In a digital marketing world crowded with strategy decks and disconnected execution, Robinson Consulting is growing by doing something deceptively simple: owning both.

The Germany-focused digital marketing advisory has reached full client capacity just 90 days after refocusing its service model in mid-2025—a pace of growth driven not by aggressive advertising, but by fast, visible client results and referrals.

For founder Benjamin Robinson, the momentum validates a clear hypothesis about what small businesses actually need from marketing partners—and what they’re tired of paying for.

Fixing a broken marketing split

Robinson Consulting’s revamped Results-Driven Digital Marketing Advisory is built around a two-part premise that challenges the traditional consulting-agency divide.

On one side are consultants, who diagnose problems and deliver strategy but rarely implement. On the other are agencies, which execute campaigns without fully owning the underlying strategy. Robinson Consulting aims to collapse that gap by providing both strategic direction and hands-on execution through a single partnership.

“Business owners have no need for one more strategy deck that ends up collecting dust,” Robinson said. “Results come quickly when strategy and execution come from one source.”

That integrated approach appears to be resonating with founders and small teams who lack internal marketing departments—and the patience for long feedback loops.

Who the firm serves—and why it’s working

The advisory focuses on three core client segments:

• Solo entrepreneurs building visibility and personal brands

• Self-employed professionals, such as consultants and coaches, looking to attract better-fit clients

• Small and mid-sized companies that need senior-level marketing guidance without hiring full-time staff

Services span strategic digital marketing advisory, personal brand positioning, lead generation campaigns, and direct marketing implementation—designed to move from plan to execution without handoffs.

What differentiates the model isn’t breadth, but speed.

Speed as a competitive advantage

Robinson Consulting emphasizes rapid iteration based on real market feedback, streamlining processes so clients see traction quickly rather than months into an engagement. That velocity has become a growth engine of its own: early wins lead to referrals, which in turn fill capacity.

The firm has also benefited from state-backed subsidies that lower the barrier to professional marketing guidance for eligible businesses. Combined with quick results, the funding support accelerates both adoption and word-of-mouth growth.

In a market where trust is often slow to build, early proof appears to be doing the selling.

A high-touch model—by design

Despite hitting capacity quickly, Robinson Consulting isn’t racing to scale indiscriminately. Robinson says the firm plans to grow selectively, prioritizing confidentiality, accessibility, and close collaboration with each client—particularly across German-speaking small and mid-sized businesses.

“Trust is fundamental for successful working relationships,” Robinson said. “That’s why we ensure confidentiality and maintain accessibility with every individual client.”

That restraint may be strategic. As more founders seek alternatives to bloated agencies and abstract consulting, boutique advisory models that combine senior insight with execution are gaining appeal—but only if they preserve quality.

A signal of shifting demand

Robinson Consulting’s rapid growth reflects a broader trend in marketing services: businesses want outcomes, not artifacts. Strategy without execution feels incomplete; execution without strategy feels wasteful.

By collapsing the two into a single engagement—and proving results quickly—the firm has found a model that aligns with how small businesses actually operate.

Hitting full capacity in 90 days doesn’t just mark a milestone for Robinson Consulting. It underscores a growing reality in modern marketing: speed, clarity, and accountability now matter more than scale.

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For years, marketers have chased content inspiration through keyword tools, trend reports, and competitive audits. According to a new analysis from Digital Silk, many of the most valuable ideas are already hiding in plain sight—inside everyday customer interactions.

The digital agency, known for its work in branding, custom web design, and digital marketing, has published a new article titled How to Get Content Ideas From Customers, outlining how organizations systematically extract content insights from customer feedback rather than relying solely on intuition or trends.

The takeaway is straightforward but timely: customer-led content ideation works best when treated as a structured research discipline, not a reactive exercise.

From anecdotes to actionable insight

Digital Silk’s analysis draws on widely documented marketing practices and research around audience engagement, feedback loops, and behavioral analysis. Instead of positioning customer input as ad hoc inspiration, the article frames it as a repeatable process that complements traditional content planning frameworks.

“Customer interactions often surface recurring questions and themes that inform content development,” said Gabriel Shaoolian, CEO of Digital Silk. “The article outlines commonly referenced ways organizations review customer input when shaping content plans.”

That distinction matters. As content saturation increases, relevance—not volume—is becoming the differentiator. Listening closely to customers, Digital Silk argues, helps brands answer real questions instead of guessing what audiences might want to read.

Seven customer-led sources shaping content ideas

At the core of the article is a breakdown of seven commonly referenced customer-led inputs that organizations use to guide content strategy. None are new individually, but Digital Silk’s analysis shows how they become more powerful when treated collectively.

1. Customer questions and inquiries
Questions submitted through sales calls, customer support tickets, live chats, and contact forms often reveal consistent information gaps. When patterns emerge, they point directly to content opportunities that can preempt future friction.

2. Customer reviews and testimonials
Reviews don’t just signal satisfaction or dissatisfaction—they capture the language customers use to describe value, concerns, and expectations. Analyzing phrasing and recurring themes can help brands mirror customer vocabulary in blogs, guides, and landing pages.

3. Surveys and feedback forms
Structured feedback tools allow organizations to gather direct insight into customer needs, preferences, and challenges at scale. When aggregated, survey responses often expose unmet expectations or misunderstood features worth addressing through content.

4. Sales and support team insights
Frontline teams are often overlooked content strategists. Sales and support professionals interact with customers daily and observe objections, misconceptions, and decision triggers that rarely appear in analytics dashboards.

5. Social media interactions
Comments, direct messages, and discussion threads on social platforms frequently surface confusion, curiosity, or debate around specific topics. High-engagement posts can signal where deeper explanatory content is needed.

6. Community forums and user groups
Online communities, user groups, and third-party forums provide unfiltered insight into how customers describe problems and solutions in their own words—often revealing pain points brands wouldn’t identify internally.

7. Behavioral and usage data
Website analytics, content engagement metrics, and user behavior patterns help validate which topics sustain attention over time. This data can confirm whether customer-inspired content ideas resonate once published.

A research-driven approach to content ideation

Rather than presenting these sources as isolated tactics, Digital Silk’s analysis emphasizes organization and evaluation. Customer input is most effective, the article suggests, when it’s systematically reviewed alongside keyword research, performance data, and business objectives.

This approach helps teams avoid chasing every comment or complaint and instead focus on themes that consistently align with audience needs and brand positioning.

In practice, that means treating customer-led insights as a qualitative layer within a broader content research process—one that balances what customers say with how they behave and what the business needs to communicate.

Why customer-led content matters now

The timing of Digital Silk’s analysis is notable. As generative AI accelerates content production, differentiation is shifting away from output volume toward relevance and authenticity. Content rooted in real customer language and real customer questions is harder to fake—and more likely to build trust.

For B2B and B2C brands alike, customer-led ideation also offers a secondary benefit: alignment. When content reflects what sales and support teams hear daily, it reinforces messaging consistency across the organization.

Turning listening into strategy

Digital Silk isn’t arguing that customer feedback should replace traditional content strategy tools. Instead, the article positions customer-led inputs as a grounding mechanism—one that keeps content efforts anchored to reality rather than assumptions.

The result is content that answers actual questions, addresses real objections, and speaks in language customers already understand.

In an era where attention is scarce and skepticism is high, that grounding may be one of the most sustainable advantages a brand can build.

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IFS is making a strong statement in the crowded field service management (FSM) software market. The industrial AI specialist has been named the only Customers’ Choice in the 2025 Gartner Peer Insights Voice of the Customer: Field Service Management report—a distinction that puts real user sentiment front and center, not analyst theory.

Unlike Magic Quadrant placements, which balance execution and vision, the Voice of the Customer report reflects verified feedback from end users who live with the software every day. In that context, being the sole Customers’ Choice is more than a marketing badge—it signals consistent satisfaction across product capabilities, support, and overall experience.

Why This Matters in a Competitive FSM Market

Field service management has quietly become one of the most strategic battlegrounds in enterprise software. As manufacturers, utilities, energy providers, and asset-heavy industries push toward servitization, FSM platforms are no longer just about scheduling technicians. They’re about uptime, predictive maintenance, workforce optimization, and recurring service revenue.

IFS has leaned heavily into this shift with what it calls Industrial AI—purpose-built AI designed for complex, asset-centric environments rather than generic enterprise workflows. Gartner peer reviewers appear to agree that this focus is paying off.

According to Gartner’s methodology, vendors placed in the upper-right “Customers’ Choice” quadrant score highly on both user interest and overall experience relative to the market. In 2025, IFS is the only FSM vendor to meet that bar.

Industrial AI Moves From Buzzword to Business Value

IFS has spent the past several years positioning AI as a practical tool for industrial operations, not an abstract innovation layer. In field service management, that means applying AI to real-world problems: predicting failures before they happen, optimizing technician utilization, and helping service organizations grow margins without sacrificing customer experience.

Cathie Hall, Chief Product and Customer Officer at IFS, framed the recognition as validation of that strategy.

“As IFS continues to drive forward the Industrial AI revolution, we feel this recognition represents an important independent validation of our leadership position in this market, and our focus on innovation.”

That focus aligns with a broader industry trend. Enterprises are increasingly skeptical of AI promises that don’t map cleanly to measurable outcomes. Vendors that can show tangible improvements in efficiency, service quality, and revenue growth are gaining an edge—and customer reviews suggest IFS is landing on the right side of that divide.

What Customers Are Actually Saying

The Gartner Peer Insights report includes direct feedback from practitioners across services, manufacturing, energy, utilities, and IT services—industries where field operations are mission-critical.

Several themes stand out in customer reviews:

• End-to-end functionality: Users highlight IFS’s ability to support the entire service lifecycle, from planning and scheduling to execution and analytics.

• Operational gains: Customers cite measurable improvements in utilization, efficiency, and user experience over multi-year deployments.

• Collaborative product development: Reviewers repeatedly mention IFS’s willingness to listen and reflect customer needs in its product roadmap.

• Strong support model: Fast response times and proactive engagement appear to be a differentiator compared to some larger, less agile competitors.

In a market where FSM tools often feel bolted onto broader ERP or asset management platforms, this feedback suggests IFS has managed to balance breadth with depth.

How IFS Compares to Rivals

The FSM market includes heavyweights such as Salesforce, ServiceNow, Oracle, SAP, and specialized players focused on scheduling or mobile workforce management. Many of these vendors offer strong point solutions or benefit from ecosystem scale.

IFS’s advantage appears to lie in its industry-first design philosophy. Rather than adapting generic CRM or IT service workflows for field use, IFS builds FSM capabilities specifically for asset-intensive environments. That approach resonates with manufacturers and utilities that need more than basic work order management.

The Customers’ Choice distinction also highlights a potential gap between vendor messaging and customer reality elsewhere in the market. Not all well-known brands translate market presence into high satisfaction—something buyers increasingly factor into procurement decisions.

A Pattern of Gartner Recognition

This isn’t an isolated win for IFS. The company was also named a Leader in Gartner’s Magic Quadrant for Cloud ERP for Product-Centric Enterprises and earned a Customers’ Choice for Cloud ERP in manufacturing in a previous Gartner Peer Insights report.

Taken together, these recognitions point to a consistent theme: IFS is gaining traction not just with analysts, but with the customers deploying its software at scale. For enterprises evaluating long-term digital transformation partners, that combination carries weight.

Implications for Service-Centric Enterprises

For organizations where service is a growth engine rather than a cost center, the message is clear. FSM platforms are evolving into strategic systems that sit at the intersection of AI, asset management, and customer experience.

IFS’s recognition suggests that buyers are rewarding vendors who:

• Deliver AI that works in industrial contexts

• Support complex, global service operations

• Actively incorporate customer feedback into product evolution

As economic pressure forces enterprises to do more with existing assets, demand for intelligent field service solutions is likely to accelerate. Vendors that can prove customer value—rather than just market vision—will be best positioned to win.

The Bottom Line

IFS’s position as the only Customers’ Choice in Gartner’s 2025 Voice of the Customer: Field Service Management report underscores a growing reality in enterprise tech: credibility increasingly comes from users, not slogans.

For industrial and service-centric organizations weighing FSM investments, this recognition signals that IFS isn’t just talking about Industrial AI—it’s delivering outcomes customers are willing to stand behind.

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DaVinci Commerce, formerly known as Jivox, is betting that the next phase of commerce marketing won’t be managed by dashboards and manual workflows—but by AI agents operating at enterprise scale. The company announced a new strategic round of financing to accelerate growth of its AI-native DaVinci Commerce platform, as global brands and commerce media networks increasingly adopt agentic AI to manage the complexity of modern retail advertising.

The funding arrives at a moment when commerce media is booming but operationally strained. Brands are pouring budgets into retail media networks, yet many struggle to execute campaigns fast enough, across enough retailers, with the compliance and measurement rigor large enterprises require. DaVinci Commerce positions itself squarely at that pressure point.

From Jivox to DaVinci: A Strategic Reset Around Agentic AI

The rebrand from Jivox to DaVinci Commerce is more than cosmetic. It reflects a strategic shift toward what the company calls agentic commerce marketing—AI systems capable of autonomously executing multi-step marketing workflows that once demanded extensive human coordination.

Originally launched in August 2023, the platform was built from the ground up to be AI-native. Rather than layering AI onto legacy ad tech, DaVinci Commerce integrates content generation, optimization, media activation, and measurement into a single system designed for scale, speed, and enterprise control.

That positioning appears to be resonating. DaVinci Commerce was recently named a Top 50 Innovation at the 2026 National Retail Federation (NRF) Innovators Showcase, signaling early industry validation for its approach to agentic AI in commerce marketing.

Why Commerce Media Needs Agents, Not More Tools

Commerce media is now one of the fastest-growing segments in digital advertising. According to eMarketer’s May 2025 forecast, U.S. commerce media ad spend is expected to grow at a 15.3% CAGR from 2025 to 2029. But growth alone isn’t the problem brands are trying to solve.

The real friction lies in execution.

Retail media campaigns must be launched quickly, localized across retailers, customized by audience and product availability, and governed by brand, legal, and retailer-specific rules. Add in closed-loop measurement expectations and the convergence with programmatic buying, and the operational burden becomes enormous.

DaVinci Commerce was designed to operate at this intersection—where commerce media, programmatic advertising, and AI-driven automation collide.

“Commerce media growth is no longer limited by media spend but constrained by the ability to handle speedy launches, multi-retailer complexity, and compliance,” said Diaz Nesamoney, Founder and CEO of DaVinci Commerce. “We built the platform from the ground up to be AI-native.”

What DaVinci Commerce Actually Does

At its core, DaVinci Commerce enables brands to operationalize agentic AI across commerce marketing through two primary capabilities.

Commerce Content Optimization uses AI to generate, adapt, and deliver commerce ads and content across programmatic environments. The goal is to enable deep personalization—creative tailored to shopper context and intent—without sacrificing scale or brand consistency.

Commerce Media Activation automates campaign launches across commerce media networks in under five minutes. That speed is critical in a retail environment where promotions, inventory, and consumer demand shift rapidly. Importantly, the platform enforces enterprise-grade guardrails, ensuring brand safety, legal compliance, and retailer rules are respected even as automation increases.

Together, these capabilities aim to reduce the cost and complexity of running commerce campaigns while improving performance through personalization and faster time-to-market.

Beyond Ads: Agentic Shopping Experiences

DaVinci Commerce is also pushing beyond traditional ad execution into AI-driven shopping experiences. Instead of directing users to crowded product landing pages, the platform supports agentic shopping flows where consumers engage with AI-powered shopping agents.

These agents guide discovery, surface relevant product options, and help shoppers evaluate choices in real time. The result is a more conversational, intent-driven path to purchase—one that links ad exposure directly to verified transactions and incremental sales measurement.

This approach aligns closely with broader shifts toward LLM-driven conversational commerce, where discovery increasingly happens through AI interfaces rather than static search results or category pages.

A Notable Investor and Board Lineup

The strategic funding round is backed by a group of investors and executives with deep roots in AI, enterprise software, and commerce.

Saama Capital, a Silicon Valley firm focused on AI and commerce technologies, led the round. Its founder and managing partner, Ash Lilani, has joined DaVinci Commerce’s board.

The investor roster also includes Amit Singhal, former Senior Vice President and Google Fellow who led Google’s core search team for over 15 years; Sohaib Abbasi, former CEO and Chairman of Informatica and an early Oracle executive; and Cosmos Nicolau, a senior engineering leader with experience at Google, Akamai, GRAIL Bio, and Neeva.

The board has also expanded to include Jerry Porter, recently Chief Research and Innovation Officer at Procter & Gamble Fabric & Homecare, alongside existing members Greg Archibald of PayPal and Robert Chatwani, President of DocuSign and former CMO at Atlassian and eBay North America.

For a company operating at the intersection of AI, commerce, and enterprise marketing, the lineup adds both credibility and strategic depth.

Why CPG and Retail Brands Are Paying Attention

Consumer packaged goods brands, in particular, are under pressure to make better use of first-party data as signal loss reshapes digital advertising. Commerce media offers a rare combination of scale and deterministic purchase data—but only if brands can activate it effectively.

“Prior to commerce media and LLM-powered agentic commerce, brands were often flying blind,” said Jerry Porter. “DaVinci Commerce makes it easy for brands to connect exposure, discovery, and purchase.”

That promise—closed-loop visibility paired with personalized engagement—is what many CPG and retail marketers have been chasing for years.

The Bigger Picture: Agentic AI Comes to MarTech

DaVinci Commerce’s timing is notable. Enterprises across marketing and commerce are moving beyond generative AI experiments toward agentic systems that can execute, optimize, and learn with limited human intervention.

In that sense, DaVinci Commerce isn’t just competing with retail media tools—it’s positioning itself as infrastructure for the next phase of commerce marketing, where AI agents work alongside human teams to accelerate execution without sacrificing trust or control.

As agentic AI moves from concept to deployment, platforms that can balance automation with enterprise governance are likely to define the category. This funding round suggests DaVinci Commerce intends to be one of them.

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TikTok may be where trends are born, but increasingly it’s also where customers are found—especially for local businesses trying to stay relevant in a video-first internet. Scorpion, a major digital marketing and technology provider for local and SMB-focused brands, is making a direct play into that shift. The company announced it has joined the TikTok Marketing Partners Program as an officially badged Marketing Technology Partner, deepening its integration with the platform and expanding what its customers can do on TikTok.

The move positions Scorpion as a conduit between TikTok’s fast-moving ad ecosystem and the small and mid-sized businesses that often lack the time, expertise, or internal teams to manage it effectively. For TikTok, it’s another step toward making its ad platform more accessible beyond large brands and agencies.

Why TikTok Matters for Local Businesses Now

With more than 1 billion monthly active users globally, TikTok has evolved from an entertainment app into a full-fledged discovery and commerce engine. For local businesses—law firms, home services, healthcare providers, franchises, and regional brands—TikTok offers something other platforms increasingly struggle to deliver: attention.

But attention alone isn’t enough. TikTok advertising requires constant iteration, creative testing, and performance monitoring, all of which can be daunting for SMBs already stretched thin.

“It’s no secret that TikTok is a very unique space. It’s where culture often happens and is being created. And local businesses should be a part of that,” said Ashlie Kim, Senior Vice President of Advertising at Scorpion. “This partnership gives our customers the ability to easily show up, reach more of their audience, and improve their performance.”

The subtext is clear: TikTok is no longer optional, but it needs to be simplified if local businesses are going to use it consistently and effectively.

What the TikTok Marketing Partners Badge Signals

TikTok’s Marketing Partners Program is designed to connect advertisers with vetted technology providers that meet the platform’s standards for integration quality, scale, and innovation. For Scorpion, earning the Marketing Technology Partner badge signals TikTok’s confidence in the company’s ability to help businesses activate, manage, and optimize campaigns without unnecessary friction.

Rather than forcing SMBs to learn TikTok Ads Manager from scratch, Scorpion enables them to advertise through tools and workflows they already use. This “meet businesses where they are” approach mirrors a broader trend in martech: platforms win adoption not by adding features, but by reducing complexity.

For TikTok, partners like Scorpion extend the reach of its ad solutions into local and regional markets that are difficult to serve directly at scale.

What Scorpion Brings to TikTok Advertising

As a TikTok Marketing Technology Partner, Scorpion now offers a tighter, more automated connection between its marketing platform and TikTok’s ad infrastructure. The focus is on operational efficiency and performance, rather than flashy features.

Key capabilities include:

• Streamlined campaign creation and management, reducing setup time and technical barriers

• Optimization tools tailored for SMB performance, not enterprise-only use cases

• Integrated reporting and insights, enabling faster, data-driven decisions

• Automated workflows that minimize manual effort and operational overhead

• Scaled support for local and multi-location businesses, a core Scorpion audience

For SMBs that typically juggle marketing alongside daily operations, automation and simplification can be the difference between running TikTok ads sporadically—or not at all—and making them a repeatable growth channel.

TikTok’s Push to Broaden Its Advertiser Base

TikTok has been steadily investing in partnerships to lower the barrier to entry for advertisers. While major brands have already embraced the platform, the next phase of growth depends on attracting and retaining SMBs at scale.

“Businesses of every size are looking for trusted, efficient ways to activate on TikTok,” said Lorry Destainville, Head of Product Partnerships at TikTok. “Our Channel Sales Partners bring the technology, automation, and expertise needed to meet that demand.”

This reflects a familiar strategy seen at Google, Meta, and Amazon: partner ecosystems do the heavy lifting of onboarding and servicing smaller advertisers, while the platform focuses on reach, formats, and measurement.

How This Fits Into the Broader MarTech Landscape

Scorpion’s TikTok partnership highlights a larger shift in marketing technology. SMB-focused platforms are no longer just managing search, display, or social ads in isolation—they’re becoming centralized operating systems for customer acquisition.

At the same time, TikTok is evolving from a standalone channel into a must-have line item in local marketing mixes. The challenge is execution. Unlike search ads, TikTok requires creative experimentation, cultural awareness, and frequent optimization.

By embedding TikTok more deeply into its platform, Scorpion is effectively abstracting that complexity away from its customers. That approach aligns with where martech is heading: fewer dashboards, more automation, and tighter integrations between platforms and execution tools.

The Bottom Line

Scorpion joining TikTok’s Marketing Partners Program isn’t just a badge—it’s a signal that TikTok advertising is entering a more mature, SMB-friendly phase. For local businesses, it means easier access to one of the most influential platforms in digital culture today. For TikTok, it means broader adoption through trusted intermediaries that understand the realities of small and mid-sized teams.

As short-form video continues to shape how consumers discover brands, partnerships like this may determine which businesses show up—and which ones get left scrolling past.

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Bloomreach is making a decisive move to help brands stay visible—and in control—as shopping behavior shifts into conversational AI. The company announced Loomi Connect, a new capability that makes Bloomreach’s product discovery technology available through the Model Context Protocol (MCP), allowing retailers to bring their ecommerce search intelligence directly into ChatGPT and other conversational AI platforms.

In practical terms, Loomi Connect lets the same algorithms, ranking logic, and performance signals that drive conversions on a retailer’s website also determine how products surface inside AI-powered conversations. As more consumers turn to ChatGPT as a shopping assistant, Bloomreach is positioning conversational AI not as a threat to ecommerce, but as its next major channel.

Conversational Commerce Is No Longer Theoretical

Bloomreach’s launch is grounded in a sharp shift in consumer behavior. According to a company survey of more than 1,000 U.S. consumers, nearly half now shop with ChatGPT several times a week or more. More striking: when asked to choose between ChatGPT and a traditional ecommerce site, 41% said they would pick ChatGPT.

That data underscores a growing reality for retailers. Product discovery is no longer confined to search bars and category pages. It’s happening inside conversations—often before a shopper ever lands on a brand-owned site.

For years, brands invested heavily in on-site search optimization, merchandising rules, and personalization engines to control how products are discovered. Conversational AI threatens to bypass much of that work unless brands can inject their own intelligence into those experiences. Loomi Connect is Bloomreach’s answer to that problem.

What Loomi Connect Actually Does

Loomi Connect integrates Bloomreach’s product discovery stack directly into ChatGPT apps built on the OpenAI marketplace. Instead of relying on generic recommendations or static product feeds, ChatGPT can surface products using the same AI models and behavioral data that power a retailer’s ecommerce search.

That includes signals such as:

• Historical conversion performance

• Product availability and relevance

• Customer behavior patterns

• Merchandising logic refined over years of optimization

The result is product recommendations that are not only relevant to consumers, but also aligned with business goals such as profitability, inventory management, and conversion efficiency.

Equally important, Loomi Connect captures interaction data from conversational channels and feeds it back into Bloomreach’s customer profiles. This allows personalization to flow both ways—between a brand’s ecommerce site and AI-driven conversations—rather than fragmenting customer data across disconnected touchpoints.

Why MCP Matters for Commerce

The launch also highlights the growing role of the Model Context Protocol (MCP) as a bridge between enterprise systems and AI platforms. MCP enables structured, governed access to proprietary data and logic, making it possible for brands to expose intelligence to AI systems without relinquishing control.

For commerce teams, this is critical. Letting conversational AI “freestyle” product discovery can lead to inconsistent recommendations, margin erosion, or compliance risks. By plugging into MCP, Bloomreach allows brands to define how their data is used, which rules apply, and how recommendations are generated—even inside third-party AI environments.

This mirrors how brands approached earlier channels like email, SMS, and social media: initial experimentation followed by a push for control, consistency, and measurement.

ChatGPT As A Channel, Not A Competitor

Bloomreach is explicit about how it views the role of conversational AI in ecommerce.

“ChatGPT isn’t the competitor to the brand experience—it’s the next channel within it,” said Raj De Datta, co-founder and CEO of Bloomreach. “Brands need to take control of their presence on conversational channels, just as they did with email, SMS, and social media.”

That framing is significant. Rather than resisting AI-driven discovery, Bloomreach is encouraging brands to treat ChatGPT as an extension of their owned experience—one that should reflect the same intelligence, personalization, and strategic intent.

This stance aligns with a broader MarTech trend: brands increasingly accept that discovery happens off-site, but they still want to influence how it happens. Loomi Connect offers a way to project brand-specific intelligence into environments that retailers don’t directly own.

The Stakes For Retailers And Brands

The implications go beyond better recommendations. As conversational AI becomes a primary interface for shopping research and decision-making, brands that fail to integrate risk losing visibility—or worse, losing control over how their products are positioned.

Generic AI recommendations can prioritize popularity over profitability, relevance over compliance, or convenience over brand strategy. Bloomreach’s approach aims to ensure that when products appear in AI conversations, they do so on the brand’s terms.

For retailers already using Bloomreach for onsite search and personalization, Loomi Connect offers continuity. Years of tuning algorithms, refining relevance models, and analyzing shopper behavior don’t disappear in the age of conversational commerce—they extend into it.

How This Fits Into The Broader MarTech Landscape

Loomi Connect lands at the intersection of three major trends reshaping marketing and commerce technology:

1. Conversational interfaces replacing traditional search

2. AI platforms becoming new discovery gateways

3. Brands demanding governance and measurement in AI-driven channels

While many vendors are racing to “add AI,” Bloomreach is addressing a more nuanced challenge: how to operationalize AI across channels without fragmenting data, logic, or control.

In that sense, Loomi Connect isn’t just a feature—it’s infrastructure for a world where product discovery is increasingly conversational, decentralized, and mediated by large language models.

The Bottom Line

Bloomreach’s Loomi Connect signals a shift in how ecommerce leaders should think about AI-driven shopping. Conversational platforms like ChatGPT are no longer experimental—they’re becoming default entry points for discovery.

By enabling brands to bring their proven search intelligence into those conversations, Bloomreach is helping retailers protect relevance, consistency, and performance as commerce moves beyond the website. For brands navigating the next phase of digital commerce, that control may prove as important as reach itself.

Get in touch with our MarTech Experts.

In an industry known for rapid churn, short-lived agencies, and relentless platform upheaval, longevity is rare. Wonderful Websites & SEO, a U.S.–based digital marketing agency founded by Chris Moreno, is entering its 17th year in business—a milestone that stands out in a sector where most firms never make it past year three.

The timing is notable. Artificial intelligence is once again rewriting the rules of digital marketing, from search and content to customer engagement and operations. For Moreno, the anniversary isn’t just a celebration of survival. It’s a marker of relevance—and a signal that small businesses need steady guidance more than ever.

Founded nearly two decades ago, Wonderful Websites & SEO has grown into a multi-location agency serving more than 300 small businesses across the United States and Canada. Its core offerings—custom WordPress websites, local SEO, social media management, and paid advertising on Google and Facebook—have remained largely unchanged. Moreno calls them “the core four,” and says that focus has been key to the company’s endurance.

Surviving Where Most Agencies Don’t

Digital marketing is notorious for high failure rates. Algorithm updates, shifting ad platforms, client churn, and commoditized services have pushed countless agencies out of business. Against that backdrop, 17 years is an outlier.

“We’re entering our 17th year in business,” Moreno said. “We’ve earned over 100 five-star Google reviews, and to this day nobody has ever left us a review under five stars. But more importantly, we’ve stayed consistent in what we do best—bringing customers to small businesses.”

That consistency has carried the firm through multiple waves of disruption: the rise of Google Ads, the dominance of Facebook advertising, mobile-first search, and now AI-driven marketing tools. Rather than chasing every trend, Moreno says the agency’s strategy has been to master fundamentals and adapt carefully.

It’s a philosophy that resonates with small businesses, many of which don’t have the margin for experimentation or costly missteps.

AI Becomes the Defining Question

If there is a single force reshaping the marketing landscape today, Moreno says, it’s artificial intelligence.

“The elephant in the room is artificial intelligence,” he said. “Everyone has a different opinion of it, but at the very least it’s changing the market for small business dramatically—and therefore it’s changing the environment for marketing agencies like us.”

Unlike previous technology shifts, AI’s impact extends far beyond marketing execution. Moreno sees it touching nearly every operational layer of a business—from emails and spreadsheets to calls, meetings, and administrative work.

“Businesses are going to be blown away by what AI can do to make their lives easier,” he said. “But AI also introduces a wave of tools and services that aren’t ready for prime time.”

That tension—between genuine productivity gains and unproven hype—is where Wonderful Websites & SEO sees its role evolving. Rather than selling AI as a silver bullet, the agency is positioning itself as a filter and advisor, helping clients decide what’s worth adopting and what should be avoided.

Trusted Advisor in a Time of Noise

Moreno says many of the agency’s long-term clients are already feeling pressure to “do something with AI,” often without clarity on what that means.

“We work with over 300 small businesses, and many have been with us for a decade or more,” he said. “We’ve become a trusted advisor. When AI hits their industry, we’re usually their first call.”

That trust didn’t emerge overnight. It was built through years of consistent delivery, transparent communication, and a business model that minimizes friction for clients.

The agency operates without long-term contracts—a rarity in digital marketing. Retention, Moreno says, is earned month by month.

“Our retention rate is ridiculous,” he said. “If you deliver results, you never need to worry about people leaving.”

In an AI-driven future, that trust may become even more valuable. As automation lowers the barrier to entry for marketing services, differentiation increasingly comes down to judgment, accountability, and human guidance.

A People-First Approach in a Tech-Heavy Industry

Despite operating in a technology-driven sector, Moreno attributes the company’s longevity less to tools and more to people.

“The team I’ve put together I would put against any agency in the country,” he said. “I was inspired years ago by the show The Profit and its focus on people, product, and process—with people being the most important. From that moment on, I only hired the very best.”

Wonderful Websites & SEO now employs 23 team members, and Moreno says hiring discipline has shaped both culture and client outcomes. That people-first philosophy extends beyond internal operations to client relationships.

Many businesses, he notes, come to the agency after negative experiences elsewhere—locked into rigid contracts, underserved, or disappointed by results.

“We relieve that pain,” Moreno said. “We return calls and emails promptly. We do what we say we’re going to do. And we produce results.”

In a market increasingly flooded with AI-generated promises and automated services, that emphasis on responsiveness and accountability stands out.

Marketing Through Economic Uncertainty

The agency’s milestone also comes amid broader economic uncertainty, as many small businesses reassess spending. Marketing budgets are often first on the chopping block—a move Moreno believes is short-sighted.

“Most marketers and business coaches will tell you that marketing and advertising is the last thing you should cut—even though it’s often the first,” he said.

For businesses relying on lead flow, visibility, and customer acquisition, effective marketing can become a lifeline rather than a cost center.

“When we’re generating leads, calls, and new customers, we become their lifeline for growth,” Moreno added.

That argument is becoming more pointed as AI reshapes competitive dynamics. Businesses that disappear from search results, paid ads, or social platforms risk being replaced by more visible, tech-savvy competitors.

What 17 Years Signals for the Future

Wonderful Websites & SEO’s anniversary is less about nostalgia and more about positioning. As AI accelerates change across marketing and commerce, small businesses are likely to face increasing complexity—not less.

Tools will become more powerful, but also more confusing. Automation will promise efficiency, but not always deliver clarity. In that environment, agencies that combine technical competence with restraint and judgment may hold an advantage.

For Moreno, the next chapter is about applying the same principles that carried the company through previous shifts: focus on fundamentals, invest in people, and act as a long-term partner rather than a short-term vendor.

Seventeen years in, that approach appears to be resonating—and may prove even more relevant as AI pushes marketing into its next era.

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Cordial is taking a clear position in the increasingly crowded AI-for-marketing landscape: if AI can’t do the work, it’s not solving the problem.

The enterprise messaging platform announced the launch of two new AI agents—the Email Production Agent and the Data Intelligence Agent—built to automate real, production-grade marketing execution inside live workflows. Together, they form the first release of Cordial Agents, a governed agent system designed to close one of marketing’s most persistent gaps: the distance between insight and action.

While many martech vendors are racing to add AI assistants that generate ideas, drafts, or recommendations, Cordial is betting on something more operational—and more controversial. Instead of dozens of narrow agents, it’s launching fewer, deeper agents that are designed to eliminate manual, duplicative work across core marketing operations.

Why “Insights” Aren’t Enough Anymore

Marketing teams aren’t short on data. They’re short on the ability to act on it.

According to Cordial’s own research, 100% of marketers still rely on behavioral signals like clicks and opens to infer intent, yet nearly two-thirds say those insights are only used during campaign planning—not during live execution. The result is a familiar disconnect: campaigns run on assumptions formed days or weeks earlier, while customer intent changes in real time.

That disconnect shows up on the consumer side as well. Only 34% of consumers feel brands truly understand their needs, and 43% of marketers report losing customer trust when intent is misread.

As AI compresses the time between signal and action, this lag becomes harder to justify. In an environment where personalization, timing, and relevance increasingly determine performance, post-campaign insights are no longer enough.

Cordial’s response is to move AI directly into execution.

From “AI Assistants” to Production Systems

“Most AI tools stop at suggestions,” said Matt Howland, Chief Product Officer at Cordial. “We built Cordial Agents to do the work itself.”

That distinction matters. Typical AI assistants live outside production systems, generating copy or ideas that still require human translation into live campaigns. Cordial Agents, by contrast, operate inside real marketing systems, with access to live data, enforced rules, and production-grade tooling.

They don’t just advise. They execute.

Cordial describes its agents as systems designed to ground, govern, execute, and coordinate marketing work end to end. The emphasis on governance is deliberate. As AI-generated outputs move closer to live customer interactions, the risk of broken logic, brand violations, or misfired campaigns increases.

Cordial’s approach assumes that AI must be constrained, validated, and measurable if it’s going to operate at scale.

The Email Production Agent: Automating the Heavy Lifting

The first of the two agents, the Email Production Agent, targets one of the most execution-heavy areas of enterprise marketing: email.

Rather than generating a draft and handing it off, the agent handles the full production workflow, including:

• Personalization logic

• Audience definitions

• Message orchestration

• Campaign measurement

Crucially, it builds emails using production-grade tools that run inside live campaigns—not simplified prompts or static templates. Before anything is deployed, outputs are validated against real customer profiles to ensure correctness at scale.

This validation step addresses a common failure mode of AI-generated marketing: logic that looks right in isolation but breaks when exposed to real data. By checking outputs before execution, Cordial aims to prevent errors from ever reaching customers.

The Data Intelligence Agent: Acting While Campaigns Are Live

If the Email Production Agent executes, the Data Intelligence Agent observes—and intervenes.

Working from the same shared understanding of customer intent, the agent continuously monitors campaign and audience performance in real time. Instead of surfacing insights after a campaign ends, it identifies emerging trends and issues while there’s still time to act.

That includes flagging underperforming segments, detecting shifts in engagement, and recommending next actions while campaigns are still running. The goal is not just awareness, but timely response.

In practice, this moves analytics closer to operations, reducing the lag between detection and decision that has long defined marketing execution.

Governed AI, Not Autonomous Chaos

Cordial is careful to frame these agents as governed systems, not autonomous actors.

Each agent operates within a defined framework that includes explicit tools, built-in quality checks, controlled retries, and enforceable guardrails tied to brand and campaign standards. Outputs are continuously checked and corrected, allowing the agents to improve results without introducing operational risk.

Execution happens through specialized tools that operate directly inside live workflows, ensuring everything an agent produces is executable, measurable, and safe to run at enterprise scale.

This focus on governance reflects a broader shift in how serious martech buyers are evaluating AI. As experimentation gives way to production use, control, auditability, and predictability are becoming non-negotiable.

Agents That Work Together—and With Humans

Another notable design choice is that Cordial Agents are built to collaborate.

Agents share context and communicate with one another, allowing insights from one area—such as performance data—to inform execution elsewhere. Humans remain part of the loop as well, contributing briefs, artifacts, and direction that improve shared understanding.

Rather than replacing marketers, Cordial positions its agents as force multipliers that remove manual bottlenecks while keeping strategic oversight with human teams.

A Contrarian Bet in a Crowded AI Market

Cordial’s “fewer, deeper agents” philosophy stands in contrast to much of the current AI marketing narrative, which often emphasizes breadth over depth. Many platforms are adding AI features rapidly, but stopping short of execution.

Cordial is betting that marketers don’t need more assistants—they need fewer steps.

By embedding AI directly into production workflows, the company is addressing a harder problem: not generating ideas, but turning intent into action without friction.

The Bigger Picture for Enterprise Marketing

As AI becomes embedded across the marketing stack, the winners are likely to be platforms that reduce operational drag rather than add new layers of abstraction.

Cordial Agents reflect that shift. They’re not positioned as experimental tools, but as infrastructure—designed to remove manual, cumbersome, and duplicative work from marketing operations altogether.

For enterprise teams struggling to act on real-time signals at scale, that may be a more compelling promise than another AI assistant offering suggestions no one has time to implement.

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