The feedback loop that makes scoring feel personal
How a thumbs up or down quietly retrains the model to think like your best SDR.
A good lead for you isn't a good lead for everyone. Your ideal buyer, your deal size, the phrasing that signals real intent in your market — all of it is specific to you. A one-size-fits-all score can only get you so far.
Every reaction is a training signal
When you thumbs up or down a lead, Eavesdrop doesn't just hide it. It extracts the pattern — this category, from this source, phrased this way — and nudges a weight for your account. Those weights get injected into every future scoring call.
Compounding, quietly
None of this asks you to configure anything. You just work your feed and react. Over a week or two, the scoring tilts toward the leads you actually want and away from the ones you don't — no settings, no retraining runs, no prompt engineering.
Week four is sharper than week one. A competitor starting today is always behind.
Why it's a moat
Anyone can wrap a search API in a generic prompt. What they can't copy is the model of your taste — accumulated one reaction at a time. The longer you use it, the more it's yours, and the harder it is for anyone to catch up.