I encountered something last week that made me genuinely sad.
After spending months trying to get their HubSpot AI working, this company was ready to switch platforms entirely. But the real issue wasn't HubSpot—their data was a mess. Duplicate records everywhere. Inconsistent naming conventions. Properties that nobody had touched since 2019. In some cases, they didn't even know the properties existed or what they were for.
The AI features were doing exactly what they were supposed to do—just with terrible input data.
Here's what gets me: companies like this are sitting on $50,000-100,000 or more in annual efficiency gains from features they are already paying for. The Breeze Agents could handle may 60% of their routine customer inquiries. Predictive lead scoring could cut their qualification time in half. Smart send times could boost their email engagement by 30-40%.
All of that value, too often, is just... waiting. Dormant. Because nobody has done the unsexy work of fixing the foundation.
Unfortunately, this isn't a unique situation. I'd estimate 73% of HubSpot Professional and Enterprise users are in similar situations. They're paying for powerful AI capabilities and using maybe 10% of them effectively... if that.
The fix isn't complicated, but it does require honesty about where you actually are versus where you want to be. It requires admitting that the shiny new feature isn't going to save you if your data quality is poor.
Most of all, it requires someone willing to do the boring diagnostic work before jumping to solutions.
I know "clean your data" isn't as exciting as "implement AI." But in my experience, it's usually the difference between AI that transforms your business and AI that sits there looking expensive. And the god news is that HubSpot's new Data Hub has some great features to help you cleanup your data so you can take advantage of these other AI features.