The problem is simple: systems don’t talk to each other. A customer starts a conversation on live chat, calls later to follow up, and then gets an email with conflicting information. Each hand-off forces them to repeat details, re-authenticate, or explain the issue all over again. Patience runs out quickly.

The cost isn’t hidden for long. U.S. companies lose an estimated $136.8 billion every year to avoidable churn. Customers leave when systems don’t connect, data is trapped in silos, workflows run in isolation, and departments push their own priorities instead of working toward the full journey.

Fixing that takes more than patches. It needs stronger journey orchestration, along with omnichannel workflow design and dependable CDP integration. The aim is for every channel to draw from the same source of truth, so the customer isn’t forced to start over at each step.

Fragmented Journeys: The Hidden Cost and Causes

The cost of fragmented customer journeys isn’t always obvious. Customers don’t usually complain about “systems not talking to each other.” They just get tired of repeating themselves, chasing updates, or being bounced between departments. Some walk away silently. Others switch to a competitor after one poor experience. That lost loyalty is expensive.

All the while, customers that get connected experiences are helping brands grow. Studies show customers who get “excellent” experiences spend about 140% more.

The Causes of Fragmented Customer Journeys

Why are fragmented customer journeys still getting worse? A big part of the answer lies in the systems. Older ERP platforms were built for accounting and operations. They store useful data, but they weren’t designed to share it across customer touchpoints.

On top of that, many firms still run sales, service, and fulfillment on different platforms. Each team shapes processes around its own system, so when customers move between departments, the context often gets lost.

Then there are issues created by:

• Multiple versions of the same customer: Without solid CDP integration, one person might exist in several databases under different IDs. That makes personalization, and even basic service, harder.
• Channels that don’t connect: Phone, email, chat, apps, and stores often sit on different platforms. Customers expect one conversation. Businesses deliver five.
• Processes that drift: Marketing offers a refund or discount, but the policy never makes it to the billing system. Customers get conflicting answers depending on who they ask.
• Automation in silos: Generic automation often backfires. A bot that can’t see the full journey adds more friction, not less.
• Slow-moving data: By the time an update syncs between systems, the customer has already called back.
• Compliance barriers: Privacy and security rules matter, but poor design can block the very context agents need to help.

Taken together, these gaps explain why customers feel let down. The business may see good metrics in one channel, but the overall journey tells another story. Until the foundation is fixed, journey orchestration and omnichannel workflow automation tools can only go so far.

Unifying Journeys: The Journey Orchestration Tech Teams Need

When customers say they feel like they’re dealing with “five different companies at once,” it’s rarely the fault of the service team. The problem sits in the systems. Fixing fragmented customer journeys means building a stack where data flows from the back office to the front line without friction.

Cloud ERP Integration

Most ERPs were built to balance books and manage inventory. They weren’t built to answer a customer who asks, “Where’s my order?” That’s why cloud ERP integration is now so important. When ERP data is connected directly to sales and service platforms, answers come back in seconds instead of days.

Cloud ERP changes that. By connecting ERP directly with CRM and service systems, data is available in real time. Smarter Furnishings made this upgrade with Microsoft Dynamics 365 and reduced quote turnaround times by 80 percent. That kind of improvement comes from eliminating the delays caused by disconnected back-office systems

CDP Integration

Most companies hold records with multiple versions of the same customer. A single person might appear in the marketing database, the CRM, and the billing platform under slightly different records. This duplication makes personalization impossible and creates obvious gaps in service.

A customer data platform (CDP) takes scattered records and pulls them into one profile. It updates as new information comes in, so teams aren’t working from old or conflicting data. That single view makes it possible to keep the journey consistent when a customer moves from one channel to another. With CDP integration, journey orchestration tools have a reliable record to draw on instead of piecing together fragments.

Combining Customer Journey Orchestration and AI Decisioning

The orchestration layer is where data turns into action. Journey orchestration engines like the industry-first solution from NiCE take context from CDPs, CRM systems, and ERPs, and use it to determine the next best step in the customer’s journey. That may mean routing a case to the right team, sending a proactive update, or triggering an RPA process in the background.

Qualtrics research shows that effective orchestration can boost revenue by 10–20 percent while reducing service costs by 15–25 percent At FedPoint, NiCE CXone drove similar results in practice: IVR containment increased from 28.5% to 33.9%, customer satisfaction rose to 98.35%, and average answer speed fell from 35 seconds to 15 seconds.

Omnichannel CCaaS

Customers don’t think in terms of “channels.” They expect one continuous conversation, whether they start with a phone call, follow up via chat, or receive an email confirmation later. Without a unified contact platform, those experiences quickly fracture.

That’s why omnichannel workflow through contact center as a service (CCaaS) is now a priority. BankUnited’s deployment with Talkdesk shows the results: self-service adoption increased by 16%, abandonment fell to 5.3%, and NPS more than doubled.

Automation and CRM Intelligence

Even with orchestration in play, journeys can stall if the back office is still running on manual tasks. That’s where RPA comes in. It takes on work like refunds, policy checks, and updates, jobs that would otherwise create delays and frustration.

On the front line, CRM automation does the heavy lifting for agents. AI creates summaries automatically, enriches profiles with data, and shares recommendations with agents in real time. The agent spends less time searching and more time solving. That combination speeds up resolution and helps ensure the journey doesn’t break in the final mile.

How to Start Reducing Journey Fragmentation

There isn’t a quick fix for fragmented customer journeys. The organizations that succeed usually take it step by step. They get the basics right, test in a few focused areas, and only then expand.

• Begin with the data: If core systems don’t share information, the journey will eventually break. That’s why so many CIOs are prioritizing ERP and CRM integration, or even tying in CDP solutions, before layering on orchestration.
• Create a single customer profile: A CDP integration pulls records together from sales, marketing, and service. It means every interaction draws from the same source of truth. Without that, different teams are still working off different stories.
• Pilot orchestration on high-value journeys: Trying to orchestrate everything at once rarely works. Pick a few critical touchpoints, like order tracking or benefit enrollment, and build orchestration around them. A Middle Eastern bank did this with Kore.ai, and eventually achieved 40% automation rates for workflows, as well as higher CSAT scores.
• Add omnichannel contact. Customers don’t think in terms of “phone” or “chat.” They want one continuous conversation. Moving to CCaaS platforms helps deliver that. Particularly when those systems can speak to ERP, CRM, and CDP solutions.
• Automate the back office. Journeys still fail when refunds or approvals sit in manual queues. RPA can process these instantly, while CRM automation gives agents context without the need to dig. Together, they prevent small delays from becoming big frustrations.

Also, measure what matters. Efficiency metrics only go so far. Average handle time may look good on a report but say little about customer loyalty. Outcome-based measures – resolution rates, effort scores, verified completions, tell you whether fragmentation is actually being reduced.

Journey Orchestration: From Fragmentation to Flow

Plenty of firms talk about improving customer experience. The real progress comes from those willing to confront fragmentation directly. They modernize their data foundations, connect ERP and CRM, put CDP integration in place, and then add journey orchestration and omnichannel workflows. Each layer builds on the last, creating a system that actually holds together.

The rewards are measurable. Containment improves without hurting satisfaction. Resolution times drop. Customers stop repeating themselves at every turn. Plus, loyalty grows stronger, the ultimate measure of success in competitive markets where switching costs are low and alternatives are one click away.

Journey orchestration is only going to matter more as AI takes on a bigger role in customer experience. But AI that runs on inconsistent data won’t deliver. Reducing fragmentation is the first step. Once that’s done, journeys become faster, cheaper to support, and more likely to end in loyalty instead of churn.

“CX isn’t viewed as a single application anymore. It’s just a systems integration problem,” says Tim Banting, Head of Research at Techtelligence.

Modern CX enterprises juggle dozens of disconnected systems – CRM, HR, marketing, data lakes – all tracking partial versions of the customer.

Even something as simple as moving contacts from one phone to another can be painful, Banting notes. Multiply that complexity across global systems, and it’s easy to see where things start to break.

AI Doesn’t Fix Bad Data – It Exposes It

The belief that AI can “make sense” of messy data is widespread – and wrong.

“A lot of people think all I need to do is turn it on, point it to a whole load of PDFs, and AI will make sense of it,” Banting explains. “But it takes a lot of data hygiene, a lot of taxonomy, a lot of clearing up.”

Rather than clarifying customer insights, AI often compounds the confusion. “It’s got so many sources that it just shows you everything and doesn’t know how to react,” he says.

Without a unified data layer, AI in customer experience will churn out inconsistent results and unreliable recommendations.

The outcome: stalled AI initiatives and frustrated leadership teams waiting for their data foundations to catch up.

The New Battleground: Data Integrity

Techtelligence forecasts that by 2027, businesses that unify CX and communications data could reduce service costs by up to 25% and improve retention by 10–15%.

The shift is already visible. Banting observes that “the most read articles on CX Today recently have been about integration, like the Agentforce rollout, rather than new features.”

Buyers, he says, are now prioritizing orchestration and connected workflows over flashy tools. Clean, unified data is fast becoming the new competitive weapon.

The Pressure to Unify Is Mounting

Data unification can no longer be an afterthought. Regulatory, financial, and operational pressures are accelerating the need for action:

• Regulation: New frameworks such as the EU AI Act demand clear data lineage and consent management.
• Economics: With static IT budgets, “buyers want fewer vendors and not more middleware.”
• Fatigue: “People are done stitching together best-of-breed tools that don’t talk to each other.”

Delaying data integration now risks slowing growth, introducing compliance hurdles, and increasing technical debt, Banting highlights.

Four Lenses to Evaluate CX and AI Vendors

Banting warns against chasing the next “shiny object” to fix data chaos. Instead, he suggests evaluating vendors through four practical lenses:

• Data Architecture: Does it build a single, unified customer profile?
• Explainability: Can AI “show its workings out”?
• Openness: Does it support open standards like MCP for integrating multiple AI agents?
• Governance: Is the solution “audit proof” with full data lineage and compliance tracking?

“You need AI to explain how it’s reached a decision,” Banting adds. “I was always told to show my workings out in maths class – AI needs to do the same.”

Matching Tools to Strategy, Not Hype

Techtelligence’s “strategic clusters” framework offers a smarter way to align CX investments.

“If the best car is a Ferrari, that’s great for racing, but not for your groceries,” Banting quips. “The same applies to CX solutions. You match the tool to the task.”

He advises buyers to focus less on technical specs and more on long-term alignment – how well a vendor fits enterprise data strategy, IT architecture, and financial goals.

The right match can transform data from a bottleneck into a springboard, reigniting stalled AI projects and restoring the promise of intelligent customer experience.

Stay Ahead in Enterprise Technology

To find Tim Banting’s full advice for tech buyers, read his latest post on Techtelligence.com.

If you’re an enterprise technology buyer or involved in procurement decisions for your business, follow Techtelligence on LinkedIn for weekly insights, analysis, and expert advice to help you make smarter technology choices.

You can also join its growing LinkedIn Community Group to discuss trends, share experiences, and connect with like-minded business professionals driving digital transformation in their industries.

Available within Oracle Fusion Cloud Applications, the agents are designed to help CX leaders unlock fresh revenue opportunities.

According to Oracle, the agents achieve this by allowing users to “operate faster and make better decisions.”

With the ability to enhance automation processes and analyze connected data, the solutions promise to equip CX leaders with the tools to deliver more personalized experiences and strengthen customer loyalty.

Chris Leone, EVP of Applications Development at Oracle, claims that the AI agents will “unlock new revenue opportunities with intelligent insights and agentic automation.

AI agents are transforming customer engagements from reactive, manual, and cumbersome processes into highly valuable and proactive strategies that enable organizations to scale quality experiences to win more business and keep customers happy.

The agents are powered by Oracle Cloud Infrastructure and benefit from being natively integrated within Oracle Fusion Applications.

In addition, agents can be embedded directly within an organization’s existing workflows.

It is clear that Oracle is placing a great deal of stock in its latest release, but can these role-based AI agents deliver on their promise?

Living Up to The Hype

In a conversation with CX Today, Martin Schneider, VP and Principal Analyst of Constellation Research, shared some insights on what makes an AI agent successful and whether Oracle’s offering can live up to the hype.

For Schneider, the driving force behind a strong AI agent is precision data, which he views as being integral to training agents and enabling them to execute on agentic workflows.

He believes that Oracle ticks these boxes, stating:

Oracle offers the breadth of business applications – and the integration and data management capabilities – to generate a more inclusive and accurate view of the customer in order to unlock agentic AI value.

Schneider also commended the vendor for making it more seamless for users to start working with agentic tools, due to the fact that a lot of their AI offerings come free of charge with existing Oracle license fees.

“This allows CX leaders to work with (or in some cases without) IT to start developing agentic flows that improve the customer experience with lower risk and cost,” he explained.

Role-Based AI Agents

With each of Oracle’s prebuilt, role-based AI agents offering different capabilities, the vendor outlined how certain agents are best suited for Marketing, Sales, and Service:

Marketing

For Marketers, the new AI agents are designed to deliver data-driven decisions about where to focus their efforts.

The Account Product Fit Agent applies predictive scoring and Ideal Customer Profile data to determine which accounts are most likely to buy, giving marketers a clearer view of where to allocate resources.

The Buying Group Definition Agent, on the other hand, focuses on mapping roles within the buying process, using title-based algorithms to identify which contacts influence specific product decisions.

Together, these agents reflect a broader industry move toward precision targeting and more accountable marketing strategy.

Sales

In sales, automation and intelligence are being integrated directly into everyday workflows.

The Deal Advisor Agent provides sellers with quick access to relevant guidance – such as product overviews, pricing information, and customer references – to support deal progression.

The Quote Assistant Agent streamlines the quoting process by answering proposal-related questions in real time, reducing the time required to prepare and send offers.

To drive revenue growth, the Product Recommendations Agent identifies cross-sell and upsell opportunities by analyzing customer history and quote data.

Collectively, these agents are reshaping how sales teams access information and engage with prospects, placing greater emphasis on efficiency and informed decision-making.

Service

Across service operations, AI is being deployed to improve responsiveness and consistency in customer support.

The Triage Agent analyzes incoming requests to determine issue type, severity, and sentiment, allowing teams to prioritize more effectively.

The Self-Service Agent enables customers to resolve common issues independently through guided digital workflows, reducing pressure on support staff.

To enhance case handling, the Service Request Creation Agent automatically converts customer messages – from chat, calls, or email – into actionable service requests.

For field operations, the Work Order Agent generates pre-filled work orders containing relevant details to support first-time resolution.

These developments underline a growing trend toward predictive and preventative service models, where automation supports faster and more consistent customer outcomes.

As these trends explode, pinpointing technology providers that will lead sales and the broader CX function into the future is a crucial mission that many enterprises are embarking on.

Analyst tools like the Gartner Magic Quadrant for Sales Force Automation Platforms aim to serve these enterprises, and the 2025 edition spotlighted three market Leaders.

As in 2024, the Leaders are: Salesforce, Microsoft, and Oracle.

Interestingly, the entire matrix looks similar to the previous year’s version, as the CRM space takes a collective breath and waits for the transformative impact of agentic AI.

That said, there is one mover this year, with SugarCRM falling from the Challenger group into the Niche Player quadrant.

Also, there’s one new entrant: Monday.com, which enters in the bottom-left square. Meanwhile, Freshworks has dropped from that square and off the matrix altogether.

ServiceNow is the most noticeable continued absentee, with its Sales and Order Management solution surprisingly missing the cut.

The Definition of a Sales Force Automation (SFA) Platform

A Sales Force Automation (SFA) platform typically sits within a CRM system that centralizes a sales team’s data – alongside data from other customer-facing functions – into a customer profile.

The SFA then takes that data and adds adjacent tooling to assist sales reps and automate several of their tasks.

As the years have rolled by, SFA solutions have swelled with new features. Yet, the fundamentals remain the same, with capabilities covering account, activity, contact, forecast, opportunity, and pipeline management.

Beyond that, there are tools for analytics, proposals and quotes, partner relationship management, and more that Gartner considers “mandatory” in its report.

Others becoming more common include: revenue intelligence and enablement solutions, digital sales rooms, and configure, price, quote (CPQ) applications.

After going through these capabilities and the many others, Gartner grouped 13 of the most prominent SFA providers into four camps: Leaders, Challengers, Visionaries, and Niche Players. Here’s how they performed.

Gartner Magic Quadrant Leaders

Leaders in the Magic Quadrant demonstrate a compelling vision for the SFA category’s future, a complete product, an above-average customer experience, and strong earnings. This year’s market Leaders are:

• Salesforce
• Microsoft
• Oracle

Salesforce

Salesforce Sales Cloud continues to lead the SFA space. Why? Per Gartner, its “strategic focus on agentic AI” is now a chief reason, with Agentforce for Sales now available to its SFA install base.

Notably, that includes a personalized Sales Coach that supports reps in advancing deals “effectively”.

Yet, Gartner also cites Sales Cloud’s “robust customization and extensibility” as another core strength, alongside its “enhanced account and contact research” features.

Since Gartner conducted its research, Salesforce has made two big moves to bolster its SFA: embedding Slack channels and acquiring Bluebirds.

The former helps Salesforce step towards a more collaborative CRM ecosystem, while the latter empowers Salesforce with an AI agent that automates prospecting.

Microsoft

Microsoft Dynamics 365 Sales benefits significantly from its broad ecosystem, converging CRM solutions with ERP and broader enterprise technologies.

Yet, the Microsoft Teams chat panel now available within the SFA caught the eye of Gartner’s team, enabling employees across the enterprise to collaborate on customer cases.

The platform also benefits from integrated Microsoft Power BI technology, enabling deeper conversational intelligence capabilities than most competitive offerings.

Gartner picked up on this and noted the native Copilot as another strength, which allows users to build customized workflow automations, dashboards, and views.

However, it didn’t spotlight the AI agents Microsoft has added to the platform, which can perform tasks like customer outreach, surfacing at-risk deals, and more.

Oracle

Oracle may not market its SFA platform with the gusto of Salesforce or Microsoft, yet its offering has many advantages, especially for those already partnering with Big Red on ERP.

Gartner picks up on its “account and contact management capabilities”, with unique tools for maintaining and enriching sales data.

The analyst also heaps praise on its “visualization and analytics” and “mobile” features, with the latter especially well-suited to sales teams that are constantly on the move.

The CX Awards 2025 judges recognized some of these features when giving Oracle the nod for “Best CRM Solution.”

Additionally, they underscored how the tech giant is integrating AI into Oracle Sales and its other Fusion apps to deliver added value without raising costs. Instead, it just comes part and parcel.

Gartner Magic Quadrant Challengers

Challengers in the Magic Quadrant are typically larger than Niche Players, matching an impressive new flow of business with an excellent understanding of the current market. Yet, their longer-term vision may not resonate with top sales execs and IT leaders, with the latter coming increasingly to the fore in CX buying decisions. This year’s Challengers are:

• SAP
• Pegasystems

SAP

Like Oracle (and Zoho), SAP can enable advanced sales automations and data workflows by pulling CRM and ERP systems onto the same platform.

Surprisingly, Gartner doesn’t highlight this as a strength. However, it does commend SAP for establishing a workspace for admins to collaborate on cases, KPIs, and more.

Moreover, the analyst lauds SAP’s “guided selling” tools and “composable and microservice architecture”. That composability is key, as when sales teams add niche tools to SAP Sales Cloud, businesses can establish a common data foundation.

As AI agents come into the fray, that data foundation may prove invaluable.

Nevertheless, SAP misses out on the Leader quadrant, with SAP citing its “reliance on add-ons and integrations” to deliver an enterprise-grade SFA platform.

Pegasystems

Pegasystems has long envisioned the “autonomous enterprise”, operating at the intersection of CRM, workflow automation, and low-code technologies.

As such, it appears well-positioned for the AI agent era, showing impressive thought-leadership when announcing an industry-first agent orchestrator in February 2024.

Gartner does not highlight this in its report. However, it does applaud Pega for its “opportunity-guided selling” and “partner relationship management” features.

Additionally, it gives Pega plaudits for its “visualization and analytics” strategy, where it develops engaging narrative summaries that tell stories and inspire action.

It does, however, lack the collaboration tooling of market leaders, and Gartner also cites limitations in its forecasting capabilities.

Gartner Magic Quadrant Visionaries

Visionaries in the Magic Quadrant can compete with market leaders in their product, pricing, and innovation models, demonstrating an excellent understanding of market trends. However, they cannot yet exhibit the execution streak of “top-right vendors”. This year’s Visionaries are:

• Zoho
• Creatio

Zoho

Zoho continues to expand across the enterprise, building payroll, HR, and various other solutions, all within one self-owned architecture. That enables it to deliver end-to-end workflows from Zoho CRM and beyond. It also allows it to effectively limit costs.

While Gartner didn’t spotlight this, it lauded Zoho for its “comprehensive partner ecosystem management”, which is another significant strength.

The analyst also pinpointed its “AI-powered account and contact intelligence” and “AI-enhanced visualization and analytics” capabilities as major plus points.

These pluses underscore Zoho’s evolving AI story, with the vendor making unique moves, such as building and customizing its own LLM, which may support its long-term ambitions to mitigate cost.

Nevertheless, there are feature gaps in Zoho’s SFA product, with Gartner citing its “basic AI-guided selling” as a caution for buyers.

Creatio

Creatio competes with the big players in CRM thanks largely to its no-code experience, enabling users to design and configure CRM workflows without any technical skills. Indeed, no low-code shortcuts or coding required.

Unsurprisingly, Gartner underscored this differentiator alongside the vendor’s ongoing “viability” and “embedded no-cost AI features”. Those include data analysis, workflow creation, and content generation, per the analyst.

Another strength that Gartner didn’t highlight is Creatio’s approach to flexible implementations, with public, private, and on-premise options. That’s paired with a promise for “rapid” deployments.

Nevertheless, the Magic Quadrant lists the need for “manual configuration in generative AI” and its “less mature” ISV (independent software vendor) ecosystem amongst its cautions.

Gartner Magic Quadrant Niche Players

Niche Players in the Magic Quadrant have gained traction, typically by excelling across specific market segments or particular industries. Yet, across the market, they may lack product depth and/or an established record for execution.  This year’s Niche Players are:

• HubSpot
• BUSINESSNEXT
• SugarCRM
• Neocrm
• Vtiger
• com

HubSpot

HubSpot typically markets to SMBs. The Gartner Magic Quadrant targets enterprise buyers. That disconnect may have hampered its performance.

Nevertheless, HubSpot does have some enterprise customers, and Gartner praised the Breeze AI layer that runs across the Sales Hub and the vendor’s broader CRM ecosystem. That’s supported by a context layer, established after the 2024 acquisition of Frame.ai.

Gartner also isolated HubSpot’s “activity management” and “visualization and analytics” solutions as core strengths.

However, listed among its cautions are its “static” opportunity-guided selling capabilities and predictive AI features.

BUSINESSNEXT

BUSINESSNEXT offers a suite of enterprise platforms typically geared towards the financial services and insurance sector. That has allowed it to establish a strong presence in the sector.

However, its platform expands beyond and includes several notable new features. Number one is its “mobile functionality”, per Gartner, with its smartphone app including advanced voice data entry functionality and AI-enhanced notifications.

The analyst also spotlights strengths in its “account and contact management” tech and industry AI models, which expand into pharma and retail, alongside finance.

Yet, “less developed” pipeline and forecasting management tools and sometimes complicated workflow configurations are listed as concerns within the report.

SugarCRM

Despite dropping into the Niche Player category, SugarCRM has added to its revenue intelligence functionality by integrating capabilities from its May 2024 acquisition of sales-i.

That strength has boosted its appeal in key verticals that prioritize revenue over lead-gen, such as manufacturing, distribution, and related industries.

Nevertheless, Gartner warns that it may have over-rotated on this strategy and has risked alienating its longstanding, diverse customer base.

It did, however, note strengths in “lead and account intelligence”, “opportunity summarization and alerts”, and its “extensible platform with industry-specific accelerators”.

Neocrm

While it’s a smaller name in North American and European space, Neocrm serves many large enterprises throughout Asia and the Pacific.

Its AI capabilities are a deal-winner, with Gartner noting how they offer a “competitive performance” against even the biggest-named vendors in the report.

Meanwhile, the analyst commends Neocrm’s activity management and customer collaboration tools.

However, although its AI may compete, Gartner notes “AI module pricing and complexity”, alongside its limited geographic scope, as two cautions.

Vtiger

Like HubSpot, Vtiger primarily targets the midmarket, which may have hindered its standing in this enterprise-focused report, reminding readers that they mustn’t take the Magic Quadrant matrix at face value.

That said, Vtiger does earn kudos from Gartner for its account, activity, and contact management features, include the ability for Vtiger One users to establish hierarchies within the sales team. “Partner enablement” is another strength.

However, the report cautions of the vendor’s narrow “vertical products”, alongside its limited “forecasting” and “proposal and quoting” tools.

monday.com

In August 2022, Monday.com launched a sales CRM, again most relevant to SMBs. Since then, it has expanded into monday CRM and quickly established a global footprint.

Pushing this fast growth is its customizable, no-code UI. Gartner rubberstamps this and applauds monday.com for its “ease of management” and “collaboration and sharing capabilities”.

Nevertheless, its “limited AI and ML (machine learning) depth” and reliance on manual data entry are among the cautions obstructing its charge further into the SFA space.

Unpack more CX Today rundowns of adjacent Gartner Magic Quadrant reports below:

• Gartner Magic Quadrant for CRM Customer Engagement Center (CEC) 2024
• Gartner Magic Quadrant for Customer Data Platforms (CDPs) 2025
• Gartner Magic Quadrant for Content Marketing Platforms (CMPs) 2025