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Revenue Operations

Smarter CRMs, Shifting Roles: Why RevOps Still Matters . . . a Lot

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CRMs are evolving fast. So are the expectations on sales teams, GTM leaders - and the RevOps professionals supporting them. With AI promising smarter forecasts, cleaner pipelines, and auto-filled fields, it’s natural to wonder: do we still need RevOps? And if so, where exactly should it focus?

In this webinar hosted by Matthew Volm, CEO of RevOps Co-op, Rob Kramer (VP of Sales at Revenue Grid) and Dom Cronshaw (Director of GTM Ops at Object First) dig into the operational reality of AI, the limits of automation, and the irreplaceable role RevOps plays in driving consistent growth across the funnel.

Spoiler: RevOps still matters - a lot. But the job is changing.

Enforcing Data Hygiene: Still a Necessary Evil?

The conversation kicks off with a live poll: are you spending too much time enforcing data hygiene? Over 70% of attendees say yes. No one is surprised.

Dom Cronshaw reflects on his own journey: managing hundreds of millions of dollars in revenue renewals in spreadsheets, chasing reps to update fields, constantly correcting close dates, and battling systems designed for rigidity rather than agility. And while CRMs are improving, the operational burden hasn't gone away - it’s just moved.

“I never understood the people who wore ‘data nerd’ shirts,” Dom joked. “I don’t love data - I love action. Data is only useful if it leads to growth.”

Rob Kramer added another layer: the rise of disconnected engagement tools - like Gong, Outreach, DocuSign, and email plug-ins - has led to a fragmented data landscape. Information lives in too many places. Without intelligent centralization, your CRM becomes more of a chaotic database than a revenue platform.

To actually fix data hygiene, the panel agrees, you need to go upstream: better tools, better processes, and clearer answers to the question, “Why are we tracking this in the first place?”

As much as we’d like to say that ignoring the pipeline hygiene problem is fine, it’s in every revenue operator’s best interest to find a way to fix it. Check out this blog post on 9 Easy Fixes for Better Pipeline Hygiene.

AI Won’t Fix Broken Processes (But It Will Expose Them)

AI isn’t replacing sales or operations teams anytime soon, but it is forcing companies to confront inefficiencies they’ve long ignored. As Rob put it:

“AI doesn’t eliminate risk - it exposes how little you actually understand your pipeline.”

He shared how Revenue Grid uses AI to highlight deal risk in real time, giving sales leaders daily visibility into the signals that matter - like multithreading status, engagement gaps, and key stakeholder alignment. This reduces hiding, delays and surprises.

“There’s no more hiding,” Rob said. “If a $100k+ deal isn’t multithreaded by a certain stage, I want to know.”

AI makes it easier to run strategic deal reviews and lets executives skip over layers of middle management to get straight to the truth. But you still need systems to interpret those insights and teams willing to act on them.

Matthew added that if you're spending any time at all enforcing data hygiene - let alone building dashboards from scratch - you’re probably behind. AI should reduce the manual lift, but only if it’s layered on top of good processes. Without clarity on what you’re measuring and why, AI will just automate bad habits.

Account and contact data management is one of the most overlooked—but high-impact—areas in revenue operations. Check out our blog post on Data Management for Busy RevOps Pros for where to focus first.

Forecasting and Slippage: A Process Problem, Not a Technology One

One of the most valuable insights from the discussion was the framing of slippage - not as a forecasting failure, but as a leadership and accountability failure.

Dom put it simply: “It’s not a sin to lose a deal. It’s a sin to take forever to lose a deal.”

Slippage happens when deals are allowed to linger in pipe with no real momentum. That’s not always on the rep - leaders often push unrealistic close dates, fail to inspect pipeline proactively, or avoid uncomfortable conversations around disqualification. According to Rob, slippage is often a reflection of unrealistic expectations, inadequate multithreading, and poor qualification discipline.

To reduce slippage:

  • Standardize deal inspection criteria (e.g., is the deal multithreaded by Stage 3?)
  • Introduce “proof of life” questions: “If this doesn’t close, why not?”
  • Create a culture of transparency, where calling a deal closed-lost isn’t punished
  • Build systems that show pipeline health by rep, team, and stage—not just volume

Forecasting accuracy improves when you design for process quality, not just CRM inputs. That’s where RevOps shines - by building frameworks that let leadership ask better questions.

If you’re looking to align the sales team’s actions with what the business requires, check out this blog post on 5 Steps to Better Forecasting in Salesforce.

Where AI Can Truly Help (And Where It Falls Short)

Rob and Dom each shared how their teams are using AI successfully - and where they’ve hit limitations.

Dom described using Revenue Grid to automatically generate meeting summaries and identify deal risk from call transcripts, even when the CS or RevOps team wasn’t present on the call. He also noted that sentiment scoring and engagement metrics help prioritize coaching and interventions.

But there’s still work to be done. Rob shared how AI struggles with data analytics, math, and financial modeling.

“It’s not built to handle spreadsheet-style logic or statistical comparisons,” he explained. “If you're looking for AI to be a financial analyst, you're going to be disappointed.”

Another limitation? Contextual nuance. Dom shared an MIT study where users of LLMs (large language models) showed weaker learning retention and memory than non-AI users.

“It gives people the illusion that they can think without effort,” he said. “But that’s not how growth happens.”

AI should accelerate your thinking - not replace it.

Without clean data, AI will deliver unhelpful insights and deal-stopping guidance. Here are 10 tips for tackling AI data quality challenges in our webinar recap Ready for AI? 10 Data Quality Must-Haves Pre-AI.

The Changing Role of RevOps

The shift is clear: RevOps is no longer just a CRM admin function. It’s becoming a growth partner across GTM.

Operators today are responsible for:

  • Preventing silos between marketing, sales and customer success
  • Connecting fragmented tools to build a coherent data layer
  • Designing forecasting and deal inspection processes that scale
  • Operationalizing AI outputs and flagging risk for leaders in real time
  • Reducing the burden on ICs by automating data capture and surfacing insights

As Dom put it:

“RevOps sits at the right hand of the growth engine.”

RevOps must also lead the evaluation of new tools. Are you buying platforms that reduce noise - or just adding complexity? Without a clear understanding of how tools affect process design and team workflows, you risk trading one problem for another.

Check out our RevOpsAF Podcast episode RevOps is Evolving, Are You? to hear from Steve Silver (former VP at Forrester) as he highlights market trends, changes in buyer behavior, and the critical role that RevOps plays in bridging organizational silos.

Culture, Coaching, and the “No Hiding” Era

You can’t just drop AI into your tech stack and expect transformation. You need culture to support the change.

Rob emphasized that deal inspection and pipeline reviews must be framed as support, not punishment:

“These tools should feel like a gym, not a courtroom,” he said. “They’re here to make you better.”

That means RevOps needs to:

  • Normalize deal disqualification
  • Reinforce process coaching without micromanagement
  • Ensure AI recommendations are explained, not just delivered
  • Be transparent about how deal data is used and evaluated
  • Build trust across the funnel, so that coaching is welcomed, not feared

Pipeline risk detection is powerful - but only if your team is willing to act on it. RevOps creates that bridge between insight and action.

Sales metrics come in various flavors. Check out this post on Sales Metrics: KPIs to Coaching Tools where we explore common metrics by audience.

Final Word: The Real Job of RevOps

RevOps isn’t becoming obsolete - it’s becoming more strategic, and therefore more important then ever.

As CRMs get smarter, the expectation isn’t that operators do less. It’s that they do better. The real job of RevOps is to:

  • Drive strategic clarity across GTM teams
  • Build systems that capture meaningful data without friction
  • Turn AI outputs into scalable action
  • Support leadership with visibility, not just dashboards
  • Create a culture where speed, honesty, and process quality are rewarded

As Matthew closed out the session:

“AI doesn’t replace people - it replaces lazy processes. And that makes great RevOps more important than ever.”

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