RevOps Best Practices: Building an Efficient Revenue Engine for 2025

As we move further into 2025, the companies that are scaling efficiently flat out prove that the “growth at any cost” mindset is no longer viable. Instead, calculated investments in growth through a strategic RevOps function is the fastest ticket to earlier profitability.

Right now in a competitive business landscape, revenue operations (RevOps) is quite literally a strategic backbone that aligns sales, marketing, and customer success teams to drive sustainable growth.

After 15+ years of experience as a GTM strategist & close contact with revenue operations, I’ve seen firsthand how a good RevOps strategy can pick up businesses struggling with data silos into cohesive revenue-generating machines.

The Evolution of RevOps Strategy

Revenue operations have been somewhat of a buzzword these days.

But put simply, RevOps is a business strategy of how organizations unify multiple growth driving GTM teams like sales, marketing and customer success through data driven decisions throughout the entire customer lifecycle.

The term RevOps, is actually fairly new and saw its first usage in 2016 by LeanData’s CEO Evan Liang.

As Collin Specter, SVP of Revenue at Orum puts it: “The best time to build out a RevOps function is yesterday, the second best time is right now.”

And it’s a sentiment I stand by, with more and more leaders emphasizing a critical implementation of RevOps early in your growth trajectory for building a GTM engine that supports scale.

Why Traditional Approaches Fail

Before we start going over the best practices, you have to know why traditional operational models that we’ve been living by often fail to deliver the best results:

1. Departmental Silos: As you go up the scale – sales, marketing, and customer success departments operate in isolation, they develop their own datasets, processes, and sometimes even objectives that aren’t aligned with overall business goals and OKRs of the company.
2. Messy Data: Without a standard approach to data management, businesses always struggle with duplicate records, incomplete information, and inconsistent metrics across departments. Or quite simply, just plain bad data.
3. Bloated Tech Stacks: When companies grow, so do budgets. While that is a very good thing to have, sometimes organizations tend to adopt too many tools that don’t integrate well, giving way to inefficiencies and data gaps.
4. Inefficient Processes: Manual workflows and disconnected systems don’t hurt initially, but as you grow it ends up in a slower deal velocity and missed growth opportunities.

RevOps Best Practices for 2025

1. Establish a Common Data Quality Definition

According to recent surveys, 79% of organizations with poor data quality report that they don’t even have a standard definition of what data quality is. This is a fundamental issue that undermines the effectiveness of any RevOps strategy so your first focus should be fixing this.

Best Practice: Gather leadership from sales, marketing, and customer success to have them aligned on what really constitutes “good data” for your organization.

For a reference, this definition should consider:

• Which fields are critical for your business operations
• What level of completeness is acceptable
• How frequently the data should be updated
• What constitutes “stale” information

As one RevOps leader notes: “We need data to almost defend us against ourselves. RevOps needs data to support or not support a change.”

2. Build a Hub-and-Spoke RevOps Model

When I studied about the most effective RevOps structures, the experts love to advocate for structures that operate as a central hub with specialized resources dedicated to different departments.

Best Practice: Create a RevOps function that includes:

• A central core team that provides all the strategic direction and handles alignment
• Specialized experts who understand the unique needs of GTM sales, marketing, and customer success
• Clear lines of communication that actuate data sharing and collaborative problem-solving

Andy Mowat, VP of GTM Ops at Carta, emphasizes that “RevOps shouldn’t be siloed and doesn’t work if it only rolls up to one function.”

The ideal structure considers both strategic vision and tactical execution.

3. Implement Integrated Systems with Automated Data Flows

Organizations with acceptable data quality are actually 50% more likely to use automatically integrated tools and three times less likely to rely on spreadsheets and manual processes.

Best Practice: It’s best to invest in a designated platform that automatically integrates with your core systems.

This could be:

• An Integration Platform as a Service
• A customer data platform
• A go-to-market analytics platform
• A data warehouse with visualization layers

The key is having data flow very smoothly between systems and creating a single source of truth that all your departments can trust.

4. Develop Proactive Data Quality Processes

Did you know that companies with good data quality are close to three times more likely to have established processes for improving their customer and prospect data?

Data can break or make a GTM playbook.

Best Practice: Create standardized procedures for:

• Data cleaning and standardization
• Regular audits to identify and resolve issues
• Validation rules that are automated to prevent bad data entry
• Clear ownership for data quality across the organization

There’s no such thing as a perfect state of data cleanliness in a CRM 24/7…

Instead, build a system to

1. Detect data issues,
2. Investigate source of issue,
3. Fix the underlying cause.

5. Focus on Leadership Buy-In and Enforcement

The biggest differentiator between organizations with good versus poor data quality is the leadership engagement. In companies with poor data quality, 55% report that adoption of key systems is not at all enforced properly.

Best Practice: Secure executive sponsorship by:

• Educating leadership on the ROI of RevOps initiatives
• Creating clear metrics to show impacts from RevOps
• Having accountability for system adoption at all levels
• Involving executives in defining data quality standards

If you don’t have a RevOps function who you give time to focus on fixing data, you’ll never have accurate reports to bet on.

6. Use Custom Solutions for Your Unique Needs

Organizations with acceptable data quality are 60% more likely to use custom apps or code to manage their customer and prospect data.

Best Practice: While off-the-shelf solutions work for many needs, you should also consider developing custom applications or scripts for:

• Complex lead-to-account matching
• Territory management
• Specialized data cleansing
• Custom reporting needs

These tailored solutions help address the deeply contextual challenges of your business that generic tools can’t completely solve.

7. Prioritize Cross-Functional Alignment on Metrics

One of the most common challenges in RevOps is disagreement about which metrics matter.

What data you should be using as your guiding light is a bit tricky to find out. The data that marketing needs is different from sales data.

Best Practice: Establish a core set of key performance indicators that:

• Span the entire customer journey
• Are understood and accepted by all departments
• Connect directly to business outcomes
• Can be consistently measured and reported

8. Implement a Continuous Improvement Cycle

The most effective RevOps teams don’t see data quality as a one-time project but as an ongoing process.

Instead of focusing on 100% of 100% of data being perfect, think about which data points really matter to invest attention in.

Best Practice: Create a system for:

• Regular data quality assessments
• Proactive identification of potential issues
• Quick response to emerging problems
• Continuous refinement of the processes and standards

Measuring RevOps Success

How do you know if your RevOps strategy is working?

Well according to Natalie Furness, Founder & CEO of RevOps Automated, a high-performance RevOps team delivers impact in one or more of these way-:

1. Increases in volume of leads at each stage of the sales cycle
2. Improves conversion rates between stages
3. Accelerates the buyer through their journey
4. Reduces cost to the business

Mark Roberge, Co-Founder at Stage 2 Capital, suggests aiming for “at least 2x ROI on the general spend of RevOps.”

This means your RevOps function should be generating a measurable value that always exceeds its cost.

Common RevOps Pitfalls to Avoid

Even with best practices in place, there are several common pitfalls that can undermine your RevOps strategy, here’s the 3 biggest ones I’ve seen:

1. Hiring the Wrong Team

A successful RevOps employee at a Fortune 500 company might not be effective as the first RevOps hire at a startup.

They will be amazing, of course, but still running revenue operations on a leaner scale is a far different game to the way it’s played in the bigger leagues.

A start-up needs someone who is willing to roll up their sleeves and do it themselves, not a big company person who is used to hiring big teams.

2. Building a Static RevOps Function

RevOps is anything but a static function with routine tasks.

Revenue operation needs to be nimble and data-driven to keep up with the dynamic challenges that your business throws at you.

Teams that wait for problems to arise rather than proactively using data to identify issues will always be one step behind.

3. Waiting Too Long to Implement RevOps

RevOps should be immediate.

The longer you wait to build a RevOps function, the greater the chance that your revenue-generating teams become siloed.

Ideally, you should start thinking about RevOps “from day one,” even if you don’t have the resources to hire a dedicated team immediately.

The Future of RevOps is AI and Automation

Looking ahead, the AI wave is becoming increasingly important in RevOps strategy too!

The 2025 State of RevOps Survey shows that organizations these days are most interested in using AI to predict customer behavior in the lines of fit, intent, and churn.

But the effectiveness of AI tools is tied closely to how good data quality is.

Companies with poor data quality will see more significant barriers to AI adoption across all categories and that shows how important establishing strong data foundations is before investing heavily in AI solutions.

The ROI of RevOps Excellence

Implementing these RevOps best practices requires investment, but the returns are hard to not look at.

As Cuyler Owens, CRO at TrustRadius, shares:

“Since leaning into a RevOps strategy we have seen our revenue/head metrics more than double with smarter account assignments, segmentation, and performance management.”

The most successful companies already recognize that RevOps isn’t a service department—it’s a strategic function that drives their growth and efficiency.

Remember, the goal isn’t perfection.

This focus on continuous improvement rather than perfection is the hallmark of a truly effective RevOps strategy in 2025 and is the “The Best RevOps Practice” that covers it all.

If you’re looking to enhance your RevOps function, stay tuned for our upcoming pieces on RevOps tools and software, as well as RevOps fundamentals, where we’ll go deeper into building and optimizing your revenue operations framework.