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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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.

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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.

Get in touch with our MarTech Experts.

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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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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.

Get in touch with our MarTech Experts.

Shopify is making a decisive move to ensure commerce doesn’t just survive the AI era—it defines it. The company has announced a sweeping expansion of native commerce across major AI platforms, anchored by a new open standard co-developed with Google called the Universal Commerce Protocol (UCP). The initiative positions Shopify as the infrastructure layer for what it calls agentic commerce, where AI agents don’t just recommend products but actively complete purchases on a shopper’s behalf.

This is more than another integration update. It’s Shopify signaling that AI assistants, chat interfaces, and conversational agents are becoming the next dominant storefront—and that it intends to power them all.

Commerce Moves Into the Conversation

AI chats have rapidly become a discovery engine. Millions of users now ask AI tools what to buy, compare products, and plan purchases without ever visiting a traditional ecommerce site. Shopify’s bet is that commerce needs to meet customers inside those conversations, natively and seamlessly.

With UCP, Shopify merchants will soon be able to sell directly within AI Mode in Google Search, the Gemini app, Microsoft Copilot, and ChatGPT, all managed centrally from the Shopify Admin through what Shopify calls Agentic Storefronts. Embedded checkout experiences remove the friction of redirects, logins, and siloed carts—allowing transactions to happen where intent peaks.

This marks a shift from “AI as a referral channel” to “AI as the transaction layer.”

Universal Commerce Protocol: A Shared Language for AI Shopping

At the center of Shopify’s announcement is UCP, an open standard designed to let AI agents connect to and transact with merchants at scale. Co-developed with Google and already endorsed by more than 20 retailers and platforms, UCP aims to solve a growing fragmentation problem: every AI platform currently handles commerce differently, if at all.

Shopify is proposing a shared language that allows agents to understand and execute real-world checkout complexity. That includes applying discount codes, honoring loyalty programs, handling subscriptions, confirming pre-orders, and respecting selling terms like final-sale policies—all within a conversational interface.

Importantly, UCP is payment-agnostic. While it works seamlessly with Shopify Payments, it also supports any payment processor. Under the hood, it’s designed to adapt to diverse commerce stacks using REST APIs, Model Context Protocol (MCP), Agent Payments Protocol (AP2), and Agent-to-Agent (A2A) standards.

For merchants with more nuanced requirements—such as furniture retailers that need delivery date selection—UCP provides a structured way to prompt agents for missing customer inputs without breaking the flow.

In short, Shopify is trying to make agentic checkout as flexible as the real world of commerce itself.

Google AI Mode and Gemini: The First Major Showcase

UCP will power a new generation of native shopping experiences inside Google’s AI products. Shopify merchants will soon be able to sell directly within AI Mode in Google Search and the Gemini app, using embedded checkouts controlled from Shopify Admin.

Google is also introducing a Direct Offers pilot, allowing select Shopify merchants to surface exclusive deals inside AI conversations. The idea is simple: when a shopper expresses high purchase intent in an AI interaction, merchants can respond with the right incentive at exactly the right moment—without leaving the chat.

For Google, this helps close the loop between discovery and transaction. For Shopify, it extends merchant reach into one of the largest AI-driven discovery surfaces on the planet.

Microsoft Copilot Checkout Expands the AI Commerce Map

Shopify is also expanding its partnership with Microsoft through a new Copilot Checkout experience. Users can now shop directly inside Copilot, completing purchases without jumping across tabs or platforms.

As Microsoft positions Copilot as a productivity and planning assistant, commerce becomes a natural extension—especially when users are researching products, organizing events, or managing personal tasks. Shopify merchants stay in control of inventory, offers, and fulfillment, while Copilot becomes another high-intent sales channel.

Brands including Keen, Pura Vida, and Kyte Baby are already using Copilot Checkout, while Monos, Gymshark, and Everlane are preparing to sell directly through Google’s AI experiences.

Shopify Catalog Opens to Every Brand

One of the most strategic shifts in this announcement is Shopify opening its Catalog to brands that don’t run their online stores on Shopify at all.

Through a new Agentic plan, any brand—regardless of ecommerce platform—can list products in the Shopify Catalog, a massive, continuously updated dataset of billions of products. Shopify uses specialized large language models to categorize, enrich, and standardize product data so AI agents can surface the right product instantly, even from ambiguous or conversational prompts.

Once listed, that data flows through Agentic Storefronts and appears across AI channels like ChatGPT, Google AI Mode, Gemini, Microsoft Copilot, the Shop app, and future Shopify partners. Merchants set up their data once; Shopify handles the distribution everywhere discovery happens.

This effectively turns Shopify into a neutral commerce backbone for the AI web—similar to how payment networks operate behind the scenes of traditional commerce.

Why Agentic Commerce Matters Now

Shopify’s push reflects a broader industry reality: AI assistants are evolving from information tools into action-taking agents. They don’t just answer questions—they plan, recommend, and execute.

In that environment, commerce can’t rely on static product pages and search ads alone. It needs to be programmable, conversational, and interoperable across platforms. Shopify’s decades of experience handling checkout edge cases, tax rules, inventory quirks, and global payments gives it a credibility advantage as standards emerge.

Rivals like Amazon, Google, and emerging AI-native commerce startups are all exploring similar territory. But Shopify’s approach—open standards, cross-platform reach, and support for non-Shopify merchants—suggests it’s aiming to be the Switzerland of agentic commerce rather than a closed ecosystem.

From Tools to Infrastructure

Shopify executives describe this moment as a platform shift on par with mobile or cloud computing. Where previous waves focused on storefronts and apps, this one centers on interfaces without screens—conversations that can transact.

By investing in protocols instead of point solutions, Shopify is betting that no single AI assistant will dominate. Instead, commerce will flow across many agents, surfaces, and contexts. UCP is designed to make sure merchants don’t have to rebuild their business logic for each one.

As AI-driven discovery accelerates, Shopify’s role is becoming less about where a store lives and more about how commerce works everywhere.

The Bigger Picture

If successful, Shopify’s strategy could reshape how brands think about customer acquisition, SEO, and paid media. When AI agents handle discovery and checkout in one flow, the line between marketing and transaction blurs. Offers, pricing, loyalty, and product data become just as important as creative messaging.

For merchants, the promise is reach without fragmentation. For shoppers, it’s fewer clicks and more relevance. And for the industry, it’s a signal that agentic commerce is moving from theory to infrastructure.

Shopify isn’t just adapting to AI-driven commerce—it’s trying to define the rules.

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Artificial intelligence is rapidly becoming the new interface between sports organizations and their fans—and the ATP is leaning into that shift. Infosys has announced the launch of Ally, an AI-powered chatbot designed to deepen fan engagement across men’s professional tennis, while also extending its long-standing partnership with the ATP through 2028.

The move underscores how digital platforms, data, and generative AI are reshaping the sports experience, turning passive spectators into active participants. For Infosys, it also reinforces a strategy it has been executing for over a decade: using enterprise-grade AI and analytics to power fan-facing experiences at global sporting institutions.

Ally: A New Front Door to the ATP’s Data Universe

Ally is built on Infosys Topaz, the company’s AI-first offering that leverages generative AI technologies. At its core, the chatbot acts as a conversational gateway to the ATP’s vast data ecosystem, providing real-time answers to questions around match statistics, tournament draws, schedules, head-to-head records, and historical performance.

Unlike basic sports chatbots that recycle surface-level facts, Ally is tightly integrated with the ATP Stats Centre, ensuring responses are grounded in verified, up-to-date data. Fans, journalists, players, and coaches can explore player comparisons, track performance trends, and surface context-rich insights through natural language conversations.

The experience is designed to be concise and intuitive, lowering the barrier for casual fans while still delivering depth for analysts and professionals who rely on accurate, granular data.

Built for Trust, Safety, and Scale

One of the growing concerns around generative AI—particularly in live sports contexts—is accuracy. Infosys and the ATP are positioning Ally as a controlled, enterprise-grade deployment rather than an open-ended experiment.

The chatbot includes multiple guardrails, such as content filtering, removal of personally identifiable information (PII), and contextual validation to detect and prevent misinformation or AI hallucinations. Continuous learning mechanisms allow Ally to refine its responses over time, adapting as new data, players, and tournaments enter the ecosystem.

This focus on governance reflects a broader trend in sports and media organizations: AI is no longer just about novelty, but about reliability, compliance, and brand trust.

A Decade-Long Digital Partnership Deepens

The Ally launch builds on a partnership that began in 2015, when Infosys became the ATP’s Digital Innovation Partner. Over the past ten years, Infosys has played a central role in shaping the ATP’s digital infrastructure, including the ATP app, ATP PlayerZone, and the ATP Stats Centre itself.

Extending the relationship through 2028 signals that the ATP sees AI and data as foundational—not experimental—to its future. As fan expectations evolve toward personalization, interactivity, and real-time insights, governing bodies are under pressure to modernize how they package and distribute information.

For Infosys, the ATP partnership also serves as a high-visibility showcase for its AI capabilities in a real-world, global environment—an approach the company has mirrored across other sports and entertainment properties.

Beyond Fan Engagement: Sustainability and Carbon Tracking

AI isn’t the only focus of the Infosys–ATP collaboration. In 2025, the partners rolled out Carbon Tracker 2.0, an updated version of the sustainability initiative launched in 2023 to help players measure and reduce travel-related emissions.

More than 300 players have used the tool, collectively tracking 2.3 million kilometers of travel and offsetting 585 tonnes of carbon in 2025 alone. The initiative reflects how data platforms originally built for performance analysis are increasingly being repurposed to address sustainability and operational efficiency—another growing priority across global sports organizations.

Why This Matters for Sports, Media, and MarTech

The launch of Ally highlights a larger shift at the intersection of sports, MarTech, and AI. Fans no longer want static stats pages or one-way broadcasts; they expect interactive, personalized experiences that mirror how they engage with digital products elsewhere.

By embedding AI directly into its data infrastructure, the ATP is effectively turning its statistics engine into a conversational product. That approach has implications beyond tennis, offering a blueprint for leagues, federations, and media companies looking to unlock more value from their data while strengthening fan loyalty.

It also reflects how enterprise AI platforms like Infosys Topaz are moving beyond back-office optimization into highly visible, consumer-facing roles—where accuracy, trust, and experience design are just as critical as technical performance.

Looking Ahead

As AI becomes more deeply woven into live sports, the differentiator won’t be whether organizations adopt it, but how responsibly and creatively they deploy it. With Ally, Infosys and the ATP are betting that conversational AI—backed by verified data and strong governance—can make tennis more accessible without sacrificing credibility.

For fans, it promises a more interactive way to follow the sport. For the industry, it’s another sign that AI-powered engagement is quickly becoming table stakes.

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Retail marketing has a data problem. Campaigns live in one system, transactions in another, loyalty data in a third—leaving retailers with fragmented insights and fuzzy ROI. At NRF 2026: Retail’s BIG Show, Celerant Technology is positioning itself as the antidote.

The retail commerce platform provider will showcase an expanded Customer Engagement Suite (CES), a tightly integrated marketing hub designed to let retailers manage campaigns, messaging, and automation from a single interface—powered directly by real in-store and online sales data.

The pitch is straightforward but increasingly urgent: stop stitching together marketing tools, and start running engagement from the same system that runs the business.

Marketing Meets the Core Retail Engine

Unlike standalone marketing platforms that rely on APIs and periodic data syncing, Celerant’s Customer Engagement Suite is built directly into its core commerce platform. That means email, SMS, live chat, social media management, online reviews, and customer communications all draw from a single, centralized retail database.

Every campaign is tied to actual transactions—point of sale, eCommerce, mobile apps, loyalty programs, and customer profiles—without manual exports or reconciliation.

“Retailers don’t need more marketing tools; they need one connected system,” said Michele Salerno, Celerant’s Chief Growth Officer. “CES becomes the central command center for marketing, powered by the same data that runs the business both in-store and online.”

It’s a clear response to a broader industry shift: retailers are under pressure to personalize outreach, prove ROI, and coordinate experiences across physical and digital channels—all while dealing with tighter budgets and leaner teams.

From Behavior-Based Campaigns to Built-In Automation

At the heart of CES is behavior-driven marketing. Retailers can build campaigns based on what customers actually do—what they buy, browse, return, or ignore—rather than relying on static lists or third-party data pipelines.

Because CES is natively connected to the product catalog, marketers can pull SKUs, images, and inventory data directly into campaigns, reducing friction between merchandising and marketing teams. Automation rules ensure messages are timely and relevant, triggered by real shopping activity instead of guesswork.

The benefit isn’t just personalization—it’s operational simplicity. By collapsing marketing and commerce into one system, retailers gain cleaner data, faster execution, and fewer points of failure as campaigns scale.

Closing the Online-to-Offline Gap With Geo-Fencing

Celerant is also using NRF to spotlight its geo-fencing capabilities, which push CES beyond digital channels and into physical retail environments.

Through branded mobile apps, retailers can trigger automated push notifications when customers enter predefined geographic zones near stores or key locations. The goal: influence purchasing decisions at the exact moment customers are close enough to act.

Once configured, these proximity-based campaigns run continuously, driving foot traffic and incremental sales without daily intervention from store teams. In an era where physical retail must justify every visit, location-aware engagement is becoming less of a novelty and more of a necessity.

Why This Matters Now

Celerant’s expanded CES lands at a time when retailers are rethinking their MarTech stacks. Best-of-breed tools once promised flexibility, but often delivered data silos, rising costs, and limited visibility into performance.

The alternative—unified commerce platforms with embedded marketing—is gaining traction. By tying engagement directly to transactions, platforms like Celerant aim to give retailers something many still lack: a single source of truth for customer behavior and campaign impact.

Competitors across the retail tech landscape are moving in a similar direction, but Celerant is leaning heavily on its single-database architecture as a differentiator—especially for mid-market and specialty retailers that don’t want enterprise-level complexity.

See It in Action at NRF 2026

Celerant will demo the Customer Engagement Suite at booth #4232, positioning it as a core pillar of its broader all-in-one retail platform. That platform already spans point of sale, inventory, eCommerce, mobile apps, fulfillment—and now centralized marketing.

For NRF attendees, the message is clear: the future of retail marketing isn’t another dashboard. It’s fewer systems, tighter data, and marketing that’s inseparable from how—and where—customers actually buy.

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