Real Purchase Intent: The Need for Transparency in Intent Data and RevTech
When making a big purchase in everyday life, like buying a car, you get to “look under the hood” and assess the details. But in the world of marketing technology (MarTech), particularly in the B2B intent data space, that transparency is often missing. This lack of visibility is a real problem for buyers.
I was jolted recently by a post from a vendor’s sales team on LinkedIn that said, “You don’t have to guess with us anymore!” This struck me because it’s rare to see a company openly admit that their previous product left customers guessing. Does this kind of honesty raise red flags for other buyers, or are people so used to vague, over-complicated solutions that they fail to see the underlying issues?
The problem with much of the intent data on the market today is that it’s collected from disparate, sometimes questionable sources and then processed by opaque algorithms. This makes it nearly impossible for you, the buyer, to evaluate the quality of the data. You can’t clearly trace what triggered a particular signal, making it difficult to know whether you’re truly looking at real purchase intent, or even relevant buyer behavior. At the end of the day, this creates a major risk for you when deciding how to spend your resources.
All Intent Data Is Not Created Equal
I’ll admit upfront that I have a bias because of the model we use at MarketingVogue, but let’s be honest here: not all intent data is the same. And you should absolutely ask your data provider to show you exactly how their data is collected. Who took what actions? What content were they engaging with? And how does that relate to the real buying journey? If a provider can’t answer those questions clearly, then how can you trust that the data they’re offering is actionable?
I’ve seen firsthand that the best data comes from companies with a business model designed to create high-quality, actionable insights. At MarketingVogue, we can show exactly who took specific actions, what content they consumed, and what other interests they have. This level of transparency is possible because we’re the publisher of the content they engage with and we have opt-in permission from users.
In short, good data comes from companies that are aligned with the right audiences, offering valuable content, and capturing permission for deeper insights. This model is powerful but difficult to replicate.
Data Is One Thing, But Systems Are Another
Let’s shift gears for a moment and talk about the systems that process this data. As companies add more tech to their RevTech stack, it’s easy to get sucked into flashy new platforms that promise to “do it all.” But as I’ve learned in my own experience, just adding another system isn’t necessarily the solution.
One thing I’ve come to appreciate is that the real value comes from making smarter use of the tools you already have. We have a solid understanding of the activities needed across our go-to-market (GTM) teams, and we’ve invested in automation technologies to help us scale efficiently. But now, rather than simply adding new tech, we’re focusing on improving the quality of what we already do.
Our strategy is simple: we aim to become more relevant in every interaction by gaining a better understanding of our customers’ needs and executing with greater precision. Our data sources are critical to this, but our systems needs are relatively straightforward. We don’t need more tools; we need to execute more effectively with the tools we already use.
Going Beyond Accounts and MQLs
The industry standard for lead qualification—like using Marketing Qualified Leads (MQLs) or focusing solely on accounts—can be limiting. I’ve come to realize that true success lies in understanding and engaging with buying groups, not just individual leads or accounts. This shift in thinking has had a huge impact on how we approach our GTM strategy.
By focusing on buying groups and leveraging the right insights, we can prioritize our outreach more effectively and tailor our messaging. This means getting marketing and sales teams aligned around opportunities that matter most, not just pushing more top-of-funnel activity.
We’re also becoming smarter about which tools and capabilities are best suited to different parts of the process. For example, while AI and automation can create big efficiencies for repetitive tasks, the real value often comes from more personalized, human-driven interactions. For sales, this means having the precise data needed to prioritize outreach effectively.
Conclusion: Focus on What Really Matters
Over the past couple of years, our team has grown much more focused and pragmatic in our approach to RevTech. We’ve become more discerning about the tools we adopt, looking for solutions that will genuinely help us execute better and drive more meaningful business outcomes. It’s no longer about collecting more data or adding more tech for the sake of it; it’s about using the right data, from the right sources, to take the right actions.
If you’re a buyer, be skeptical of flashy promises and complex systems that claim to solve everything. Demand transparency and a clear connection between the data and the buyer’s journey. This is the only way to make sure your efforts are truly aligned with real purchase intent—and ultimately, with success.
