Companies have always wrestled with siloed sales, marketing, and customer success teams. The term “RevOps” to describe this challenge goes back a decade or so, but it really picked up steam in recent years and is now something business leaders everywhere are talking about and investing in.
Gartner predicts that by the end of this year, 75% of the highest-growth companies will operate with a formal RevOps model. At Kuno, we saw this coming and launched a dedicated RevOps department ahead of the curve. The demand we see from clients has only served to validate that decision.
We work with companies across industries that are doing a lot of things right but still experiencing friction in their revenue operations. The challenges tend to follow familiar patterns: teams that aren't fully in sync, data that's hard to trust, tech stacks that have outgrown the strategy behind them, reporting that's better at describing the past than informing what's ahead.
Here are some of the top RevOps challenges and solutions we see and how to address them with an eye toward sustainable revenue growth.
Before getting into the challenges, it helps to be clear on what revenue operations is and, perhaps more importantly, what it isn't.
In a nutshell, RevOps is the system that aligns sales, marketing and customer success around a single revenue engine. It spans the full customer lifecycle: lead generation, qualification, handoff, pipeline progression, deal velocity, onboarding, expansion and retention. When it works, every team operates from the same data, moves toward the same goals and hands off with enough context that nothing falls through the cracks.
But RevOps isn’t a quick fix for a slow quarter. The challenges that it solves (especially fragmented data, misaligned teams, disconnected tools) accumulate and compound over time.
RevOps addresses the system, not just the symptoms.
Not every organization needs a full RevOps overhaul. But if several of these sound familiar, the problem is likely systemic rather than isolated:
These aren't signs of failure, but they do indicate that something needs to change sooner rather than later.
When teams operate toward separate goals with separate KPIs and separate incentives, friction builds across the funnel, despite everyone individually doing their jobs well.
And that shows up in the revenue with wasted budget, slower conversions, lower win rates and a customer experience that feels inconsistent because it is. What makes this particularly frustrating for marketing leaders is that misalignment problems often get misdiagnosed as demand generation problems.
The fix involves:
Use a CRM long enough and, in most cases, your customer data starts to take on a history of its own.
Contacts aren’t cleaned up consistently. Different users define lifecycle stages their own way each time. Lead scores were built on logic that no longer reflects how buyers actually behave. Plus, manual processes introduce human error at every stage.
If this is you, you are far from alone!
Bad data erodes confidence in reporting, produces inaccurate forecasts and makes it harder to defend marketing investment when leadership asks for proof. When teams can't trust the numbers, they often default to gut feel – which is hard to scale and harder to improve.
There is an important difference here between data cleanup and true data governance. Cleanup is a one-time fix, but governance is the ongoing discipline that keeps customer data reliable. That means field standardization, validation requirements, enrichment processes and recurring audits with clear ownership.
The results from good data are powerful and well worth the effort. As an example, we worked with one company that needed to consolidate and clean its data before migrating to a new CRM. By prioritizing data quality before the move rather than after, they achieved 100% sales rep adoption from day one and cut the time spent pulling reports in half.
We see this one all the time. Marketing and sales teams accumulate tools over time. Sometimes to solve a specific problem, sometimes inherited from previous hires. Regardless of the reason, this results in a technology stack that's partially redundant and difficult to optimize because no one fully understands how all the pieces connect.
The bigger problem in terms of RevOps, though, is that disconnected tools limit visibility at exactly the moments when clarity matters most. No single tool holds the full picture, so reporting is fragmented across systems and teams.
The goal should be the right tools, connected well and with clear ownership. One company we worked with, for instance, eliminated a significant portion of its manual processes entirely through better use of tools they were already paying for. This led to a 99% reduction in time spent on tasks that are now automated, with zero additional spend on new technology.
A healthy top-of-funnel can mask a broken handoff process. When leads move from marketing to sales without enough context, or sit uncontacted because routing wasn't built for a specific scenario, conversions suffer while volume looks fine.
The deeper problem is the feedback loop (or the lack of one!) Without it, marketing has no visibility into what happens to the leads it generates, and keeps optimizing for the wrong things.
Fixing this requires:
Plenty of teams have dashboards. Fewer have dashboards that actually change decisions.
The gap usually comes down to what gets measured. Vanity metrics confirm that activity happened but don't tell you whether it mattered.
|
Activity Metrics |
Revenue Metrics |
|
Email opens and clicks |
Pipeline velocity |
|
Website sessions |
Lead-to-close conversion rate |
|
MQL volume |
Customer acquisition cost by channel |
|
Campaign impressions |
Sales cycle length and forecast accuracy |
The problem is that attribution often breaks down because systems and teams aren't aligned, so connecting campaign activity to revenue outcomes becomes nearly impossible. Different dashboards show different numbers and source tracking is inconsistent. As a result, the revenue data describes the past without informing the next steps.
Here’s a great example of this in practice. One client, a benefits management company operating across five internal teams, had been assembling monthly reports manually from disconnected systems. That process consumed an estimated 60 or more hours each month.
After migrating to HubSpot and working from a unified platform with proper attribution in place, that same reporting can now happen automatically. The leadership team gained real-time visibility into how marketing activity connected to pipeline, and the five teams that had been working in silos were finally operating from the same data.
Customer retention and expansion are where RevOps comes full circle. Acquisition fills the top of the funnel, but retention and expansion determine whether growth compounds or stalls.
That’s why net revenue retention, how much revenue you keep and grow from existing customers, is increasingly a board-level metric for good reason. Retaining and expanding customers is more efficient than replacing them.
But the challenge is that customer success teams often operate in isolation. Onboarding data, health scores, and renewal signals live in a separate system that marketing and sales can't easily see. Without a feedback loop on fit and churn risk, upsell signals go unnoticed and retention becomes reactive rather than strategic.
The fix is connecting customer success to the rest of the revenue team. That means tracking retention and expansion alongside acquisition metrics, giving sales and marketing visibility into onboarding and making sure what was promised in the sales cycle actually matches what customers experience after they sign. When the full customer journey lives in one place, growth becomes both more predictable and more sustainable.
With any big challenge, a common instinct is to either try to tackle everything at once or stall because the scope feels overwhelming. Neither solves the problem, though.
Instead, start with the foundations (you can't build scalable processes on top of bad data, and meaningful attribution isn't possible if systems aren't integrated) and prioritize beyond that based on revenue impact.
A first 90-day frame typically includes:
At Kuno, our RevOps work starts with comprehensive discovery: understanding your existing processes, your systems and where things are breaking down before recommending anything. From there, we focus on the work that moves the needle most whether that’s streamlining operations, cleaning and connecting customer data and configuring your tech stack.
If the revenue engine isn't keeping up with your growth goals, that's exactly the kind of problem we solve. Let’s talk.
Editor's Note: May Johnson contributed to this article.