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Your intent data provider tells you that someone at Acme Corp was researching a topic related to your product. They slap a score of 72 on it. And then... that's it. Your rep is left staring at a dashboard wondering "what am I supposed to do with this?"
There's a reason the intent category grew up inside Account Based Marketing. That data is genuinely valuable to marketing teams. They can take a spike in intent and run awareness campaigns, retargeting ads, nurture sequences, all the things that slowly try to convert that signal into an MQL. ABM platforms have always justified the price tag by promising that sales will benefit too, but that promise falls flat almost every time.
Sellers don't run ad campaigns. They need to know who to call and why. An intent score doesn't answer either question. So what happens? Reps ignore the scores entirely and go back to doing things the manual way. Building their own lists, doing their own research, grinding through the same motions they were doing before the company bought the platform.
The actual problem isn't a lack of data. It's a lack of direction. Your reps don't need to know that "something happened" at a company. They need to know which accounts to prioritize out of the thousands in their territory, and they need a reason that connects back to the specific problem your company solves.
Think about how your most tenured seller operates. The person who has been at your company for seven years, knows every use case, knows every win story. That person doesn't look at a lead score and start dialing. They glance at a company for 30 seconds and say "yeah, call them, here's why." They know which accounts matter because they can pattern-match what's happening at a company against the problems they've solved a hundred times before.
That's the gap GTM AI should actually fill. Not just observing that signals exist, but telling the rep which accounts deserve their time and why those accounts are a fit right now.
When GTM AI actually learns your tribal knowledge (your value props, your win stories, the specific problems you solve), it can do what your tenured rep does. It can scan thousands of companies and skip past the noise to find the ones showing symptoms of the exact problem you handle. And instead of handing back a ranked list of scores, it explains the connection in plain language.
One sentence: here's why you care about this account, and here's your in.
The way your most tenured rep would explain it to someone on their first week. Plain language that connects what's happening at the account to why your company is the answer, so your rep can actually do something with it immediately. That's what Syft does.
Once your rep knows who to target and why, the messaging becomes a byproduct. When you understand the problem a company is dealing with, you don't need to fake relevance by referencing their alma mater or congratulating them on a job change. Nobody cares that you know they went to Ohio State. They care that you understand their project and have a perspective on the risk they're staring at right now.
Syft builds perspective-driven messaging around the activity happening at the company, not surface-level personalization about the contact. But that messaging only works because the targeting was right in the first place.
Intent data isn't going away, and it shouldn't. But for too long it's been sold as a silver bullet for sales when it was really built to fuel marketing campaigns. The result is a platform that gives your reps visibility without direction, and visibility without direction is just noise.
The gap between "someone at this company did a thing" and "here's who you should call and why they need you right now" is where deals are won and lost. Most platforms stop at observation and leave your reps to figure out the rest. Your best seller wouldn't do that to a teammate. Neither does Syft.
Want to see what this looks like in practice? Head to syftai.com and watch a live simulation of how Syft finds Value Matches for a real company. If you want us to build one for yours, we will.
By Zach Wright, Cofounder at Syft AI
