A three-tier framework for RevOps data quality

If you’ve ever tried to build a house on a shaky foundation, you know the results aren’t pretty. The same goes for building a revenue operations (RevOps) strategy on poor-quality data. Yet, many organizations are doing just that, hoping their tech stack will hold everything together. Spoiler alert: It won’t.

The tech boom’s shadow: data debt

The past decade has been an exhilarating ride for RevOps. The explosion of SaaS solutions and go-to-market (GTM) technologies has empowered teams like never before. But there’s a catch. With every new tool added to the stack, many companies are unknowingly piling up data debt—those nagging issues like outdated records, duplicates, and silos that make data unreliable and difficult to manage.

Data debt isn’t just an IT problem. It’s a business problem. In RevOps, where the stakes are high, the cost of poor data quality can be devastating. Imagine trying to make strategic decisions with data you can’t trust, or worse, missing out on opportunities because your data was incomplete or outdated. That’s the reality for many teams today.

When good isn’t good enough

So, how do we fix this? The first step is recognizing that the traditional, IT-centric definition of data quality—focused on accuracy and completeness—isn’t enough. In RevOps, data quality must be understood in broader, more strategic terms. It’s not just about having good data; it’s about having the right data to drive the right actions.

That’s where our new framework comes in. By redefining data quality across three tiers—technical, operational, and strategic—we can ensure that data isn’t just reliable, but also actionable and valuable.

Technical quality: the trust factor

The foundation of our model is technical quality, or the basic integrity of your data. Can you trust that your data is complete, accurate, and up-to-date? Without this foundation, nothing else matters. It’s the equivalent of making sure your house has a solid foundation before you start building.

Think of it this way: if the address on a lead record is incorrect, your geographically-based sales territories won’t function properly. That hot lead you’ve been waiting for could bounce around your sales team or get lost entirely. In RevOps, the stakes are too high to let poor data quality undermine your efforts.

Operational quality: ready for action

Technical quality is just the beginning. The next level is operational quality—ensuring that your data is ready to be acted upon. This means that related datasets are properly linked, the data is formatted correctly for the systems that need it, and it’s assigned to the right users at the right time.

Imagine you have technically perfect data, but it’s sitting in a silo, disconnected from the systems that need it. Or worse, it’s in the hands of someone who doesn’t know what to do with it. Similar to having a reliable car with gas in the tank, operational quality fuels your data, making it ready and able to drive your RevOps engine forward.

Strategic quality: the differentiator

Finally, we reach the top tier: strategic quality. This is where data quality transcends the basics and becomes a true competitive differentiator. At this level, having clean, well-linked data is not sufficient. You need data that provides insights to help you make smarter, faster decisions.

Strategic quality means understanding the relevance, value, and effectiveness of your data, knowing which accounts are most likely to convert, which campaigns are driving the best results, and where your team should focus their efforts. In short, having good strategic quality ensures your RevOps team is not just playing the game, but playing to win.

Why it matters now more than ever

In today’s fast-paced business environment, having a rock-solid RevOps strategy isn’t just a nice-to-have, it’s a must, and that strategy begins with data quality. As more companies embrace the RevOps framework, those that get data quality right will be the ones that thrive.

The current economic climate is pushing CFOs to scrutinize every dollar spent on technology. They’re demanding verifiable ROI, and that ROI is directly tied to the quality of your data. Projects like ABX and CDP are only as good as the data feeding into them. If your data is garbage, the results will be, too.

Ready to transform your data quality?

If you’re ready to take your RevOps strategy to the next level, it’s time to rethink how you approach data quality. With our comprehensive guide to RevOps data quality, you’ll learn how to implement a three-tier model that ensures your data is trustworthy, actionable, and strategically valuable.

Don’t let poor data quality hold you back. The future of your RevOps strategy depends on the foundation you build today. Ready to redefine your data quality? Download our ebook now and start building a RevOps strategy that’s built to last.

Recommended Resources