Navigating the RevOps Automation Maze: My Journey as Matt Slonaker from M. Allen

As Matt Slonaker from M. Allen, I’ve spent years immersed in the world of revenue operations (RevOps), and let me tell you—it’s a wild ride. The pressure to “do more with less” has become a familiar refrain, especially as IT costs climb, systems fragment, and the push to adopt AI intensifies. Recently, I dove into the State of RevOps Automation Report by Zapier, which surveyed over 450 RevOps professionals, and it hit home. The insights mirrored the pains I’ve faced, the challenges I’m still tackling, and the strategies I’m refining to keep my team ahead. Here’s my take on this journey, blending my personal experiences with the data to shed light on what’s working—and what isn’t.

The Pains: Feeling the Squeeze in a Fragmented World

One of the biggest pains I’ve encountered is the sheer sprawl of tools in our RevOps tech stack. The report revealed that 70% of RevOps pros, myself included, manage five or more apps, with a staggering one-fifth juggling 10 or more. At M. Allen, I’ve seen this firsthand—our stack grew as we scaled, especially in the 501-1,000 employee range, where 26% of teams reported handling over 10 apps. The result? Skyrocketing licensing fees, siloed data, and processes that feel like they’re held together with duct tape.

What stings even more is that consolidation alone isn’t the fix. I’ve tried trimming tools, hoping to streamline, but the report’s finding that 53% of teams use multiple automation types to bridge gaps rang true. At M. Allen, we’ve layered built-in automation, third-party platforms, and even custom engineering to connect the dots, yet 36% of our challenges remain only partially resolved. That automation gap is costing us time and money, and it’s frustrating to see only a third of us leveraging automation for revenue-driving tasks like cutting customer acquisition costs or boosting deal velocity.

Another pain point? The disconnect between systems and strategy. I’ve felt the pressure to “make it work” with fragmented tools, often without the bandwidth to craft a cohesive plan. The report quotes Mike Rizzo of MarketingOps.com, who nailed it: teams are treated as tech stack managers rather than revenue enablers. I’ve been there, patching up inefficiencies while leadership demands direct ROI, leaving foundational issues like data hygiene and cross-team collaboration on the back burner.

The Challenges: AI, Adoption, and Alignment

The rise of AI adds another layer of complexity. I was excited to see that 70% of RevOps pros, including me, use AI daily, with 68% pairing it with automation. At M. Allen, we’ve experimented with workflows—like routing tickets from Slack to Notion with AI prioritizing them—and the potential is huge. But the report’s stark contrast at the organizational level hit me hard: only 21% report widespread AI adoption. I’ve seen this play out—while my team embraces AI, the broader company lags, with many colleagues using tools in untrackable ways, raising security red flags.

Barriers like security concerns, lack of knowledge, and budget worries are real challenges I’ve grappled with. I’ll admit, I was skeptical at first—why add AI when automation already saves time? But as Lena Yue from Zapier put it, I didn’t understand the power it unlocks until I tried it. Now, I’m navigating accuracy concerns and the cost-benefit analysis, especially when Sara McNamara from Hyperscayle warned that the wrong use cases can drain resources.

Alignment is another hurdle. The report highlights that 50% of teams aren’t automating cross-team collaboration, despite its criticality for scaling companies like mine. I’ve seen misalignment between departments lead to data accuracy issues, with 36% of respondents citing this as a top remaining challenge. Add in manual data entry and training gaps, and it’s clear we’re not just fighting tools—we’re fighting a mindset mismatch where RevOps is seen as a support function rather than a revenue driver.

My Strategies: Attacking the RevOps Maze

So, how am I tackling these pains and challenges at M. Allen? The report’s insights have guided me to a strategic approach, and I’m putting it into action step by step.

1. Conducting an Automation Audit to Tackle Tool Sprawl
I started by mapping our tech stack—listing every tool across the revenue cycle, from CRMs like Salesforce (which 86% of pros use, per the report) to MAPs like Pardot. Next, I documented our automation solutions—built-in features, Zapier workflows, and custom scripts—pinpointing where and how often we use them. The goal? Identify gaps. For instance, I noticed our strategic partnership workflows lack cohesion, echoing Forest Donovan’s point about the alliance automation gap. This audit is my foundation to prune wisely, focusing on an integration strategy that scales with our business goals rather than chasing arbitrary tool cuts.

2. Bridging the Automation Gap with Strategic Foundations
To close the 36% gap where challenges are only partially resolved, I’m rebuilding our RevOps foundations. That means tackling data governance and cross-functional alignment head-on, even if it’s messy. I’ve scheduled stakeholder meetings to set clear rules, inspired by Mike Rizzo’s advice about high-functioning teams. Then, I’m auditing our automated processes—what’s working (like reducing manual tasks for 70% of pros) and what’s not (like the 28% not boosting deal velocity). For smaller teams, I’m leaning on third-party tools like Zapier, as Sara McNamara suggests, to avoid over-relying on scarce engineering resources.

3. Harnessing AI + Automation with Guardrails
AI is my competitive edge, and I’m scaling it thoughtfully. First, I addressed security by collaborating with IT and Legal to establish usage policies, asking vendors tough questions about data handling—Zapier’s security practices are on my radar. I started small, experimenting with free ChatGPT, much like Sara did, and now I’m exploring paid instances for tasks like data enrichment. Matt Volm’s advice to work backward from use cases resonates—I’m testing AI to enhance CRM records, potentially cutting costs on external data providers. With Zapier’s 270+ AI integrations, I’m building workflows to free up time for strategic work, not replace it.

The Road Ahead

This journey isn’t easy, but the data from the State of RevOps Automation Report has been a lifeline. At M. Allen, I’m committed to turning these strategies into action—auditing our stack, fortifying our foundations, and scaling AI with purpose. The pains of tool sprawl and the challenges of adoption won’t vanish overnight, but with a clear plan, I’m confident we can transform RevOps into a revenue-driving force. If you’re in the trenches like me, start small, align your team, and don’t shy away from AI’s potential. Together, we can navigate this maze and come out stronger.

Matt Slonaker, M. Allen