Every AI CRM vendor selling into 2026 has an AI agent story by now. The differentiator is no longer whether agents exist, but who is allowed to build the next one, how long that takes, and what happens to the bill once it works. For decades, CRM has promised growth and mostly delivered data entry, decaying from a system of action into a system of record. The agentic shift changes that, and with it the questions buyers should ask. Let’s put Creatio's AI CRM to those questions, following a deal from lead to order to see how much orchestration ships out of the box and how much a revenue team must assemble. The findings are published in full in my report, AI CRM for Revenue Growth: Inside Creatio's AI-Native No-Code Platform.

The company behind the platform

Creatio is a privately held, AI CRM and no-code workflow automation company headquartered in Boston, founded in 2014 by Katherine Kostereva, who remains CEO. It ran as bpm'online until a 2019 rebranding, bootstrapped until its first institutional round in 2021. A $200 million round led by Sapphire Ventures in June 2024 lifted its valuation to $1.2 billion; total funding raised now stands at roughly $268 million, and it reported around 50 percent year-over-year revenue growth at the time.

Creatio employs around 1,000 people and sells through more than 500 implementation partners worldwide. The company’s partner program has held a 5-star rating in CRN's Partner Program Guide for eight consecutive years. Customers span more than 100 countries, among them AMD, Colgate-Palmolive, and MetLife, with millions of workflows launched daily.

One platform, two studios

The product serves marketing, sales, and service on a single unified data model. Creatio Studio sits on top, split into Business Studio for no-code applications and AI Studio for autonomous agents, both sharing one data, security, and governance model. An in-app AI Twin now lets end users build their own agents from an IT-approved library without leaving the CRM. What makes this an AI CRM rather than a CRM with AI attached is where the intelligence sits: Creatio combines predictive, generative, and agentic AI in a single Creatio.ai architecture, reachable by end users in natural language, instead of bolting a chatbot onto a system of record.

Two authoring patterns cover most agent use cases. Prompt agents are simple assistants defined by a natural-language instruction plus the tools and skills the agent is allowed to use. Workflow agents are multi-step processes built on the same drag-and-drop designer that powers the rest of the AI CRM. Both are built by the same business-side practitioner who already configures pipelines and dashboards. There is no separate developer queue, AI-specialist hiring profile, or code repository in the middle.

Creatio was named a Leader in Nucleus Research's November 2025 LCAP Technology Value Matrix, and it was the only Leader in Forrester's 2024 Wave for low-code platforms built for citizen developers. That recognition shows up in practice too: BSN Sports runs its entire deployment for 2,600 users with just three administrators, while Howdens rolled out to 7,000 users across more than 800 depots in twelve weeks. Nucleus has separately measured 61 percent faster lead response, 70 percent faster implementation, and 37 percent lower total cost of ownership against legacy systems. Industry editions — including an agentic banking Solution that provides the basis for a Banking Blueprint that covers onboarding, lending, and KYC/AML — extend the platform into regulated sectors.

The pricing bet

In 2026, Creatio introduced an Unlimited plan tied to its Unlimited Enterprise operating model. One subscription covers unlimited users, custom agents, applications, workflows, custom objects, and API calls as a single platform fee, with AI included rather than metered. Beneath it, credit-based consumption is the default and per-user licensing remain available; AI Studio and AI Studio Twin add no incremental license.

The test: five agents, one deal

To test the authoring claim directly, I looked at a five-agent scenario across a single deal's lifecycle, combining shipped Creatio.ai agents with customer-specific ones authored in AI Studio:

• An ICP-fit agent and an engagement-fit agent jointly qualify inbound leads, built on Creatio's Account Research and Lead Scoring agent patterns, promoting a lead to sales-accepted once both clear their thresholds.
• An opportunity-health agent layers S/M/L risk sizing on Creatio's native MEDDPICC scoring, reads the opportunity record and call transcripts, and gates stage advancement until the criteria are met.
• A SPIN-style coaching agent proposes concrete next moves on a stalled deal but cannot act without rep approval.
• A service-brief agent, built on the shipped Customer Support and Knowledge Base agents, compiles ticket history, sentiment, and invoice status into an on-demand pre-call summary.

All five are registered, monitored, and governed in Creatio's unified administration layer, with PII policy, approval gates, cost thresholds by agent and model, and audit logging applied uniformly, whether the agent shipped with the product or was authored in-house. Each customer sets the rigidity, from letting agents auto-transition stages to requiring a human at every gate.

How the competition does it

Most competing approaches to agent-building fall into one of three patterns:

• an agent designer wired tightly to a fixed data model, as with Salesforce's Agentforce and ServiceNow's AI Agents;
• a horizontal builder paired with a separate CRM, as with Microsoft's Copilot Studio and Dynamics 365; or
• a pro-code toolkit that still needs the engineering capacity it was supposed to eliminate.

Each carries a trade-off: opinionated designers constrain any customer whose process diverges from the vendor's reference, horizontal builders mean stitching two governance models together, and pro-code toolkits demand the scarce engineers they promised to free up. Creatio's pitch is that collapsing the AI CRM, the data model, the process engine, and the AI authoring layer into one product, governed from one console, sidesteps all three.

Analysis

The architectural claim holds up on inspection: governance, authoring, and the AI CRM itself sit in one architecture rather than three, which is a structural condition most agentic CRM vendors talk about, but few actually deliver.

The Unlimited Enterprise pricing model is the more interesting bet, however. It shifts the conversation from seats to execution at a moment when every competing consumption model bends upward exactly as AI adoption succeeds. The caveat is that Creatio's own default is AI credit-based consumption, so the unlimited promise and the metered tier still need reconciling. Whether it holds as genuinely unlimited at scale is the open question I would flag for any multi-year commitment.

The weaker spots are predictable for a company this size. Brand recognition in the upper enterprise and the North American mid-market still trails the legacy CRM incumbents, and delivery runs through that partner network, where outcomes vary with partner maturity. Neither is disqualifying, but both belong in a buyer's due diligence.

The AI CRM category itself is still being defined, so the more durable test isn't feature count. It's whether this architecture and this commercial model survive contact with deployments larger than the reference customers cited above.

Want the full picture, including the complete five-agent scenario, the competitive comparison, and the SWOT? My full report is available for download here.

Every single week, I sit through pitches from enterprise software vendors boasting about the next iteration of their " AI-powered sales pipeline optimization platforms". They promise to auto-magically turn cold leads into closed contracts while minimizing human intervention. That sounds great on a slide deck designed to pump the stock price before an earnings call. In reality, however, these systems are automating an architectural flaw that has plagued B2B organizations since, well, forever: the linear sales funnel.

Let me be clear here. The classic sales funnel is not an asset; it is a structural failure. It assumes a predictable, straight line where marketing captures raw interest, tosses a lead over a wall to a sales development representative, who then passes it to an account executive to close the deal. Once the contract is signed, the customer disappears from the pipeline, and is handed off to an underfunded customer success department that operates like a glorified complaints department. This system assumes that buying journeys have a finite endpoint.

The B2B buying journey does not end when a contract is signed. By treating marketing, sales, and service as isolated phases with independent processes and technology stacks, enterprise organizations create massive amounts of friction. Norbert Schuster, a veteran B2B strategist who joined us in the latest episode of the CRMKonvos podcast, summarized this beautifully when he described the classic setup as the "Currywurst-Pommes effect". Individually, a sausage or a plate of chips is acceptable; combined, they become something functional. Yet, in most organizations, marketing automation platforms and CRM instances do not communicate well. They sit side by side as poorly connected line items on an IT budget, completely unaware of the buyer's actual context.

TL;DR

If you want to watch the full CRMKonvo, please go ahead here (optimized for smartphones) or here (optimized for tablets/computers).

Else, be my guest and continue to read.

Or do both …

Exposing the Mess with a Digital Spotlight

AI is not a strategy. Anyone who tells you that deploying an LLM-based agent will fix your declining customer acquisition metrics is selling vaporware. AI is an amplifier. It takes whatever processes, data models, and organizational habits you already have and executes them at massive scale and speed. If your data hygiene is abysmal, your processes are broken, and your teams are actively fighting over lead ownership, AI will simply automate that chaos and deliver bad results faster than any human ever could.

The reality is that customer behavior has moved beyond the internal structures of the average enterprise. Schuster uses a great concept to describe this phenomenon: the "Sunday-Monday gap". On Sunday evenings, B2B buyers act as modern digital consumers. They use highly integrated, AI-driven platforms to book travel, order food, and manage their lives with single-click simplicity. On Monday morning, they walk into a corporate environment and are forced to deal with siloed databases, manual handovers, or sales reps who rely on a sheet of paper because the corporate CRM is too cumbersome to use.

This gap means that buyers are conducting the vast majority of their research completely hidden from your tracking scripts. They are reading peer reviews, participating in private communities, and leveraging generative AI tools to evaluate vendors long before they ever fill out a form on your landing page. When they finally do show up, they are not looking for a generic corporate brochure or an automated five-email nurturing sequence. They expect an immediate, context-aware interaction based on the specific business problems they are trying to solve.

Moving Beyond Handovers to Loops

To fix this, organizations must replace the linear funnel with an integrated revenue engine. This requires an mental and architectural shift from handovers to loops. In a traditional siloed structure, a marketing manager’s responsibility ends when a lead achieves an arbitrary lead-score threshold and becomes a "marketing qualified lead". This metric is entirely self-serving. It measures internal activity rather than external buyer readiness.

A true revenue engine changes the core question. Instead of asking who owns a lead at any given moment, a cross-functional revenue team asks a much more relevant question: what information or interaction does this specific buyer require to make their next business decision? This requires a new architecture. It acknowledges that the buying process is cyclical, encompassing landing, expanding, and maximizing lifetime value. If a customer signs an initial agreement, they immediately enter a new phase of the journey focused on cross-selling, upselling, or platform adoption.

If your organization still separates "hunters" who bring in new business from "farmers" who manage renewals, you are likely losing massive amounts of revenue at the handover point. Most account management teams operate reactively. They wait for a renewal date to approach or for a client to log a support ticket before initiating a meaningful conversation. There is no predictive lead management, no presales automation, and no continuous content alignment designed to show how a client can derive more value from their initial investment. The energy simply evaporates the moment the initial deal closes.

Rebuilding the Organizational Fabric

If you look at the underlying cause of this, it is rarely the software. The issue is organizational design. Marketing and sales teams routinely operate with completely separate key performance indicators, entirely distinct vocabularies, and incompatible views of the ideal customer profile. Marketing celebrates record-high lead volumes, while sales misses its quarterly numbers and blames marketing for delivering low-quality data.

To overcome this structural divide, organizations need to bring these functions under a unified leadership structure, such as a Chief Revenue Officer who owns the entire customer journey from initial discovery through long-term retention. This ensures that data definitions are shared, technology stacks are integrated natively, and incentive structures are aligned around total revenue generation rather than departmental vanity metrics.

We can look to a sport like rowing to visualize how this works when executed correctly. An eight-person rowing crew requires total synchronization. Every single rower must move with identical timing, guided by a single coxswain who maintains the direction and tempo. If one side of the boat pulls harder than the other, or if individuals decide to row to their own rhythm, the boat loses momentum and veers off course. This is exactly what occurs when marketing, sales, and customer success operate as independent silos. They pull in different directions, burn through budgets, and ultimately fail to deliver a coherent customer experience.

Corporate Realities for Enterprise Tech Buyers

Enterprise buyers face a difficult environment when evaluating sales and marketing technology. The market is saturated with “platforms” claiming to solve every revenue problem with automated intelligence. To avoid buying expensive software that fails to deliver a return on investment, decision-makers must keep some fundamental realities in mind:

Reject the Illusion of Out-of-the-Box Integration

Every software vendor claims their marketing automation tool integrates seamlessly with your existing enterprise CRM. In practice, these integrations are often shallow API connections that sync basic contact fields while completely failing to transfer behavioral context or historical intent signals. If your sales representatives cannot see which whitepapers a prospect read, which private community threads they interacted with, or how they used your digital tools directly within their primary CRM view, your systems are not integrated. Do not sign a contract until you have audited the data model compatibility under real-world conditions. Deep architectural alignment is what transforms disconnected software into a functional revenue engine.

Prioritize Process Clarity Over Automated Intelligence

Deploying a generative AI email outreach tool or an automated lead-scoring algorithm on top of a broken data architecture will only accelerate your pipeline problems. AI is highly effective at finding patterns and executing repetitive tasks, but it possesses zero strategic judgment. If your teams do not have a clear, shared definition of a qualified buying signal, or if your customer data is trapped in disconnected silos, an AI tool will simply generate masses of generic messages that alienate your target audience. Before investing in AI capabilities, invest time in identifying your core buyer journeys and cleaning your data infrastructure. Software cannot optimize a process that does not exist.

Maintain Absolute Control Over the Human Relationship

Automated workflows, automated nurturing sequences, and AI-generated content can handle initial research inquiries and routine data entry effectively. However, they can’t own the relationship with the buyer. B2B purchasing decisions are high-risk corporate investments made by real people who are risking their internal reputations and budgets. These buyers do not want to be processed by a series of automated emails or generic conversational bots. They require empathy, technical expertise, and personal accountability from their vendors. Use technology to remove administrative burdens from your sales and service teams, but ensure your human professionals remain the primary point of contact for every meaningful decision. Enterprise revenue engines are built on human trust.

Technology is merely the infrastructure that supports it.

There is a moment in every technology cycle where a vendor decides the best way to signal relevance is to put the current buzzword in its name. We seem to be in that moment.

SugarCRM, the mid-market CRM vendor backed by Accel-KKR, just rebranded to SugarAI. The company declared that CRM as a category has failed to deliver on its 30-year-old promise and that AI makes a fundamental reset possible. CEO David Roberts frames it as moving from "AI as a feature" to "intelligence as the system."

That is a strong claim.

And a good claim!

Let us see what is behind it.

What Sugar Is Actually Saying

Strip away the rebrand fanfare and there are three substantial moves here.

First, Sugar is narrowing its identity around what it calls "precision selling." The concept: CRM should stop being a passive system of record that sellers resent updating and start actively telling them where to focus, what accounts are at risk, and what to do next. This is not a new aspiration in the CRM industry. What makes Sugar's version more interesting than the usual hand-waving is the second move.

Second, Sugar is leaning hard into the ERP-CRM bridge. The 2024 acquisition of sales-i gave Sugar the ability to ingest transactional data from over 180 ERP systems and surface revenue signals that traditional CRM cannot see. When a distributor's reorder volume drops 30% or a manufacturing customer shifts purchasing patterns, that signal lives in the ERP, not in the CRM. Sugar is betting that connecting these dots is where real value sits. Cameron Marsh at Nucleus Research called this "a pragmatic approach to AI," and he is right. It is one of the more grounded AI stories in CRM right now.

Third, Sugar is doubling down on verticals. Manufacturing, wholesale, distribution. Industries with long buying cycles, complex product catalogs, and deep account relationships. Industries that largely sat out earlier waves of sales technology because those tools were not built for their world. Sugar is saying: we are built for your world.

All three moves are coherent and mutually reinforcing. That alone puts this rebrand ahead of most.

The Name Problem

Here is where my enthusiasm somewhat decreases.

Every enterprise software vendor will have AI deeply embedded within 24 months. When that happens, having "AI" in your brand name will feel like calling yourself "CloudCRM" in 2024. Nobody does that, because cloud became table stakes.

The brands that age well are anchored to outcomes. Salesforce is about the sales force. ServiceNow is about service delivery. SugarAI is about... a technology ingredient. If Sugar can make "precision selling" synonymous with its brand the way Salesforce owns "CRM," the name not only survives, but can become category shaping. If precision selling remains a tagline rather than a category, expect another rebrand by 2029.

I give this name a coin-flip chance of lasting five years. The strategy underneath it is far stronger than the label on top.

At the very minimum, this rebranding becomes a conversation starter, gives some startup vibes and an internal catalyst to focus efforts, which are good things in themselves.

The Competitive Landscape Sugar Needs to Navigate

SugarCRM co-founder Clint Oram, who stepped away from the company in 2025 after 21 years, shared a competitive read that is worth examining.

He argues that the rebrand matters most in the context of Salesforce, HubSpot, Zoho, and Creatio. His take, in brief: Salesforce is a juggernaut where switching costs keep accounts locked. HubSpot serves a fundamentally different market (SMB, short sales cycles, inbound-first). Creatio owns the DIY ops buyer who wants to build processes, a segment Sugar moved away from years ago. And Zoho's horizontal "everything" brand cannot match Sugar's vertical depth.

He is largely right. But there is a significant gap in this competitive frame.

Microsoft Dynamics 365 is the competitor Clint does not name, and it may be the most dangerous one Sugar faces. In mid-market manufacturing and distribution, Microsoft already has native ERP (Business Central), native CRM, native AI (Copilot), and the entire Microsoft 365 productivity stack, including Teams that buyers already live inside. Sugar's anti-complexity pitch works well against Salesforce. Against Microsoft, that argument is harder to sustain. The buyer who runs their email, collaboration, ERP, and business intelligence on Microsoft will need a compelling reason to add a separate CRM vendor to the stack. This reason could be "precision selling".

SAP is another factor. Sugar targets verticals where SAP is the dominant ERP. If Sugar's story is "we bridge CRM and ERP data," buyers running SAP S/4HANA will ask why they should not just use SAP CX. The SAP CX suite has been struggling, which creates real opportunity, but SAP is not walking away from its installed base.

Freshworks competes at the lower end of mid-market with Freddy AI and a simpler deployment model. There is no direct ICP overlap, but Freshworks is moving upmarket and Sugar should be watching the rearview mirror.

And a word about Zoho. Zoho actively moves away from a horizontal approach and is building interesting ERP and AI capabilities, focusing its messaging around value. Along with the company's upmarket move, there is another one to watch out for.

What Precision Selling Needs to Become

The concept is sound, more than sound, actually. Its defensibility might become a challenge.

"Precision selling" as a term is intuitive and appealing. But it is also generic enough that any competitor could adopt it tomorrow. Salesforce could fold it into Agentforce messaging. Microsoft could embed it into Copilot for Sales positioning. The term is strong. The moat around it is shallow, unless there will be a trademark around it.

For precision selling to become a durable category rather than fizzle out as a campaign, Sugar needs three things.

Customer evidence. Five to ten reference customers publicly attributing measurable revenue lift to the ERP-CRM bridge and AI-guided selling. With the help of partners like Technology Coast Partners, this shouldn't be hard to achieve. Analyst placements (Nucleus Leader, Constellation ShortList) are necessary but not sufficient. Buyers trust other buyers more than they trust quadrants.

Product proof. The AI guidance has to demonstrably change outcomes, not just surface insights. There is a meaningful difference between "here is a dashboard showing your account is at risk" and "here is the specific action that will retain this account, based on what worked in 40 similar situations." Sugar needs to be on the action side of this divide.

Repetition at scale. Category creation requires marketing investment that a PE-backed mid-market vendor may or may not be willing to sustain. Accel-KKR's appetite for brand-building spend will determine whether precision selling becomes a market term or stays a Sugar term.

What Buyers Should Do

If you are evaluating SugarAI for your shortlist, here is how to cut through the rebrand noise. Start by ignoring the name. A rebrand tells you what a company wants to be. A proof of concept tells you what it actually is.

Ask for vertical references who can quantify results. it's not about logos on a slide but about customers in your industry who will tell you what changed after they connected ERP and CRM data through Sugar. No references, no result. Just a vision.

Backtest the AI. Ask Sugar to run their precision selling guidance against your last two quarters of actual deals. Would the recommendations have changed outcomes? Would at-risk accounts have been flagged earlier? Retrospective validation is the fastest way to separate signal from marketing.

Compare against Microsoft, not just Salesforce. If your organization already runs Dynamics 365 or Business Central, the integration cost of adding Sugar as a separate layer needs to justify itself against what Microsoft delivers natively. If you are not on Microsoft's stack, Sugar's independence becomes an advantage.

The Bottom Line

SugarAI is a better strategy than it is a name. The vertical focus, the ERP bridge, and the precision selling concept are coherent and differentiated. The brand name bets on AI remaining a meaningful differentiator in a world where it is rapidly becoming wallpaper.

The next 18 months will tell us whether Sugar built a category or just changed a logo.

Recently, while on the ground in Austin, Texas, attending ZohoDay 2026, I had the pleasure of sitting down with Vaibhav Dani, the CEO of Map Communications. In the enterprise software ecosystem, we talk endlessly about digital transformation, but it is always refreshing to ground those lofty concepts in reality by speaking directly with the leaders navigating these complex implementations.

Our conversation touched on a surprisingly common, yet notoriously difficult challenge: harmonizing a homegrown operational tech stack with off-the-shelf enterprise software. Map Communications’ journey with the Zoho ecosystem provides a masterclass in pragmatic architecture, the age-old "buy versus build" dilemma, and the foundational data hygiene required to actually make artificial intelligence work.

TL;DR  

If you do not want to read this, here’s the full length video interview.

Everybody else, please read on.

The Business Context: Bespoke Service at Scale  

To understand their technology strategy, you first have to understand their business. Map Communications is a nationwide, employee-owned (ESOP) virtual receptionist and bespoke answering service operating across the US, Canada, and the UK. They serve a wide array of clients, ranging from legal firms and SMBs to large enterprises in various industries.

Because their core service is highly specialized, Map relies on its own proprietary, homegrown software lineup to manage day-to-day operations and real-time answering services. However, when it comes to managing the customer lifecycle from the moment a prospect lands on their website to the execution of contracts and ongoing support, they rely on the Zoho suite.

The Age-Old Dilemma: Buy vs. Build  

As businesses grow and their processes add complexity, leadership is inevitably faced with a choice: do we build custom modules into our core software or do we buy an off-the-shelf solution?

Dani approaches this with a highly disciplined decision framework. Map evaluated their requirements and realized that building tools to manage vendor and customer contracts or constructing a native quoting tool that would expose their internal APIs simply wasn't a valuable use of their development capacity.

Instead, they followed the Pareto principle and applied an 80/20 rule. As Dani rightly pointed out, "If 80 percent of the requirements are met, we'll be fine because no system would have 100 percent software requirements". Chasing those elusive final 20 percent now often results in over-engineered, heavily customized systems that become a nightmare to manage and support later. By accepting the solid 80 percent requirements fit that tools like Zoho Contracts and Zoho CRM offered, Map Communications avoids unnecessary technical debt while keeping their internal developers focused on their core, proprietary service offerings, the very ones that differentiate Map Communications.

Decluttering the Stack and the "Evil" of Copy-Paste  

One of my core theses as an industry analyst and consultant is that the "copy and paste" of data is the root of all evil, well, at least much of it, in enterprise software. Dani wholeheartedly agrees. When data is manually moved or fragmented across multiple systems, automations break, billing mishaps occur, and the customer experience suffers.

Still, it is often necessary,

Map Communications deliberately architected a separation between their real-time operations and their CRM environment. They utilize Zoho Data Bridge to move data smoothly into Zoho CRM, Zoho Desk, and Zoho Analytics asynchronously, ensuring they don't burden their live, day-to-day answering systems with heavy real-time external integration calls.

Furthermore, they are looking to Zoho Social to centralize their marketing technology, aggregating Google Ads, LinkedIn profiles, and Trustpilot reviews into a single pane of glass. The goal is clear: declutter the system. By minimizing the number of distinct data silos, Map establishes an authoritative data source, a single source of truth.

This isn't just about clean reporting. As Dani wisely noted, the highly anticipated "agentic AI" that every vendor is currently hyping is practically useless without properly governed, centralized data. If your AI doesn't know which system holds the truth, it cannot act effectively on your behalf.

Knowing When to Ask for Help  

Another trait of a mature organization is knowing when to raise a hand and ask for help. Map Communications’ journey with Zoho began around 2021, and they initially worked directly with Zoho's professional services teams, who worked tirelessly across time zones to pull off a complex legacy migration.

However, as they acquired more businesses and faced tighter integration timelines, they didn't hesitate to bring in specialized external implementation partners, like Workflow Academy, to accelerate the process.

As a consultant myself, I always appreciate a leader who recognizes the value of an outside perspective. External partners bring cross-platform experience. They have seen migrations from Salesforce, Zendesk, or Freshdesk, and can help organizations avoid costly architectural mistakes early on. At the end of the day, this is mostly cheaper than running into a sequence of snafus. The key, according to Dani, is ensuring that the vendor provides thorough documentation and cross-training so the internal team isn't left in the dark when it's time for the next iteration.

Past the Honeymoon Stage: Looking to the Future  

Map Communications is well past the "honeymoon stage" with their CRM vendor, entering that mature, long-term marriage phase where continuous improvement is the name of the game. And so far, this marriage seems to be a happy one.

But no software relationship is perfect. When asked for the one missing feature he desperately wants to get from Zoho, Dani didn't hesitate: a unified single sign-on that allows C-suite executives to toggle seamlessly between their multiple, distinct Zoho instances without having to constantly log in and out.

Consider the pressure publicly applied, Zoho!

Ultimately, Map Communications proves that a successful CRM strategy isn't about buying the most expensive system on the market. It’s about rigorous data governance, pragmatic vendor selection, avoiding scope creep, and relentlessly focusing on communicating value to the customer.

Three Key Takeaways for Pragmatic Tech Leaders  

As we wrap up this insightful conversation, a few core themes stand out that any organization evaluating their software architecture should take to heart.

Embrace the 80/20 Rule: Chasing a system that perfectly fulfills 100 percent of your business requirements will lead to over-engineering, scope creep, and bloated budgets. If an off-the-shelf solution meets 80 percent of your needs, accept it, work around the remaining 20 percent, and avoid building costly, complex custom systems on top of it.

Clean Data Precedes AI: The industry is still not stopping to buzz about agentic AI, but as Dani correctly highlighted, AI is completely dependent on having an authoritative, decluttered data source, a single source of truth. Eliminating manual workarounds because copy-pasting of data across systems is truly evil, and harmonizing your core tech stack are absolute prerequisites for any future AI success.

Demand Knowledge Transfer from Partners: Recognizing when you need external help for complex software migrations is a sign of mature leadership. It is a strength, not a weakness. However, when you do bring in outside consultants or vendor implementation teams, you must mandate thorough documentation and cross-training. Your internal team needs to be fully empowered to manage, fix, and iteratively improve the system long after the consultants have rolled off the project.I am already looking forward to checking back in with Dani in the course of the next year to see how Map Communication’s preparations for agentic AI going forward and eventually help the company.

The Lost Strategy: What CRM Was Supposed to Be

CRM at its very origin, was a strategy. With the advent of systems that support the execution of this strategy, the term more and more got shifted to describe a system. This shift can get seen in the words of CRM GodfatherPaul Greenberg. His pre-2009 definition of CRM was “a philosophy and a business strategy, supported by a system and a technology designed to improve human interaction in a business environment.” This changed to "Customer Relationship Management is a technology and system that sustains sales, marketing and customer service activities. It is designed to capture and interpret customer data, both structured and unstructured, and to sustain the management of the business side of customer related operations. CRM technology automates processes and workflows and helps organize and interpret data to support a company in engaging its customers more effectively" in acceptance of this change (emphasis by me). These days, people often even mean a sales force automation system, when they say “CRM”.

In another dimension, the systems themselves more and more turned into systems of record. Implementations often were management-oriented as opposed to team-oriented, which led to increasing dissatisfaction and the creation of new terms and categories like social CRM, system of engagement, customer data platform, customer engagement, customer experience management, and so on.

There is much more, but in consequence, CRM lost both, the “C” and the “R”. CRM turned from a strategy into a glorified rolodex and a tool to manage teams, in particular sales teams, instead of helping organizations and teams to manage and improve the customer relationship.

The Great Divide: The Gap Between Sales and Marketing

As CRM turned into a sales tool, obviously marketing and customer service needed their own tools. Which vendors happily supplied, up to an extent that the 2025 Martech Landscape Supergraphic counts well above 15,000 applications. This marks a 100x growth since 2011. The number of sales or service-oriented SaaS applications is similarly substantial.

In the era of on-premises software, technology purchasing was centralized. The CIO controlled the strings of the wallet. But the rise of SaaS brought with it the era of decentralized budgets. Suddenly, a VP of Marketing could swipe a corporate credit card and purchase a Marketing Automation Platform without consulting IT or Sales. Simultaneously, the VP of Sales was buying their own "best-of-breed" tools for outreach, forecasting, and enablement.

Shadow IT raised its ugly head.

The Accelerant: SaaS and the Era of Shadow IT

If the reduction of CRM to a sales tool created a crack between Marketing and Sales, this combination of decentralized purchasing with the explosion of the SaaS model turned that crack into a chasm.

This “democratization” of technology happened without operational guardrails.

Marketing bought tools to generate leads.

Sales bought tools to close deals.

Customer Success bought tools to manage tickets.

None of these systems were designed to talk to one another natively. Integration became an afterthought. We traded a unified strategy for a "frankenstack" of disconnected applications. This technological anarchy created disjointed processes and solidified organizational and data silos. It meant that "Marketing Ops" and "Sales Ops" spent their days managing their specific tools, optimizing their own KPIs, rather than improving the customer journey and lifecycle. The proverbial shouting match between the VP of Sales claiming that sales doesn’t get any leads from marketing with the VP of Marketing countering that sales just doesn’t use them is a visible sign of this result.

The Emergence of Revenue Operations (RevOps)

RevOps emerged out of the necessity to overcome this. It “is the strategic integration of sales, marketing and service departments to provide a better end-to-end view to administration and management, while leaving day-to-day processes within the departments. The holistic approach of RevOps is designed to break down silos between departments.”  RevOps’ objective is not just to align people, but to reign in the chaos of a decentralized tech stack that had spiraled out of control.

And importantly, RevOps is not a software tool, although there is an increasing number of RevOps and RevTech vendors. Still, it is mostly asking the wrong question. It asks “How can we align our teams to reduce friction?” While RevOps uses outside signals, it is still about fixing the machinery to be able to increase business, improve the margin, reduce cost, etc. It looks from the inside out. The key levers are organizational alignment, improved data flows, better integration and last, but not least, in-depth analytics and dashboards. In short, it establishes the operational backbone, the plumbing that enables inter-departmental cooperation based on shared data.

The Paradigm Shift: Why RevOps is a Part of CRM

The real question to ask is “How can we better help the customer become successful (and thereby become more successful ourselves)?”

In the rush to adopt the latest buzzwords, we, the tech industry, have made a critical error. Driven by vendors, analysts and consultants, we have started treating Revenue Operations as the successor to CRM. We look at RevOps as the "new and improved" version of CRM that makes the old concept obsolete. And just to be clear, RevOps is even more about the transaction than CRM ever was. Look at Gartner’s infographic titled “Is it time for RevOps?” as a good example for this (free, but behind a registration).

This is a fundamental misunderstanding of what CRM actually is.

If we accept Paul Greenberg’s original definition that CRM is a business strategy designed to manage relationships, then the hierarchy becomes clear. RevOps does not replace CRM; it serves it, improves it. And yes, to do this, it needs technology and systems.

Inside-Out vs. Outside-In

To better understand why RevOps supports CRM, we have to look at the main thinking flow of these two concepts.

CRM starts with the customer and helps us identify what we need to do to make the customer successful within the constraints that our business has. It is "Outside-In." It asks: What does the customer need? How do they want to engage with us? How do we solve their specific problem? CRM is a market-facing philosophy that puts the customer at the center of the company and dictates how the company sets itself up to better serve this customer. The customer is the way.

RevOps, on the other side, is "Inside-Out." Revenue Operations, by definition, focuses on the machinery of the business. It looks at the fragmented mess of departments, sales, marketing, customer success, finance, etc. and asks “How is our data flowing? Are our APIs connected? Do our KPIs align?” RevOps is the harmonization of internal processes to remove friction. But "removing friction" is not a strategy in itself; it is an operational challenge. RevOps is a philosophy that helps optimizing internal processes so that the business can become more successful. The customer is the means.

The Engine Room of Strategy

For the last decade, companies have failed at CRM strategy because they lacked the necessary outside-in thinking to support it.

The strategy (CRM) promised a 360-degree view of the customer that helps businesses serve them better.

The reality (SFA) delivered a disconnected database where Marketing data didn't match Sales data.

This is where RevOps enters the picture. RevOps is the "how" to CRM’s "why."

When Marketing Ops and Sales Ops emerged, they were band-aids to fix department issues. They optimized locally. RevOps unifies these functions to optimize globally. It constructs the internal plumbing, the unified data model, the shared technology stack, the handoff SLAs, etc., that finally makes the outside-in promise of CRM possible.

But that’s it. RevOps does not replace CRM.

The Verdict

We must stop viewing Revenue Operations as the silver bullet that makes CRM irrelevant. Instead, we must recognize the dependency:

CRM is the destination: A business strategy that puts the customer at the center of all business operations.

RevOps is more of a tactic: it provides the operational infrastructure that is required to get there.

RevOps is therefore not the new CRM. RevOps is the operational backbone that allows CRM to function as a strategy, instead of just being a piece of software.

Restoring the Promise

For the past thirty or so years, businesses have been chasing a ghost. They spent billions on CRM software and made CRM the biggest market in enterprise software. They were made believe that all it needs to unlock customer loyalty and revenue growth is a license key or a subscription. Instead, they ended up with expensive digital rolodexes, systems that are geared for management, dismal adoption, and teams that speak different languages.

We, as an industry, failed because we confused the map with the terrain.

CRM is the terrain. It is the strategy. It is the outside-in philosophy that says the customer relationship is the single most important asset a company owns, and that this asset appreciates the more the company helps the customer be successful.

RevOps is the map and the compass. It is an inside-out discipline. It is the tool that provides the operational framework, the harmonized data, the integrated tech stack, and the aligned KPIs that are required to navigate that terrain.

Revenue Operations is not a replacement for CRM; it is a tool that helps linking internal processes to customer experience. One could say that it is the acknowledgment that you cannot have a seamless external customer experience if your internal operations are fractured by siloed tools and competing metrics.

So, stop looking for the next piece of software to save your sales numbers. The solution isn't in the tool; it's in the wiring. If you want to realize the strengths of the strategy of Customer Relationship Management, you must first build the engine of Revenue Operations. Want help? Contact me!

Beginning of September 2025, the CRM Magazine published its 2025 CRM Industry Leader Awards on Destination CRM. This year, the awards nominate five outstanding companies across eleven categories. As in recent years, CRM Magazine asked some renowned analysts to chose Industry Leaders for 2025 using a simple question: “If you had to recommend a CRM solution—whether an enterprise suite, contact center infrastructure, or a customer data platform—to a client, what would they choose, and why?”

And, of course, the analysts – being analysts – gave their answers. And good answers they are.

But this is not the topic of this post. 

What is it then? Glad you asked …

It is about the term “unified customer experience platform” and the corresponding award category. Looking at the winners and their corresponding descriptions, it turns out that there seems to be a clear dominance of customer service and contact center solutions in this area – with the exception of the honorary mention of Sprinklr, which has its origins in the social media sphere.

This dominance suggests that customer experience is somehow made equivalent to customer service. This shows quite some success of the narratives that CCaaS and customer service vendors are telling. This is especially true if very renowned analysts, who are in part thought leaders as well, follow it.

Which somewhat irks me. And it reminds me of how the term CRM got more and more appropriated by vendors of sales force automation, SFA, solutions, until CRM almost became synonymous to SFA, which it isn’t. And never was.

Again, this is not about the winners. They are great and very successful companies in their own rights. But, to me, customer experience platform is not equal to customer service or contact center. It is rather a term that describes a more holistic category. I’d argue that both, customer service and contact center are part of a customer experience platform – if there is one single solution that makes up this platform at all. Or can make up one.

Let’s decompose the term into its three main components, namely “unified”, “customer experience”, and “platform”. 

I want to start with customer experience.

Using the definition of Paul Greenberg, customer experience is “how a customer feels about a company over time”. Bruce Temkin defined customer experience similarly as “the perception that customers have of their interactions with an organization”. So, let’s just roll with these. 

Both, especially Temkin’s definition, are about multiple interactions. Neither limits the type of interactions. So, essentially, the customer experienced is a result of all interactions, across all channels and on all journeys customers are when interacting with a company. This is the complete customer life cycle. From a CRM point of view, this includes marketing, sales, and service. It also includes interactions with products or services themselves. 

What both definitions implicitly include is the notion of measurement; so, it needs an analytics component.

The basis for all of this is data, reliable data. Data that covers all (digital) interactions that a customer has with a brand, which makes up a customer profile.

This brings us to the term “unified”

Customers interact with companies on a variety of channels. In order to make this interaction data really useful, companies must work on creating a unique profile of a customer, i.e., harmonize or unify customer profiles from several, potentially disjoint sources, to become a single authoritative one that enables the reliable identification of a customer. 

The data coming from different sources also requires a governance process. How does the data need to look like, how can the underlying data structures be amended or changed, which data sources exist, and which take precedence, who owns it, who is able to change or interfere, how does data age? All these questions, and more, need to be answered.

Me being me, I will add that customer consent is an essential part of all this. 

For a customer to have an individual experience, this data needs to be activated and be supplied to the downstream systems with which the customer interacts. I’ll call this an engagement. This requires omnichannel capabilities, if not even the ability to be channel agnostic. The customer interactions often, if not mostly, need to be personalized, at least to some degree. In some instances, interactions also require real-time capabilities. This is necessary e.g., when engaged in a chat with a digital agent or a customer service agent, or even when a promotion shall be served to the web site. In other situations, timing requirements are less strict. 

To round this off, a notion of journey and journey orchestration is required. After all, customers are interacting with companies to get a solution to a problem or just some information. In any case, some steps, often across channels, are required to accomplish this. These steps need to be orchestrated to be most effective for both parties, customer and company.

Last, but not least, platform

According to Merriam Webster, a platform in a computer science sense is “an application or website that serves as a base from which a service is provided”. The service in this case is customer engagement with the goal of the customer having a good or better customer experience. Note, the systems do not “deliver” an experience. They allow the customer to have one.

The platform provides the scalability of the overall system. It also provides the APIs that are necessary to effectively and efficiently communicate with potential up- and downstream systems. Plus, it provides the foundation for storing and activating the data, so that it can be used for individual interactions. Technically, this is the strong analytical component that I referred to above, and which is also necessary for the journey orchestration component. As customer requirements change, the analytics component needs to be supported by an AI / machine learning solution.

And what does this mean?

In the first instance this means that the appropriation of the term unified customer experience platform by customer service and CCaaS vendors diminishes the value this type of platform can deliver. It also means that there is a sore lack of a definition. During the 2018 CRM Evolution conference, I spoke about rethinking CRM to become CEM. As part of this, I proposed a customer experience architecture, which I think is still relevant.

I defined this architecture an open platform that consistently receives customer signals and processes these data (legally) in a way that companies can serve customers with information that is relevant for them in context. One of the core objectives is to break down silos, department silos as well as data silos. Today, I will go a few steps further.

Unified Customer Experience Platform – a definition

A unified customer experience platform is an open software solution that enables businesses to engage in consistent and personalized interactions with customers, across all touchpoints and journeys, based on a unified customer profile.

This definition caters to all the points I discussed above. 

On checking, it is also quite close to the definition of a delivery CDP by the Customer Data Platform Institute. 

So, a unified customer experience platform might rather be a concept than a software category. This is actually what I do think.

But more importantly: What do you think?

The news

I had the pleasure of spending two days at the Creatio NoCode Days in the Ritz-Carlton in Orlando, together with customers, partners and some fellow analysts to learn about what is new and to generally learn more about Creatio itself.

The event itself showed a very vibrant community of customers and partners.

On topic, in a nutshell, the event was all about whether and how AI reshapes business software, its creation, deployment, use and the corresponding impact on a business’s ecosystem.

Creatio reiterated its four pillars of having AI at the core, AI being actionable, creating unified data through AI and offering a composable architecture, demonstrating this with four core agents, the marketing, sales, service, and studio twins, and how they help users become more efficient. Based on these pillars, Creatio enables customers to have fast turnaround times when implementing necessary changes. This drives a high user adoption and satisfaction plus a low total cost of ownership.

It also changes the role of the CIO and, equally crucial, of implementation partners. CIOs morph more into partners and advisors for the business units while implementation partners focus less on the actual implementation but on identifying the value of an implementation, therefore turning more into consultants.

There have been a multitude of customers and partners – on and off stage – who shared their experiences. Extreme ones include the functional replacement of a failed CRM implementation in a mere weekend and a seven thousand seat implementation with a 100 per cent user adoption that the company attributes to the flexibility of the system and the users’ ability to (within limits) adapt the system to their needs.

The bigger picture

The increasing popularity of no-code and low-code development environments combined with the advance of AI has the potential to dramatically change the world of business software. For several decades now the make or buy decision is in favor of buy because buying a prepackaged software is strongly supported by economies of scale.

Of course, the downside of this is that software regularly needs to be configured (i.e., adapted using tools that require no coding) or customized (including tools that require coding) to fully support business needs. Depending on functional gaps, this causes considerable implementation time and cost after buying or subscribing to the software. Configuring or customizing tasks regularly need to be performed by specialized people, external consultants or dedicated in-house personnel. This often causes slower than desired progress. None of this did really change in times of SaaS. Consequently, the time to value for customers is often still quite long. A positive side effect for vendors is that this tends to create a buyer lock-in while systems integrators can make tidy time and material revenues.

In come no-code and low-code development environments and business applications that are built and delivered on top of these platforms. This has two effects. First, it becomes fast to develop new business applications as limited or no technical knowledge at all are required. This leads to removing above mentioned bottleneck by broadening the pool of people that are able to build or adapt applications for business needs – the so-called citizen developer has been born. The impact of a no-code platform is even bigger if it gets delivered as a part of a business application, i.e., if the application itself is already built on it.

Lastly, generative AI services can boost this effect a lot. Vibe coding is in everybody’s mind and some business leaders already predict a 100x productivity increase. Whether these predictions are spot-on or optimistic, a significant productivity increase will not only be seen in developing new applications but also in their adaptation to customer needs – the configuration and customizing process.

My analysis and point of view

Whoever I talked to during the event spoke about three things.

• Fast time to value
• Low TCO
• High user acceptance rate

So, Creatio is certainly up to something. One thing that contributes to this on the user side is the strong emphasis on making the interaction with the system follow human communication patterns, i.e., conversational, while being available where the user is instead of forcing users to work within the application frame. The other part is terminology. While every vendor, including Creatio positions its AI agents as helpers that take away onerous tasks, employees often see them as a threat rather than as helpers. Creatio addresses this by going a smart step further. The company names its agents “Twins”. This is a term that has far more positive connotations. A twin is not a threat but instead one’s best friend.

The second point is that we actually might be at a tipping point that flips the business applications playbook. For years vendors have made the point that it is far more efficient to deliver prebuilt software that works around “best practices” and is adapted to industry and customer needs when needed. Especially with cloud software, customizing capabilities were drastically reduced, compared to on premise solutions. One thought behind this is the avoidance of changes where a company is unlikely to have a differentiator. A mostly unacknowledged one is that maintenance is far easier for the vendors if customizability is limited.

As a result, the implementation of business applications became cumbersome, lengthy, and expensive. The combination of powerful no-code environments and generative AI has the potential to flip this calculation. If this flip happens, Creatio and a few select other vendors are uniquely positioned to take advantage of it. Evidence for this are a focus on the midmarket and the lower end of the enterprise market, an ecosystem that already now has understood that systems integrators need to offer high value services and turn into consultants and customers praising fast implementations and low TCO. Another indicator is the genuine care that Creatio exhibits for its customers. CEO Katherine Kosterova says that she wants to continuously “delight customers, no matter what”, but what Creatio really is doing is having its customers backs. This is effectively even better as it does not create the same vicious circle that the objective of “continuously delighting” customers does.

What remains is getting more attention. With events like the NoCode Days, working with analysts and showing successes, Creatio is on a good way here, too. The challenge remains to continue to send signal in an ocean of noise.

And maybe the signal that the age of packages software is past its zenith is just that signal.

During ZohoDay2025 I had the pleasure of having a conversation with Udit Pahwa, CIO of Blue Star Ltd. Blue Star is a nearly 80-year-old company, based in India, which is a leader in cooling solutions for both the residential and commercial market. The company offers a variety of cooling products, including deep freezers, air conditioners, and chillers. Solutions are provided through direct sales, channel sales, or a combination of both.

Blue Star went through a series of five CRM proof of concepts, evaluations and implementation attempts with limited success before settling on Zoho CRM. Blue Star certainly has been a “burnt child” at that time.

The main reason for Blue Star deciding for going with Zoho CRM is that Blue Star did not want to go for what Pahwa calls a canned solution. Zoho offered the willingness and ability to co-create a solution that is tailored to Blue Star’s needs. “They're ready to tailor it for us. That was a big advantage” he says.

Before embarking into this sixth implementation, Blue Star performed what Pahwa calls an introspection to find out why there was no adoption but, in fact, resistance. He says that “what we came to know is any CRM for a sales guy is looked upon as moral policing”.

This is not terribly uncommon and can be addressed. Blue Star chose to work with a comprehensive set of three levers to drive adoption.

Here you can watch the full conversation with Udit Pahwa,

The company started with executive sponsorship and a top-down approach in a division that had what Pahwa calls a “visionary leader who was also a technology enthusiast. This leader set a goal to eliminate spreadsheets and to only use a digital platform, which helped drive user adoption of Zoho CRM within that division.” This sent the clear message that the implementation is not yet another implementation that doesn’t matter but that it is important for the company. In addition, this strategy facilitates doing a further roll-out on the back of a successful implementation (or limits the losses in case of a failure).

Second, Blue Star answered the important question “what is in it for me” that the sales reps have. The sales teams’ concerns were mitigated by explaining and later showing how unproductive time would be reduced by the CRM via eliminating spreadsheets and significantly simplifying visit reports. This way, sales reps spend less time with administrative parts and instead can do more of what they really want – spend time in the field with their customers. “So, no more filling out of spreadsheets, no more creation of visit reports, uh all the manual stuff which they used to get into. We said you don't need to do part of it will be done on by the app and part of it you will have to do it on the app, and it will format everything for a review.”

The sales teams seem to have understood and believed this. What also helped was that the new system was no more referred to as a CRM system but as a “sales organizer”. This contributed to positioning the system as a helper instead of a monitoring tool.

“So I think they realized that as we are growing their unproductive workload is going to grow even further and here is a tool which will help me reduce my unproductive time so that I have more time to spend in the market with the customer and I don't have to worry about all the administrative tasks which I need to do in the back end.”

Instead, the system digitalized a good part of the workload. The system minimizes the need for input into a visit report to five or six structured fields, automates the summarization, reporting and analysis, helping both, the sales reps and back-office staff who are relieved of the cumbersome consolidation of reports that came in via Excel spreadsheets. In addition, this enables the system to draft a route plan for the sales reps, facilitating their planning. In Pahwa’s words “that took out a sizable chunk of admin work for the users as well as the supporting staff who were attached to the users”. And this is also where Blue Star sees the way ahead with the sales organizer. Next steps include the evaluation of AI powered speech to text technologies to further reduce efforts. Instead of typing, sales reps will then be able to dictate visit summaries etc. This input then shall be converted to text and then automatically populate the CRM.

Of course, users have to pay a price for this, which is mandatory use of the system. Managers won’t accept reports in the form of spreadsheets anymore and require that all pertinent data is entered into the sales organizer. Basically, the approach is that “if it ain’t in the system, it doesn’t exist”. This again is facilitated by offering all sales reps and managers personalized dashboards that give real-time insight into budget vs. actual sales, also thanks to an integration into the SAP ERP system.

One could say that this is a kind of a carrot and stick approach, however one with a considerably sized carrot and a fairly small, yet effective, stick. Especially since Blue Star plans to make work with the system even easier and more beneficial for the sales reps.

The result? Success. “… this worked well and we had near 100% adoption with that business division so much so that their pipeline of leads I think went up by about 35% and they were able to attract a larger business you know under their fold because for us in the in the commercial air conditioning segment the more leads you have the more chances are for the conversion and growth of business. So that worked well for them.”

This, in turn, caused the other divisions to get on board, or as Pahwa says “When this was a success in one business division it started having a rub-off effect across the organization and as we speak today the entire sales organization is live and 100% adopting the my sales organizer which is the Zoho CRM.”

In summary, Blue Star worked with a smart combination of decisions that turned out to be a winning strategy to achieve the goal of 100% user adoption and to drive business through it.

• With Zoho CRM, Blue Star chose a flexible tool.
• With Zoho, Blue Star found a partner that was willing to co-create a solution with them.
• Blue Star promised and delivered significant value for the sales reps and not only for their managers.
• Blue Star moved away from the term CRM, which was a burnt and positioned the tool as a helper, naming it sales organizer.
• There is executive buy in to the solution with not only sales reps being mandated to use it but also managers and executives wanting to use a system.

Fresh from the 2025 SugarCRM Analyst Summit, waiting for my plane home, it is time to sort my thoughts.

From Monday, 1/27 evening to Wednesday 1/29 in the morning we had some time jam packed with information and good conversations with SugarCRM execs, customers, and in between analysts. The main summit started with a bang, namely the announcement that industry icon Bob Stutz joins the SugarCRM board of directors, which is something that few of us, if any, had foreseen. This is exciting news.

With David Roberts, who succeeded Craig Charlton in September 2024, SugarCRM itself has a new CEO with a long time CRM pedigree.

As with every leadership change, this promises some change. Every new CEO evaluates what they see vs. where they want their company to go and then, together with the team, establishes and executes a plan to get there. Usually, this involves some change in the structure of the executive leadership team, too.

This is what happened and happens with SugarCRM. The company had and has a strong leadership team, with new faces like Paul Farrell (joined in March 2024), Jason Glass, and soon a new Chief Customer Officer – although with Christian Wettre or Chris Pennington some other strong players left for various reasons.

As I have written in the past, the company has a great yet varied history and, more importantly, potential due to great software. What SugarCRM to some extent is missing is a distinguishable identity. In a market that is as crowded as the CRM/CX market, differentiation is of crucial importance. As I have said and written before, SugarCRM’s messaging needs to change to avoid being perceived as a “me too” product.

Functionally, SugarCRM has a competitive sales solution, and fair marketing- and customer service solutions, plus a number of add-ons, some of them really interesting, e.g., sales-i, its intelligence add-on or Sugar Connect, which makes Sugar available outside the application frame. Whenever I conduct a software selection for clients of mine, I witness the strength of the Sugar Sell solution myself. It regularly makes it at least amongst the finalists and often gets selected by my clients. This is not only due to its capabilities but also thanks to strong performances and demos by the Sugar sales teams. And this is in spite of Sugar Sell resembling more of a toolbox than a preconfigured solution with built-in processes. Again, this is testament to the functional strength of Sugar Sell (although it has some deficiencies, too).

From a messaging point of view, really everyone (and their dog) talks about platform and being a CX player. SugarCRM needs to change away from these two points, as they also do not communicate much about outcomes, let alone value.

And Sugar will do this. More about this in a bit.

So far, Sugar’s value proposition revolves around the platform, automation, and discovering opportunities. Targeted personae include marketing, sales, and service leadership, although the winning chances in marketing and service against formidable opponents like HubSpot or Zendesk are slimmer than in the sales area – which does not mean that customers who chose Sugar Market or Sugar Serve are unhappy, on the contrary! Still, I regularly heard from Sugar executives that “we tend to win, when the customer need is sales, and not marketing driven.”

In addition, the messaging is a little about everything for everyone. It is not that Sugar doesn’t deliver but the value is not immediately clear. Add to that the fact that the flexibility offered by Sugar lets the fresh application appear a bit like a toolbox rather than a ready-to-use system.

To be fair, Sugar initiated a transition already more than a year ago, based upon the realization that the company is highly successful in the manufacturing, wholesale and distribution markets, in particular in the mid- and upper mid-market. This created an obvious focus area for the company. Yet, the message didn’t evolve enough to support this change.

After the analysis done by David Roberts and his management team, this is subject to change. One of the words we heard over and over during the analyst summit is “focus”, the other one is “aligned execution”. Both are terms that I strongly associate with Bob Stutz, so I see a formidable alliance of seasoned executives with similar values and passions joining forces now.

Which leads me to the strengthening of Sugar’s transition

David Robert’s vision for SugarCRM can be summarized with “boldly focus on our strengths while not forgetting about our customer base – and be clear about it”. The new Sugar strategy, including an upcoming more specific tag line revolves around it, from a product- and technology view, but encompassing GTM and partner strategy. Stay tuned, I cannot and will not take away the thunder. So, a drumroll here …

My point of view and analysis

The strategy is straightforward and consistent. As said, it builds upon earlier realizations and extends a change that is ongoing for more than a year now.

Its risk, apart from the human aspect (not everyone lets readily go of ingrained habits) lies in not to antagonize the existing customer base outside the sharpened ideal customer profile (ICP). This requires a balance that is hard to maintain. Yet, keeping churn numbers low via word and action is of crucial importance.  So, careful balancing and execution is key. I am quite sure that Bob Stutz can and will give great advice, as he has executed this kind of strategic shift multiple times.

One thing that is really refreshing and creating signal in the noise is the notable absence of “agentic AI”. Instead of focusing on buzzwords, SugarCRM looks at AI as a means to achieve business objectives. I regularly advise my clients that AI is a means, not an end. Communicating it as such is far more powerful than jumping on the buzzword train.

The executive team that we met on the analyst day seems fully on board, which is extremely important, as following through do mean some changes, not in the least some more process rigor and some preparational work, which is ongoing.

Given all this, I am excited about 2025 and 2026 and very interested in seeing how Sugar evolves. Repositioning will take a bit, but I see a sweet future for SugarCRM.

Sorry, I could not resist this one.