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.

The news

Today, May 22 2024, SugarCRM and sales-i announced the acquisition of sales-i by SugarCRM. sales-i is leading provider of a revenue intelligence solution that helps businesses maximize their revenue and profitability. It targets at making sales professionals more efficient and effective by providing actionable insight into every customer, product and sale.

The acquisition comes nearly a year after Sugar announced a partnership with sales-i to improve business-to-business (B2B) sales performance by delivering AI-powered revenue intelligence that leverages the data of a business's enterprise resource planning (ERP) system and CRM. This combination provides businesses with actionable insights that improve sales, marketing, service and support, resulting in greater revenue and higher levels of retention.

You can read the full announcement here.

The combination of SugarCRM and sales-i combines the detailed transactional data residing in ERP systems with the rich sales data in SugarCRM. According to the release information, his shall create an intelligent data hub enabling customers to successfully execute impactful sales strategies to improv revenue, maximize profitability and increase customer satisfaction.

In this combination, sales-i delivers the revenue intelligence, while SugarCRM delivers the CRM data; both of which are needed for a better sales enablement.

Together, SugarCRM and sales-i intend to deliver the most innovative intelligent account management solution in the marketplace by utilizing leading edge sales enablement technologies provided by both companies and the rich revenue intelligence capabilities provided by sales-i.

The bigger picture

The market for CRM and CX solutions is crowded while only few vendors enjoy significant mindshare. And what is more, both terms, CRM and CX, get increasingly fuzzy as many vendors use them to endorse their own offerings. This results in oddities like a customer service software vendor claiming to have a “complete CX solution” or the term CRM used synonymously to sales force automation.

The same holds true for the term “platform”. Nearly every vendor claims to be a platform vendor – regardless of the breadth or width of the offering. And every single one of them is saying that the platform makes easier for employees and delivers better results for customers.

In addition, triggered by the enormous success of Open AI, every vendor jumped on the AI bandwagon – with most of them delivering more or less the same feature set.

The consequence is a cacophony. There is nearly too much noise to identify any signal.

At the same time, customers start to look more into margin and profitability, which requires targeted solutions that are ready to run without a lengthy or complicated implementation program.

For vendors this means that they need to increasingly concentrate on easy-to-implement business scenarios that deliver a fast return on investment. By nature, these business scenarios must work along and supporting, corporate value chains. Delivering to these business scenarios that show real business value, along with adequate and distinctive messaging, is one important way for vendors to get heard again.

My analysis and point of view

Why am I not surprised about this acquisition?

For one, the partnership has been deep. Second, the combination of SugarCRM and sales-i fulfills exactly the need for easy-to-implement and valuable business solutions that I described above.

Both, SugarCRM and sales-i share a focus on manufacturing industries and have a good standing partnership with a number of common customers. The short-term opportunities for SugarCRM lie in the ability to tap into the mutual other client base to increase its footprint, plus the ability to use sales-i as a door-opener to place SugarCRM in companies that run an ERP but not yet a sales-oriented CRM solution.

Implemented right – of which I do not have any doubts, the incorporation of sales-i into the SugarCRM fold also addresses one of the analytics weaknesses that SugarCRM has. While it is simple to create reports and to display them where it matters also in a graphical representation, the analytics system itself is fairly limited by being ‘in-module’. sales-i should give SugarCRM the capability to deliver more immediately useful, as it is directly actionable, analytics, along with the predictions and recommendations based on it. This complements and enhances what is currently available with Sugar Predict. The combination of Sugar Predict and sales-i does open up some interesting avenues for SugarCRM customers.

The longer-term benefits for both, SugarCRM as well as customers, lie within the data – and AI – realm. The combination of ERP- and CRM data allows for the far more specific and accurate identification of revenue potentials – and the way to realize these potentials.

Having the ability to combine and use both ERP and CRM data natively is something that not many vendors can offer. Top of mind are actually only suite vendors and not CRM (or ERP) specialists. This ability sets SugarCRM quite apart from the CRM/CX competition, which is something that becomes increasingly important in a CRM/CX world that increasingly lacks differentiators, both functionally and messaging-wise.

Plus, given customers’ consents, there is a treasure-trove of data that can be used for additional services, including the comparison of a company vs. an industry or a sector. This could help businesses adding to existing strengths and mitigating weaknesses.

Lastly, SugarCRM now has now increased its ability to get out of the cacophony of vendors. There are now some ways to communicate and demonstrate actual business value that should help in lifting the “let the platform do the work” message to the next level.

This acquisition opens exciting prospects, not only in the short term. Kudos to both, the SugarCRM and the sales-i teams.

This CRMKonvo was supposed to be with Thomas Verly, a highly experienced Sales- and IT leader. We wanted to learn from his experience how to enable sales operations. What is important, what to measure? Do you really need a CPQ system?

Unluckily he could not participate due to the heavy snow storm in Texas that caused major disruption. The good news is that Thomas and his family are safe

Now, the CRMKonvos team has more than 70 years of CRM experience. We are coming from very different angles. So, we decided to tackle the topic, making some good points.

Enjoy this episode and look forward to another one with Thomas Verly. Coming soon!

• Different presentations and panels show that (Conversational) AI and machine learning are of high interest, not as technologies but embedded into business applications. This shows that the vendors are going the right way
• The intersection of marketing and sales is a topic for businesses. There is a good interest amongst the attendees and speakers delivered different and good perspectives on this field of tension
• Organizations seem to struggle with the same issues they had ten years ago. Data silos, organizational silos, inertia. This means that they are still a ways from implementing truly helpful solutions, because they do not have a strategy, not even talking about a plan. What is also lacking is the ability to acknowledge culture as an important driver to achieve this necessary change. This became abundantly clear when the extremely knowledgeable and persuasive Silvana Buljan had an audience of just six people for her highly interesting talk about how to use a cultural transformation program to increase employee satisfaction and then sales.