Ever since I started migrating data between platforms like Salesforce and HubSpot, I've noticed a pattern. CRM and RevOps vendors, especially the new AI-powered ones, have gotten *really* good at using impressive-sounding language that doesn't actually tell you what their product does. It's like a fog machine for features.
I used to get dazzled by claims of "seamless intelligence" or "proprietary algorithms that unlock revenue potential." Now, my first instinct is to ask for the concrete steps. If a tool says it "automatically enriches lead data," I want to know: which specific fields? What are the data sources? What's the match rate in a real test with messy data? If they say "AI predicts churn," what are the model inputs? Can I see the actual factors and their weights, or is it just a black box score?
Here's what I've started doing, and maybe you all have your own tricks. I mentally translate their marketing copy into operational questions. "Leverages cutting-edge machine learning" becomes "What actions can my team take directly from this insight, and what's the workflow to do it?" "End-to-end platform" becomes "Show me the API documentation for the specific integration point I need."
It's saved me from a few costly mistakes. Has anyone else developed a good radar for this? I'm particularly curious about spotting the hand-wavy claims around data quality and automation, since that's where the real work happens.