11 meetings booked from content they already published
Meetings booked
11 meetings
from the first set of leads
Replies
14
from 64 posts already published
Time to value
4 minutes
before seeing their first lead
Intro
Vamo
Vamo finds and recruits top engineers straight from GitHub — the cracked builders who never show up on LinkedIn. They sell to recruiters, staffing firms, and founders trying to fill engineering seats fast. Here's the twist: the engineers Vamo sources live off LinkedIn, but the people who buy Vamo live on it. Their founder's LinkedIn following was driving real demand from hiring teams, and nobody could keep up with it. With traxy, Vamo went back through 64 posts they'd already published and turned that engagement into 14 replies and 11 booked meetings without writing a single new post.
Results at a glance
Gabe Granados
Founding Partnerships Lead, Vamo
Before traxy
The problem
Vamo's founder was getting heavy engagement on LinkedIn from exactly the people they sell to: recruiters and hiring teams looking for engineers. Likes, comments, shares. But turning that into pipeline meant someone manually reading every post, scanning every commenter, and guessing who was actually worth a message. They didn't want to blast everyone - they only wanted to reach people the message was relevant to. So most of it never got touched. The result: roughly four months of leads sitting stalled. Real buyers engaging with their content, and no system to catch them.
The Gap
Most teams don't have a lead-gen problem, they have a signal problem. Vamo tells engineers to get off LinkedIn, but that's exactly where their buyers live and four months of that intent was engaging with their founder's posts and going uncaught.
The shift
Why traxy
Vamo was deep in go-to-market tool evaluation - demoing outbound platforms, automated SDR tools, the whole category. Most of it was cold. traxy was different because it was signal-based. Instead of buying strangers, it worked the network they already had. Every post they'd published was sitting on intent data, and traxy turned it into qualified leads. Two things closed it: speed and clarity. The platform surfaced the right people in minutes instead of hours, and the ICP match meant they could see exactly who was worth reaching out to.
Before & after
The transformation
From guessing to ICP match. traxy scans the engagers on each post and flags the ones that fit their ICP. No more reading every comment and guessing. From stalled to activated. They went back through 64 old posts, exported the matched leads to a CSV, and ran email sequences off it. Months of dormant engagement turned into a working pipeline. From one profile to many. They started with the founder's account, then expanded to their new CEO, thought leaders, and competitor audiences - mapping intent well beyond their own network. From hours to minutes. Surfacing leads from a post now takes half the time it used to.
By the numbers
Key metrics
Time to surface leads from a post
Manual, hours per post
Cut in half
Stalled LinkedIn leads
~4 months ignored
Reactivated across 64 posts
Replies from posts
0 tracked
14
Meetings booked
Day-one replies
Zoom out
The takeaway
Most teams treat LinkedIn engagement as a vanity metric. Vamo treated it as pipeline sitting in plain sight. The lesson isn't "post more" - they didn't write a single new post to get 11 meetings. They already had the demand. What they were missing was a way to read the signal and act on it before it went cold. If your founder is posting and the right people are engaging, you're already generating intent. The only question is whether you're catching it or letting four months of it slip.
traxy learns your ideal buyer and turns real-time engagement signals into qualified leads, delivered the moment intent appears.
