects how modern teams actually want to build agents,” said Nur Hamdan, Head of Product at aiXplain. “Instead of forcing teams to map every path in advance, we designed aiXplain Studio around intent, autonomy, and runtime decision-making. Teams start with what they want done, and agents coordinate execution dynamically. Inspectors ensure quality, compliance, and policy alignment continuously, so teams can move fast without sacrificing control.”

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MarTech for Retail Growth: Why Manual Reviews Still Matter in an AI-driven Marketing World?

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MarTech for Retail Growth: Why Manual Reviews Still Matter in an AI-driven Marketing World?

Artificial intelligence and automation have changed the modern Martech ecosystem. It has changed how retailers plan, carry out, and judge their marketing efforts. In the last ten years, advanced marketing platforms have grown, allowing firms to automate complicated tasks that used to take a lot of time and effort. AI-powered technologies have made marketing operations more efficient, faster, and scalable, from analyzing data to improving campaigns. Because of this, businesses can now handle a lot of customer data, get insights more quickly, and provide more personalized marketing experiences across many digital channels.

One of the biggest advances AI has made to Martech is that it can now automate operations that are boring and require a lot of data. More and more, retailers use automated tools to run their campaigns, find customers, and analyze their marketing data. Modern marketing systems may automatically divide consumers into groups based on their behavior, preferences, and buying habits. These technologies look at how customers engage with each other in real time and let marketers provide targeted messages through email campaigns, social media ads, mobile notifications, and website experiences. Digital advertising platforms with automated bidding systems can also improve ad placements and budgets by constantly learning from data on how well campaigns are doing.

Automation has also made it easier for merchants to run big campaigns with more accuracy. AI-powered systems can look at millions of data points to figure out which audiences are most likely to buy, which marketing channels give the best return on investment, and which content connects with customers the best. Dashboards that show real-time information and forecast insights let retailers keep an eye on how well their campaigns are doing. Marketing teams may make decisions faster and respond rapidly to changes in consumer behavior with this level of automation. In retail settings where there is a lot of competition, automated MarTech systems can provide you a big edge by making things faster and easier.

Even with these technical improvements, automation can’t completely replace human judgment. AI systems are great at processing data and finding patterns, but they typically don’t have the contextual knowledge needed to make strategic decisions. Brand positioning, client emotions, cultural trends, and long-term business goals are all things that affect marketing tactics. Human knowledge is very important in these areas. Most automated systems work by using algorithms and past data, which means they could miss changes in the market that are happening now or misread strange patterns in how people behave.

This constraint shows how important it is to find a balance between automation and human review in marketing technologies. Retailers need to make sure that automated procedures are checked on a regular basis and fit in with the company’s overall plans. Automated systems can’t readily copy the critical thinking, creativity, and grasp of context that human marketers have. They may interpret information, examine assumptions, and change strategies to make sure that marketing technology continues to help businesses reach their goals.

This is where the idea of doing manual MarTech reviews really comes in handy. An organized review of Martech systems, data flows, campaign processes, and performance metrics is what a manual MarTech review is all about. Marketing staff can find inefficiencies, integration problems, and lost opportunities that automated systems might not notice by looking closely at these parts. These reviews help stores figure out if their technology stack is being used correctly and if their campaigns are getting the outcomes they want.

In the end, manual MarTech assessments help retailers keep strategic control over marketing ecosystems that are getting more and more complicated. Businesses may get deeper insights, fix problems, and find new growth possibilities by using AI-powered technologies and human-led analysis together. Even if automation is taking over a lot of jobs, human monitoring is still very important to make sure that marketing technology really helps stores succeed in the long run.

The Rise of AI in Marketing Technology

Artificial intelligence is a big reason why modern marketing technology is changing so quickly. In the last several years, stores have been using more and more powerful systems that let them automate complicated tasks, look at huge amounts of data, and give customers more tailored service. These new ideas have changed a lot about how organizations plan their marketing, run their campaigns, and look at their results. Because of this, Martech‘s position in retail has grown from just being a set of marketing tools to a complex ecosystem that combines data, automation, and predictive intelligence.

Retailers can run their businesses more efficiently and learn more about how customers act with the help of AI-powered Martech systems. These systems can find patterns, predict trends, and help marketers make better decisions by using machine learning algorithms and a lot of customer data. Retailers used to have to do their own analysis by hand, but now they utilize smart platforms that learn from new data all the time and improve their suggestions over time.

  • Predictive Analytics for Customer Behavior

Predictive analytics is one of the most useful ways that AI may be used in retail marketing. Predictive models look at past data, how people browse, how they buy things, and how engaged they are to guess what customers will do in the future. Retailers can use these insights to figure out what customers will want, find high-value groups of customers, and figure out which products are most likely to appeal to certain groups of people.

Modern Martech systems provide predictive analytics tools that let marketing teams go from making decisions based on what has already happened to creating plans for the future. For instance, stores can guess when a consumer is likely to buy something again or find shoppers who could be about to stop shopping. These insights help organizations create customized ads that keep customers coming back and raise their lifetime value.

  • Automated Ad Bidding and Campaign Optimization

AI is also changing the way digital advertising is managed by making it automatic. Retail marketers generally run ads on a number of different channels, such as search engines, social media sites, and display networks. It might take a lot of time to manually manage bids, budgets, and targeting settings across different channels.

Automated ad bidding and campaign optimization are two ways that AI-powered Martech solutions help with this problem. These technologies look at campaign performance data in real time and change the way they bid to get the best results. They can set aside money for advertising that does well, stop campaigns that don’t do well, and keep improving their targeting tactics.

Retailers may spend less on advertising and get better results from their campaigns by using smart automation. Instead of spending hours changing campaign settings, marketing teams can spend more time on big-picture strategy while the technology takes care of operational optimization.

  • AI-Driven Personalization and Recommendations

In the retail industry, personalization has become a major competitive edge. People are more and more expecting firms to give them relevant product suggestions, personalized discounts, and tailored information in all of their digital interactions. AI-powered personalization solutions let you address these needs on a large scale.

Advanced Martech platforms look at each customer’s preferences, purchasing history, and browsing habits to make individualized product suggestions. You can find these suggestions on websites, in email campaigns, or in mobile apps. Retailers can get customers to buy more often and engage with them more by giving them content that is really relevant to them.

AI also lets you personalize your marketing across numerous channels in real time. For instance, email marketing tools can automatically change the messages they send based on different groups of customers. Similarly, website experiences can change in real time based on how users act. This level of customisation lets stores have more meaningful conversations with their customers.

  • Marketing Automation Platforms

Another significant part of modern retail marketing ecosystems are marketing automation solutions. These tools make it easier to do marketing chores that have to be done again and again, such as sending out emails, nurturing leads, dividing customers into groups, and planning campaigns. Retailers can make sure they always talk to their consumers by automating these tasks, which also cuts down on the amount of labor they have to do by hand.

AI-powered Martech automation tools take things a step further by figuring out the best times to communicate, suggesting different types of content, and looking at engagement metrics. They help marketing teams get the correct message to the right people at the best time. This not only makes things run more smoothly, but it also makes it more likely that people will convert.

Automation also makes sure that marketing initiatives are still going on at the same time across many touchpoints. Retailers can make sure that their messages are consistent throughout email, social media, SMS, and internet interactions, giving customers a seamless and unified experience.

  • Scaling Campaigns and Processing Massive Data

One of the best things about AI-driven Martech is that it can swiftly handle a lot of data. Retailers get information from a lot of different places, like online sales, website analytics, loyalty programs, and social media interactions. It would be almost impossible to look at this information by hand.

AI-powered Martech systems can look at millions of data points in seconds and find trends and insights that would otherwise go unnoticed. This feature helps stores run bigger marketing campaigns while still being accurate in their targeting and messaging.

For instance, businesses who run big marketing campaigns can use automated analytics to keep an eye on how well they’re doing in different areas, with different types of customers, and through different marketing channels. These insights let organizations change their plans on the fly and make sure that their marketing spending pays off.

Increasing Adoption in Retail Marketing Ecosystems

More and more retailers are using AI-powered marketing tools every day. To stay competitive in a market that is becoming more data-driven, businesses of all sizes are adding smart tools to their marketing stacks. Companies, from big global retailers to new e-commerce enterprises, are seeing the strategic importance of modern Martech platforms.

These technologies are getting more connected and easier to use as they change. Retailers can now combine several marketing tools into single platforms that handle customer data, automate campaigns, and give useful information. This integrated environment lets marketing teams work more strategically and quickly respond to changes in how people act.

In the end, the rise of AI-powered Martech solutions is a big change in how retail marketing works. Retailers can make their marketing more effective and give customers better experiences in a very competitive digital marketplace by using automation, predictive analytics, and personalization.

What Automated MarTech Tools Can’t Do?

AI and automation have made modern marketing systems much more efficient. Retailers today use modern Martech tools to run campaigns, look at data, and improve the effectiveness of their marketing. These tools let organizations run big marketing campaigns quickly and accurately, which would be hard to do by hand.

Even though automated marketing systems provide a lot of benefits, they do have some drawbacks. Martech systems can handle big numbers and find trends, but they don’t necessarily know the bigger picture behind how customers act or how a firm plans to grow.

Automation works best with data that is structured and processes that are clear. But marketing typically involves complicated human behavior, making decisions based on feelings, and markets that change quickly. This is why automated Martech systems often have trouble figuring out deeper insights that need human judgment. Retailers who want to use technology well without relying on it blindly need to be aware of these limits.

  • Lack of Contextual Understanding of Customer Behavior

Automated Martech systems have a big problem: they can’t fully grasp why customers do what they do. AI systems can look at things like browser history, purchase history, and engagement data, but they can’t simply figure out why people do what they do or how they feel about it.

A customer could cease buying something not because they are unhappy, but because their demands have changed for a short time. Automated systems can wrongly put this consumer in the “unprofitable” or “disengaged” category. Such mistakes can lead to unsuccessful targeting techniques or badly timed advertising if people don’t look at them.

To be successful in retail marketing, you need to know about cultural trends, changes in the seasons, and other things that affect how people buy things. People who work in marketing can see these patterns and change their plans to fit them, while automated Martech systems might not be able to spot these small changes.

  • Misinterpretation of Data Patterns

Automated systems are made to find patterns in big datasets, however these patterns aren’t always useful or correct. When there are other factors that affect how customers act, correlations in data can be misleading.

For example, a Martech platform can see a lot of activity for a certain campaign and think that the content is doing well. But the rise in activity could be caused by things that have nothing to do with it, such seasonal demand, promotions from competitors, or general market trends.

Because automated systems depend so much on statistical relationships, they may sometimes mistake short-term trends for long-term insights. Marketers who are people are very important for making sure that these findings are correct and that decisions are based on correct interpretations of the facts.

  • Over-Optimization Based on Incomplete Datasets

Another problem with automated Martech systems is that they often over-optimize campaigns when they use incomplete or broken datasets. A lot of marketing platforms simply look at the data that is available in their own systems, which may not show the whole client journey.

For instance, a platform might improve digital ads based only on online interactions, not taking into account offline purchases, customer service interactions, or brand engagement as a whole. This narrow view can lead to plans that seem to work in short-term reporting but don’t help long-term marketing goals.

Too much optimization might also lead to sending the same message over and over again or targeting the same client groups too much. Algorithms try to get the most conversions in the short term, but they could make customers tired or miss chances to reach new audiences. To make sure that marketing initiatives stay in line with the company’s overall goals, a balanced Martech strategy needs to be overseen by people.

  • Limited Ability to Evaluate Creative Strategy and Brand Messaging

Data analysis and campaign performance measures alone do not define marketing success. Creative storytelling, emotional connection, and brand positioning are all very important when it comes to getting people to buy something. Sadly, automated Martech systems can’t do a good job of judging how good or useful creative content is.

Algorithms can figure out how many people are interested in a campaign, how many people click on it, and how many people buy something, but they can’t tell if a campaign really connects with people on an emotional level. They also can’t tell if a brand message fits with the brand’s long-term identity and position.

When people evaluate, they use their imagination, gut feelings, and strategic thinking. They make sure that marketing activities support brand values and develop meaningful interactions with customers by looking over campaign messaging and creative materials. This human point of view is still an important addition to computerized Martech analytics.

  • Algorithm Dependence and Market Complexity

Most automated marketing platforms use machine learning models and algorithms that have already been set up. These models use past data and programmed logic to provide suggestions. This method works well in calm situations, but it might not perform as well when the market changes quickly.

There are many things that can change in retail marketplaces that are hard to forecast, such as changes in the economy, societal trends, and what competitors do. Automated Martech systems might not see these changes right away, which could mean using old techniques or missing out on chances.

Human marketers are better at understanding complicated market situations and changing their marketing plans as needed. Their ability to use data insights in real-world situations helps keep marketing plans useful and up-to-date.

The Need for Balanced Technology Use

Automated Martech tools are very efficient and powerful for analysis, but they can’t completely replace human expertise. Retailers who rely only on automation could miss important information that needs strategic thought and understanding of the situation.

The best marketing plans use both technology and the knowledge of professional marketers to get the best results. Companies may utilize Martech more responsibly and make sure that their marketing activities keep supporting sustainable retail growth by knowing where automation doesn’t work.

Why Manual MarTech Reviews Are Important?

As marketing technology gets better, merchants are using more and more advanced tools to run campaigns, look at data, and improve customer interaction. Automated platforms can be faster and more scalable, but they can’t totally replace human evaluation. This is when manual Martech reviews come in handy. These assessments give you a way to look at marketing systems, find areas where they aren’t working as well as they should, and make sure that technological investments are in line with the company’s overall goals.

When you do a manual Martech study, you look closely at the marketing technology stack that a company uses. This process involves looking at platforms, integrations, workflows, campaign management systems, and data pipelines to make sure everything is working well. Experts don’t just look at automated dashboards or AI-generated data; they also look at the procedures that make marketing work. This study done by people lets organizations find problems that automated systems might miss.

Understanding the Role of Human Expertise

In today’s retail world, marketing systems generally use many different platforms that work together. These platforms include advertising tools, analytics software, consumer data platforms, and automation systems. Experts might do a manual Martech assessment to see how these systems work together and if they are getting the outcomes they want.

People who work in marketing look at how marketing workflows are set up, how data moves between platforms, and how campaigns are being run on multiple channels. They can find problems in processes, find misconfigured marketing platforms, and make sure that the technological stack is helping the organization reach its goals instead of making things more complicated than they need to be.

Automated systems use pre-defined algorithms, but human specialists use their knowledge of the situation and their ability to think critically to evaluate. They think about things like how the market is doing, where the brand stands, how customers are acting, and the company’s goals. Retailers may make better choices about how to spend their money on marketing technologies when they look at the whole picture.

  • Identifying Hidden Inefficiencies

One of the best things about doing manual Martech evaluations is that they can help you find hidden problems in your marketing operations. Automated reports might show how well a campaign is doing, but they don’t always show where operations are getting stuck or where there are unnecessary steps.

For instance, several technologies in a marketing stack might do the same thing, which would add extra costs and duplicate work. A manual review can find these overlaps and suggest ways to combine them that make the whole system easier to use. Also, specialists can find old practices that make it harder to run a campaign or make marketing less flexible.

Retailers can make their Martech ecosystem more efficient and make sure their technologies are functioning together well by finding these problems.

  • Verifying Data Accuracy and Integration Issues

Good marketing strategies depend on having accurate data. But when information moves across different platforms or when systems aren’t well connected, data discrepancies might happen. Automated tools might handle this data without noticing any quality problems that are hidden.

Manual Martech assessments are very important for making sure that data is correct throughout the marketing ecosystem. Analysts check how consumer data is gathered, kept, and shared throughout platforms to make sure it is accurate and consistent. They can also find difficulties with integration that lead to duplicate data, inconsistent reports, or incomplete client profiles.

By fixing these problems, marketing teams may be sure that they are making judgments based on correct information instead of bad data.

Evaluating Marketing Performance Beyond Automated Reports

Automated marketing platforms usually make performance reports based on set parameters like click-through rates, conversions, and levels of engagement. These indicators give us vital information, but they don’t necessarily show us the whole picture of how well our marketing is working.

Experts might look at marketing performance from a strategic point of view when they do manual evaluations. They look at whether campaigns fit with the company’s bigger goals, whether the messages speak to the target audience, and whether the money spent on marketing is worth it in the long run. Manual Martech assessments give a more complete picture of marketing results by integrating data analysis with strategy appraisal.

Maintaining Control Over the Marketing Technology Stack

As retail companies add more digital tools, their marketing technology stacks are getting harder and harder to use. If you don’t check these systems on a frequent basis, they can become hard to administer and may not give you the value you want.

Retailers may keep control of their technological environment by making sure that tools, integrations, and workflows are still in line with business needs through manual martech audits. These studies help companies get the most out of their technological investments, make their operations more efficient, and promote long-term marketing growth.

In the end, automation is still a big part of modern marketing, but human-led Martech evaluations make sure that technology continues to help achieve strategic goals and produce useful commercial results.

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Key Areas Where Human Analysis Adds Value

As automation becomes increasingly popular in marketing, many stores rely on complex Martech solutions to run campaigns, keep an eye on consumer behavior, and look at performance data. These technologies make marketing systems faster, more efficient, and more scalable. But there are still some sectors where human expertise is quite important. Martech systems can look at huge amounts of data and automate tasks that need to be done over and over again. However, human marketers can comprehend the context, be creative, and think strategically in ways that technology can’t.

Human analysis helps businesses understand the insights that Martech tools give them, check the accuracy of automated suggestions, and make sure that marketing decisions are in line with the company’s overall goals. Retailers can get better results and keep their marketing plan balanced by using data-driven technology and professional evaluation together. The next parts will talk about important areas where human knowledge makes modern Martech ecosystems work much better.

a) Evaluating the Customer Experience

One of the most crucial things that makes a store successful is how well it treats its customers. Martech platforms can keep track of things like click-through rates, conversion rates, and engagement levels, but they frequently can’t completely understand the emotional and contextual variables that affect how customers act.

Human analysts can look at input from many places, like customer reviews, polls, support encounters, and social media chats, to find out more about what customers want and how happy they are. These qualitative insights go along with the numbers that Martech products collect.

An automated Martech system, for instance, might notice that the number of conversions on a website is going down. The platform can show the pattern, but it might not be able to properly explain why it happened. Human marketers can look into the problem more by reading customer reviews, looking at user journeys, and finding possible spots of friction in the buying process.

Marketers can also use human evaluation to see small changes in how people feel about a product. Changes in consumer preferences, cultural trends, and the seasons can all affect how people see a brand. Martech analytics can find changes in behavior, but people need to interpret those findings in order to turn them into useful tactics that make the customer experience better overall.

Retailers may make marketing plans that are based on both data-driven patterns and what customers really want by using both automated insights and human knowledge.

b) Review of Content and Creative Strategy

Creative narrative is still a key part of marketing that works. Martech platforms can tell you how well your marketing materials are doing, but they can’t properly judge the quality or emotional effect of creative content.

People who work in marketing offer creativity, gut feelings, and knowledge of brands to the process of evaluating material. They can figure out if marketing communications fit with the brand’s identity, speak to the right people, and tell the story they want to tell.

Automated Martech analytics can tell you which ads get the most hits or conversions, but they don’t necessarily say why some material does better than others. Human experts can look at the tone of the messaging, the visual storytelling, and the consistency of the design to see if the creative elements help with long-term brand positioning.

For example, a store might run several different ads advertising a seasonal sale. Martech platforms can quickly find the best version based on engagement data, but human marketers may look at the messaging style, images, and emotional appeal that made that campaign a success. These insights assist teams improve their future creative plans and keep the brand language constant.

Human evaluation also makes sure that marketing strategies are still relevant to the culture and morally sound. Brands need to be careful about how they connect with different groups of people in different parts of the world. This will help them prevent misunderstandings or unintentional messaging clashes.

In the end, human creativity and Martech data work together to make campaigns that connect with people and generate stronger brand connections.

c) Campaign Plan and Budget Distribution

Careful planning and resource allocation are needed for marketing efforts. Martech platforms can automatically improve bidding methods and change campaign settings, but a human specialist is still needed to make sure that campaigns are in line with the company’s overall goals.

Before starting a campaign, marketers look at the goals, target audiences, and long-term business goals. They use data from Martech analytics to help them make decisions, but they employ their own strategic judgment to figure out the best way to promote their products.

For instance, a Martech system can suggest putting more money into a certain advertising channel based on how well it has done recently. But human analysts might realize that the rise in performance is only transient or caused by short-term trends. Marketers may make better investment choices by looking at market conditions, what their competitors are doing, and their brand goals.

When you plan your budget strategically, you also look at how each marketing channel helps your overall revenue growth. Automated Martech statistics may show how well each campaign is doing on its own, but a human’s analysis may show how all the efforts work together to support the whole marketing funnel.

People in charge make sure that marketing investments are in line with both short-term outcomes and long-term brand growth. This balance helps businesses get the most out of their marketing investments while keeping their marketing strategy going for a long time.

d) Fraud Detection and Risk Assessment

Digital marketing settings are becoming more and more open to scams like click fraud, bot traffic, and fake impressions. Martech systems have built-in ways to automatically find fraud, yet complex fraud patterns may still get beyond these protections.

Human analysts are vital for looking into strange data patterns and finding problems that automated methods might miss. For instance, a sudden increase in website traffic from a certain area may look good on a Martech monitor. But a human analyst may find that the traffic is coming from artificial bots instead of real people when they look more closely.

Marketing teams can better judge the integrity of a campaign with the use of human knowledge. Analysts can look at where traffic comes from, how people interact with the campaign, and check to see if the results are real.

Companies may lower the chance of fraud and keep their marketing performance data accurate by using both automated detection systems and human assessment. This teamwork approach makes sure that Martech analytics are still dependable and trustworthy.

e) Data Quality and Integration Checks

There are frequently many different technology platforms in retail marketing ecosystems. These include analytics tools, customer relationship management systems, advertising platforms, and e-commerce software. These systems make a lot of data that needs to be combined and synced so that it can be analyzed correctly.

Martech platforms are meant to handle data flows on their own, yet problems with integration can still happen. If you don’t fix inconsistent data formats, duplicate records, and inadequate datasets, they could mess up marketing insights.

Human analysts do regular Martech checks to make sure that data from multiple sources is valid and linked correctly. They check for differences in reporting metrics, look at how well data pipelines work, and look at how well different platforms work together.

For instance, a retailer’s Martech stack might gather customer information via website visits, email marketing, loyalty programs, and transactions made in the shop. Human review makes sure that these data sources are combined correctly to make a single consumer profile.

By accurately combining data, marketing teams can get a full picture of the consumer journey and come up with better plans. Without human monitoring, fragmented datasets can give you false information and cause you to make bad marketing judgments.

Combining AI Tools with Human Expertise

The best retail companies use a mix of automation and human expertise to stay ahead of the curve as marketing technology changes. Martech technologies give you the computing capacity you need to work with huge datasets, automate boring operations, and get analytics in real time. At the same time, human marketers bring creativity, strategic thinking, and the ability to understand things in context that technology can’t copy.

This partnership between technology and human knowledge makes for a balanced marketing environment where Martech solutions take care of operational efficiency and experts make strategic decisions.

a) AI for Data Processing and Automation

One of the best things about modern Martech platforms is that they can swiftly process a lot of data. AI-powered systems look at how customers engage with websites, mobile apps, social media, and advertising networks.

Automated Martech solutions can split up audiences, find the best places to put ads, and make predictions about how customers will act in the future. Retailers can conduct big campaigns with little manual work thanks to these features.

Martech technology frees marketing teams to focus on strategic planning and creative creation by automating processes that are done over and over again, such designing campaigns, analyzing data, and reporting on results.

b) Human Strategic Control

AI-driven marketing technology solutions are great at finding trends, but they often need a person to make sure that the insights are used correctly. Marketing professionals look over automated suggestions and decide if they fit with the company’s overall aims.

People in charge make sure that marketing plans can still work in the real world. Analysts can query automated insights, check out strange tendencies, and add outside aspects that computers might not see.

For example, a Martech platform can suggest spending more on ads because engagement rates are going up. But human analysts might be able to find other factors, such seasonal trends or promotions from competitors, that affect how well a campaign works. Their strategic view makes sure that marketing spending stays in line with long-term goals.

c) Collaborative Marketing Workflows

More and more businesses are using AI systems and marketing specialists to work together. Retail teams often use Martech dashboards to look at how well their campaigns are doing and find ways to make them better.

Marketing teams might start by looking at the automated insights that Martech analytics tools give them. Then they use what they know to make sense of the outcomes, change the campaign plans, and come up with fresh marketing ideas.

Doing regular Martech audits is another crucial part of working together. These reviews make sure that technology systems stay in line with corporate goals and keep giving correct information. Retailers may run their marketing activities more efficiently and keep strategic control over their technology environment by combining human experience with automated systems.

The Future of Retail MarTech

Data, automation, and artificial intelligence are driving the retail industry into a new phase of digital transformation. As customers’ needs change, businesses are using advanced Martech solutions to provide more personalized, efficient, and interesting experiences in both digital and physical channels. The future of Martech will be shaped by improved data integration, smarter automation, and more advanced marketing intelligence that lets merchants understand and serve their customers better than before.

Martech platforms will get stronger and more linked as technology keeps getting better. Retailers will depend more and more on integrated ecosystems that bring together AI-driven solutions, consumer data platforms, and analytics to make marketing operations run smoothly. These platforms will let businesses look into complicated client journeys in real time, find new ways to connect with customers, and run very focused marketing efforts on a large scale.

  • More Advanced AI-Driven Personalization

The rise of AI-driven personalization is one of the most crucial themes that will shape the future of Martech. These days, people expect brands to know what they like and give them experiences that are relevant to their needs. With advanced Martech systems, stores will be able to have very individualized conversations with customers based on their behavior, purchase history, browsing trends, and engagement data.

AI will let Martech platforms look at a lot of client data and make personalized product suggestions, tailored promotions, and dynamic content experiences. For instance, a store’s website or mobile app might automatically change the way it shows products based on what a client has bought or looked at in the past.

This level of customisation will go beyond digital platforms. Retailers will be able to send individualized messages through email campaigns, social media ads, loyalty programs, and in-store experiences. Because of this, Martech systems will be very important for making sure that customers have consistent and meaningful interactions with your business at all of its touchpoints.

  • Integration of Customer Data Platforms (CDPs)

The expanding use of Customer Data Platforms (CDPs) is another big change that will happen in the future of Martech. Retailers often get information from a lot of different places, such as e-commerce sites, mobile apps, social media, transactions in stores, and conversations with customer care. If you don’t integrate this data correctly, it can stay spread out across different systems.

More and more, modern Martech ecosystems will use CDPs to combine different data sources into one unified consumer profile. Marketers may better comprehend the whole client lifecycle and come up with better marketing plans with this unified picture.

Retailers may learn more about how customers act, spot trends across numerous channels, and make better segmentation strategies by adding CDPs to their Martech stack. This integration will let marketing teams work together on campaigns across platforms while still keeping track of what customers like and how they have interacted with the brand in the past.

  • Predictive Marketing Models

Predictive analytics will also be very important for the growth of Martech. Future marketing technologies will focus more on predicting customer behavior and finding chances before they happen, rather than just looking at how things have gone in the past.

Predictive Martech models employ machine learning algorithms to look at past data and make predictions about what customers will do in the future. These technologies can assist stores figure out which people are most likely to buy something, which products might become popular, and which marketing methods are most likely to work best.

For instance, predictive Martech systems can spot early signs of customer churn, which lets merchants start targeted retention programs before consumers leave. Predictive models can also help firms make the best use of their inventory, timing of promotions, and product suggestions.

As predictive skills get better, Martech platforms will help retailers switch from reactive marketing to proactive decision-making. This will give them an edge over other businesses in marketplaces that change quickly.

  • Data strategies that protect privacy

As Martech systems keep using client data a lot, privacy and data protection will become ever more crucial. Governments and regulatory organizations all over the world are making data privacy rules tighter. These regulations oblige firms to be responsible with customer data.

Data practices that put privacy first will become more important in future Martech efforts. Retailers must make sure that they acquire customer data in a clear way, keep it safely, and utilize it in a way that follows changing rules. This means getting unambiguous permission from customers, using safe data management methods, and being more open about how personal data is used in marketing.

Martech solutions that focus on privacy will also help the trend toward first-party data strategies flourish. Retailers will stop using third-party tracking technologies a lot and instead focus on creating direct relationships with customers and getting data through loyalty programs, subscriptions, and one-on-one encounters.

The Continued Importance of Human Oversight

Automation and AI will keep making Martech better, but people will still need to be experts. As Martech ecosystems get more complicated, marketing experts will be very important for making sense of data insights, judging automated suggestions, and making sure that marketing plans fit with the company’s overall goals.

AI systems can swiftly find patterns in huge volumes of data, but they still need people to give them context and tell them what to do. Marketing experts will be in charge of putting data-driven insights into plans that can be put into action and that are based on what customers want and what is really going on in the market.

People will also need to watch over Martech systems to make sure they are used in a responsible and ethical way. Marketing leaders will have to find a balance between automation and openness, innovation, and customer trust.

  • Building the Next Generation of Marketing Ecosystems

The future of Martech in retail will depend on how well companies can use both advanced technology and human knowledge together. Companies that can successfully combine AI-driven automation, predictive analytics, and unified data platforms will have strong tools for getting to know and connecting with their consumers.

At the same time, creativity, strategic thinking, and ethical monitoring will still be very important for marketing to work. Retailers that embrace both new technology and human understanding will be best able to create strong marketing ecosystems that support long-term success.

In the next few years, Martech will be more than just using new technologies. Instead, it will focus on making smart, connected marketing environments where data, automation, and human expertise work together to give customers great experiences and help businesses succeed in the long run.

Conclusion

Digital technology is moving quickly, and this has changed the way stores offer their products in a big way. Businesses can now run campaigns faster, more accurately, and more efficiently thanks to artificial intelligence, automation, and advanced analytics. Retailers can now use modern Martech platforms to handle huge amounts of data, automate processes that need to be done over and over again, and improve their marketing plans in real time.

Companies who wish to stay competitive in a market that is becoming more data-driven need these technologies. AI-powered solutions make retail marketing much easier. They help firms run their campaigns on more than one channel, look at client behavior in great detail, and find trends that might not be obvious otherwise. Martech solutions can handle complicated tasks like audience segmentation, personalized recommendations, and ad optimization thanks to automation. This feature lets marketing teams send the correct messages to the right customers while doing less effort by hand.

Even while modern marketing technologies are smart and efficient, automation can’t completely replace the knowledge and skills of people. When making marketing decisions, you often have to figure out what the situation is, how customers feel, and what the company’s overall goals are. These are places where human intuition is still very important. Martech systems can give useful information, but people need to look at that information, question automated suggestions, and make sure that plans fit with long-term goals.

Manual evaluations and reviews guided by people are still very important for finding deeper insights that computerized reporting could miss. Retailers may find hidden problems, check the accuracy of their data, and make sure that their marketing technology stack is working properly by doing frequent Martech audits. These reviews also assist businesses figure out if their tools and processes are in line with their main goals. Also, people in charge of marketing can keep an eye on complicated technical ecosystems thanks to human oversight.

As companies use more advanced Martech platforms, the number of technologies and data sources that work together is growing. These systems can be hard to maintain and give false information if they aren’t watched closely and given strategic direction. People who know what they’re doing make sure that marketing technology keeps working toward corporate goals instead of just making automatic outputs. In the end, the best retail marketing tactics will use both technology and human knowledge in a balanced way.

AI and automation give you the computing power you need to look at big data sets and run campaigns on a huge scale. At the same time, human marketers have creativity, critical thinking, and an awareness of the context that technology can’t match. Retailers who use this mixed approach will be best able to develop in a way that lasts.

Businesses can make better marketing plans, give customers meaningful experiences, and quickly adjust to changes in the market by using Martech tools that are efficient while still having strong human oversight. In a retail world that is changing quickly, the companies that combine new technology with smart people will have the biggest edge over their competitors.

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Midaxo, the M&A Intelligence Platform, Has Been Named a Leader in the IDC MarketScape: Worldwide AI-Enabled Deal Management 2025 Vendor Assessment

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Indexly Announces Mission to Build the AI Visibility OS for the Modern Internet

Midaxo CEO, Founder, Key Executive Team, Board of Directors & Employees

Midaxo has been recognized as a Leader in the IDC MarketScape: Worldwide AI-Enabled Deal Management 2025 Vendor Assessment, highlighting the company’s platform for managing the full M&A lifecycle with AI-enabled insights.

Midaxo, the M&A intelligence platform for corporate development and deal teams, has been named a Leader in the IDC MarketScape: Worldwide AI-Enabled Deal Management 2025 Vendor Assessment (doc #US52999425, November 2025).

The IDC MarketScape vendor assessment evaluates technology providers based on their current capabilities and future strategies for supporting organizations across the deal lifecycle, with increasing focus on AI-enabled functionality, workflow automation, and governance.

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As deal volumes increase and transactions become more complex, organizations are moving beyond fragmented tools toward platforms that combine execution, insight, and control across the deal lifecycle. Midaxo supports this shift by delivering a single end-to-end platform that connects structured deal workflows with AI-enabled insights across strategy, pipeline management, due diligence, integration, and value realization.

“M&A teams are moving beyond systems of record toward systems of intelligence,” said Erica Magnegård, CEO of Midaxo. “Our focus has been to build an M&A intelligence platform that brings together data, workflows, and AI across the entire deal lifecycle. We believe being recognized by the IDC MarketScape reinforces that direction and the value we deliver to customers pursuing repeatable, programmatic growth.”

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Midaxo’s platform is designed to integrate with customers’ existing enterprise tools while serving as a system of record for deal execution, collaboration, and governance. By embedding intelligence directly into day-to-day deal workflows, Midaxo helps teams improve visibility, reduce risk, and deliver outcomes more consistently.

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Swayable CEO Appointed to Advertising Research Foundation Board of Trustees

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Swayable CEO Appointed to Advertising Research Foundation Board of Trustees

Swayable CEO James Slezak joins the ARF’s distinguished body of industry leaders shaping the future of advertising and marketing research.

Swayable, the causal AI platform used by the world’s top brands to measure the impact of their messaging, announced that CEO Dr. James Slezak has been appointed to the Advertising Research Foundation (ARF) Board of Trustees for 2026.

The ARF, founded in 1936, is the standard-bearer for unbiased research on the impact of media, marketing, and advertising. It counts among its membership more than 400 of the nation’s top advertisers, agencies, research firms, media companies, educational institutions, and international organizations. Trustees play a key role in guiding the ARF’s mission to further, through research, the scientific practice of advertising and marketing. As a trustee for 2026, Slezak joins industry peers from organizations including McCann, PepsiCo, Ipsos, IAB, Paramount, and Microsoft.

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“I’m honored to join the ARF Board of Trustees alongside so many distinguished leaders from across our industry,” said Slezak. “The ARF’s commitment to rigorous, evidence-based research is deeply aligned with Swayable’s own mission to measure the impact of the world’s most important messages. I look forward to contributing to the ARF’s vital work and to the conversations that will help the marketing industry make smarter, more impactful decisions.”

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Slezak’s appointment reflects Swayable’s growing influence in the marketing measurement landscape. The creative pre-testing platform has developed patented technology that uses randomized controlled trials (RCTs) and advanced machine learning to deliver Swayable Impact Scores—recognized by an increasing roster of major brands as the gold standard evidence of creative impact, that is, lift caused in consumer attitudes. Major brands, including Amazon, Airbnb, T-Mobile, DoorDash, and Paramount use Swayable to deploy creative tests.

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PagerDuty Expands AI Ecosystem to Supercharge AI Agents and Deliver Autonomous Operations

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PagerDuty Expands AI Ecosystem to Supercharge AI Agents and Deliver Autonomous Operations

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Strategic partnerships with Anthropic, Cursor and LangChain expand PagerDuty ecosystem to more than 30 AI partners across 11 categories to power the future of AI-first operations

PagerDuty, Inc. , a leader in AI-first operations management, announced the expansion of its AI integration ecosystem, marking a significant enhancement of its PagerDuty Advance agents and AI platform capabilities to help organizations enable autonomous operations. As development velocity increases and more AI code is generated, the industry faces a critical new challenge—to ensure code does not break in production. Today, PagerDuty has added more than 30 AI partners across 11 categories to its AI integrations website. Through this intuitive, searchable public web directory of integrations and agentic workflows, the PagerDuty Operations Cloud Platform and PagerDuty Advance Site Reliability Engineer (SRE) Agent seamlessly connect with leading AI-native platforms and SaaS enterprise applications and help organizations tackle the challenge of AI operations.

Enabling Critical Use Cases Across the Full Incident Management Lifecycle

PagerDuty’s expanded AI integration ecosystem transforms operations across multiple high-value scenarios. By ingesting rich observability telemetry, PagerDuty’s AI ecosystem powers a self-reinforcing context flywheel that enables automated triage with deep observability context—allowing, for example, PagerDuty’s SRE Agent to automatically correlate alerts, accelerate root-cause analysis and deliver more resilient operational outcomes.

The ecosystem also empowers developers and engineers to deliver more reliable code by embedding operational context directly into integrated development environments (IDE) for pre-commit risk scoring and safe deployments, helping to prevent incidents before code can ship. For organizations building AI-powered applications, the ecosystem extends into large language model operations (LLMOps) and agent governance while enabling agentic cloud operations through direct communication between PagerDuty and cloud provider agents for automated remediation and self-healing infrastructure.

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Powering the AI-Era with an Integrated Operational Layer

The expanded PagerDuty AI integration ecosystem helps to establish PagerDuty as the indispensable system of intelligence and action for AI-driven operations. With an existing foundation of more than 700 integrations, the ecosystem expands into AI-focused segments spanning agentic operations, coding agents, integrated development environments, enterprise copilots and beyond—enhancing interoperability via Model Context Protocol (MCP) integrations for seamless AI-to-platform connectivity.

The company’s AI integrations connect through three pathways: partners connecting to PagerDuty’s MCP Server, which enables partners to access service, team, and incident context; PagerDuty’s connections to partner MCP servers for seamless interoperability; and direct API integrations between partner platforms and PagerDuty. These integrations, if enabled by customers, help to power the context flywheel, which becomes smarter with every incident to resolve issues faster and prevent incidents from happening.

“Organizations are racing to adopt AI agents, but the real challenge is making them work together seamlessly in production environments,” said Jennifer Tejada, CEO and Chairperson of PagerDuty. “Our AI integration ecosystem solves this by connecting 30-plus AI partners directly into the operational workflows teams already rely on. This means faster incident resolution, reduced downtime, and the ability to prevent issues from impacting customers at all.”

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Strategic Partnerships with Key AI Tools

The launch announcement features three upcoming marquee partnerships that demonstrate the power of the ecosystem in action:

  • Anthropic/Claude Partnership
    PagerDuty launched a plugin for Claude Code, powered by MCP, now listed in the official Anthropic marketplace. This plugin helps developers catch risky code changes before they reach production by analyzing uncommitted changes against historical incident data. The plugin features pre-commit risk scoring that evaluates code deployment safety, along with a background agent that automatically investigates and summarizes incident context. By surfacing potential risks and providing actionable recommendations before code is committed, developers can prevent incidents that impact customer experience and avoid costly emergency responses—all without leaving their development environment.
  • Cursor Partnership
    PagerDuty’s newly launched MCP plugin for Cursor, now available in the official Cursor Marketplace, offers a one-step installation that brings critical operational context directly into the Cursor developer workflow. Developers can access on-call schedules, service information, and incident history without leaving their AI coding platform. When incidents occur, Cursor can automatically trigger agents to investigate logs and summarize potential root causes in real-time. This empowers developers to resolve incidents more quickly and build with confidence.
  • LangChain Partnership
    As application logic moves from code to the model, LLM apps and agents fail in ways traditional monitoring misses: silent degradation, inconsistent outputs, regressions that do not throw errors. Catching these problems fast and routing them to the right people requires observability and incident management to work together. LangSmith’s native integration triggers PagerDuty incidents when it detects critical issues like error spikes, latency increases, or feedback score drops. Teams get notified through their existing PagerDuty workflows without additional configuration. LangChain and PagerDuty also collaborated on an Incident Responder agent template for LangSmith’s Agent Builder. Built on PagerDuty’s MCP server, it lets teams create an agent that analyzes alerts, cross-references your runbook, and recommends actions.

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Semrush Unveils New Brand Identity to Command the AI Search Era

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Semrush Unveils New Brand Identity to Command the AI Search Era

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The industry leader evolves into the unified intelligence engine for brand visibility across modern search

Flam Onboards Ben Feld of Niantic Labs to Scale Interactive Advertising

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Flam Onboards Ben Feld of Niantic Labs to Scale Interactive Advertising

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Flam, the deep-tech startup pioneering AI-native content, has announced the onboarding of Ben Feld, new Sales Lead in San Francisco.

“Ben’s arrival marks a pivotal moment for Flam as we transition from building our deep-tech foundation to global enterprise scale,” said Shourya Agarwal, Founder and CEO of Flam.

With 15 years of experience, Feld has represented immersive technology platforms at leading global industry events, including Cannes Lions, SXSW, and VivaTech, where he worked closely with brands exploring next-generation digital engagement. Known for working effectively within cross-functional teams, Feld has led multi-year SaaS contracts, secured Fortune 500 adoption, and built strategic partnerships at companies such as Niantic, 8th Wall, and HP.

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Most notably, Feld was a driving force behind 8th Wall’s rise to dominance and its subsequent high-profile acquisition by Niantic, where he successfully navigated the complexities of global brand adoption for 8th Wall’s product suite. He led business development at Trivver, an AI-powered mixed-reality platform, focused on redefining immersive experiences.

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At Flam, Feld will focus on expanding enterprise adoption of AI-native content solutions, working with brands and agencies to transform consumer touchpoints into interactive, human-like visual experiences across marketing, communications, and commerce.

“Ben’s arrival marks a pivotal moment for Flam as we transition from building our deep-tech foundation to global enterprise scale,” said Shourya Agarwal, Founder and CEO of Flam. “Having witnessed Ben’s success in scaling interactive advertising, I know he is the right leader to help brands move past ‘passive’ engagement and embrace the future where AI-native content is the primary driver of commerce and advertising.”

“I’ve spent my career at the intersection of what’s next, from the early days of the spatial web to the current AI revolution,” said Ben Feld. “What Flam is building is the foundational infrastructure for a new type of human-visual interaction. I’m eager to join the team and take charge of a future where every consumer touchpoint is intelligent, interactive, and inherently human.”

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WSI Introduces Adaptive SEO Strategy as AI Rewrites the Rules of Online Visibility

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AI-Driven Search Trends Influence SEO Strategies for Brisbane Businesses

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As AI reshapes how customers discover products and services and decide which brands to trust, WSI, a global leader in digital marketing and AI consulting, has unveiled an updated version of its WSI AdaptiveSEO® framework, re-envisioned for the AI-driven search landscape. The shift is already underway.

In The AI Search Revolution: Adaptive SEO in the Age of AI, WSI Founder Dan Monaghan cites research showing that nearly 60% of Google searches now end without a click, and AI-generated summaries appear in nearly half of all informational queries. These shifts are changing how people build awareness, compare options, and make purchase decisions. Customers are increasingly turning to tools like ChatGPT, Perplexity, and Google’s AI Overviews for answers, often forming opinions before they ever visit a website. For businesses still relying on traditional search engine optimization alone, visibility can erode quietly over time.

“Search has changed drastically and structurally,” said Dan Monaghan.”Rankings used to be the goal. Now, online visibility increasingly depends on whether AI systems reference your brand when customers ask questions and look for recommendations. Businesses that only optimize for Google are playing by rules that are changing fast. ”

WSI’s updated Adaptive SEO framework addresses this new reality through five core principles, three of which form the foundation of how businesses must rethink their approach to building visibility today.

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Search Everywhere Optimization: Customers no longer search in one place, and neither does AI. Businesses need to show up across the platforms and content types that influence discovery, including social media, video, podcasts, forums, and editorial media.

Citations Are the New Clicks: Being mentioned now matters more than being visited. When a brand is referenced in trusted publications, industry discussions, or community platforms, AI treats those mentions as proof of relevance. According to research from Hard Numbers, 61% of AI citations about brand reputation come from editorial media, not company websites.

Trust and Authority Are AI Currency: AI doesn’t take a brand’s word for it. It evaluates signals like third-party validation, consistent business information, expert authorship, and original research before deciding which sources to recommend.

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“The opportunity here is significant for businesses willing to adapt,” Monaghan added. “AI doesn’t browse the web the way people do. It weighs trust signals and decides who or what to reference. Adaptive SEO is how you strengthen those signals so your business is more likely to show up in the answers customers are relying on now. ”

WSI AdaptiveSEO® is available through WSI’s global network of digital marketing and AI consultants. To learn more, visit wsiworld.com/our-services/adaptive-search-everywhere-optimization.

Dan Monaghan is available for interviews on how AI is reshaping search, what “AI visibility” means in practice, and the steps businesses can take now to remain discoverable.

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HaloBridge Technologies Launches HaloBridge Mobile™ to Extend Human-in-the-Middle AI Governance to Mobile Workflows

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HaloBridge Technologies Launches HaloBridge Mobile™ to Extend Human-in-the-Middle AI Governance to Mobile Workflows

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HaloBridge Technologies, the company behind the HaloBridge AI governance platform powered by the Gallo document intelligence engine, today announced HaloBridge Mobile™, enabling organizations to capture evidence, review AI-assisted documents, and certify decisions through Human-in-the-Middle™ review workflows directly from mobile devices—extending audit-grade AI oversight into real-world operations.

HaloBridge Technologies today announced HaloBridge Mobile™, a mobile extension of the HaloBridge AI governance platform, currently available in private preview.

As organizations rapidly deploy artificial intelligence to process documents, automate workflows, and analyze sensitive operational data, the need for human oversight and verifiable governance has become increasingly critical.

HaloBridge was created to address this challenge by introducing Human-in-the-Middle™ (HIM) review workflows designed to keep AI-assisted processes transparent, accountable, and auditable.

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HaloBridge Mobile extends these capabilities beyond the desktop, enabling users to submit documents, review AI-assisted outputs, and certify operational decisions directly from mobile devices.

This allows organizations to maintain governance controls even when work occurs in the field, across distributed teams, or outside traditional office environments.

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Mobile Evidence Capture for AI-Governed Workflows

Organizations across healthcare, finance, legal, and enterprise operations are increasingly deploying AI-assisted workflows, creating a growing need for transparent oversight, AI governance, and verifiable decision accountability.

Through integration with the HaloBridge platform and its underlying Gallo document intelligence engine, the mobile client enables documents and supporting evidence to be securely captured and routed into governed workflows.

Users can attach:

  • photos
  • video recordings
  • audio evidence
  • written notes
  • supporting files

to create a complete operational evidence record tied to specific business decisions.

Once submitted, documents and evidence pass through structured Human-in-the-Middle review workflows, where designated reviewers validate AI-generated outputs, approve document actions, and generate audit-ready evidence logs.

These capabilities support organizations operating in environments where documentation integrity, accountability, and decision traceability are essential.

Built for Secure Enterprise Deployment

HaloBridge Mobile is designed to operate with both HaloBridge Cloud deployments and self-hosted Gallo infrastructure, giving organizations flexibility to meet their own security, compliance, and data residency requirements.

This architecture allows companies to deploy AI-assisted document workflows while maintaining governance, compliance oversight, and operational transparency across distributed teams and mobile operations.

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