Launching today
DocMetrics Silence Checker
Know what buyers do with your proposal after you hit send
10 followers
Know what buyers do with your proposal after you hit send
10 followers
Sales teams often treat every silent buyer the same, leading to generic follow-ups and missed opportunities. DocMetrics helps you understand what buyers are actually doing after a proposal is sent by revealing engagement patterns, repeat views, stakeholder activity, and proposal behavior. This launch also includes the free Silence Checker, which helps sales reps interpret buyer silence and choose a more informed follow-up instead of relying on guesswork.
How does the Silence Checker actually figure out if a buyer is just busy versus genuinely uninterested, especially if they're opening the doc on mobile where engagement signals might be messier?
@ykselwil7 it does not distinguish "busy" from "uninterested" with certainty and it says so explicitly in the result. The confidence note at the bottom of every reading acknowledges that document signals alone cannot explain why silence is happening, only what pattern the observable behavior matches.
What it does is narrow the possibilities based on what can actually be observed. A buyer who has not touched the document at all during the quiet period is in a different situation from one who keeps returning to specific sections privately — those two patterns call for different follow-up approaches regardless of whether the underlying reason is busyness, indecision, or lost interest.
On mobile engagement being messier — you are right, and it is a real limitation. Page-level time data on mobile is less reliable than desktop because of how mobile browsers handle tab switching and background activity. The Silence Checker does not actually read your real document data — it asks you to describe what you observed, so the mobile noise problem lands on whatever tracking tool you used before coming here. DocMetrics itself handles this by being more conservative with confidence levels when session data looks inconsistent with typical reading patterns.
The honest ceiling of this tool is that it reads a pattern, not a mind. It is most useful for ruling out the least likely explanations and narrowing what the follow-up should address — not for giving a verdict on buyer intent that the data cannot actually support.