We Sent 344 Connection Requests to LinkedIn Post Engagers: 73% Accepted, 17% Replied

The numbers For the first week of this campaign.

Two rates are worth reading twice. Acceptance was 73.26%, and reply was 16.86% of everyone we sent to, which is 23% of the people who accepted.

The setup

The whole point of this campaign was the audience. We did not buy a list or filter by title and company. Every single person we contacted had already liked or commented on a LinkedIn post about our topic. That is it. The audience was 100% post engagers.

We pulled those engagers with Periodix Actions running inside n8n or MCP. The workflow find target post URLs, calls Get Post Reactions and Get Post Comments to collect everyone who engaged, and enriches each person with their headline, company, and location. A pre-filter removed obvious non-fits, then Claude scored each remaining person against our ideal customer profile. For the strong fits, Claude drafted a connection note and a first message that referenced the exact post the person had engaged with. Then we sent, on a schedule, within safe daily limits.

If you want to reproduce the exact pipeline, it is written up as a playbook on mining LinkedIn post engagement for intent signals.

Why acceptance was this high

A 73% acceptance rate is not normal for cold outreach. Two things drove it.

Intent. Everyone we reached had just shown interest in the topic. They were primed to accept a connection from someone in the same conversation.

Relevance of the opener. The note was not "I see you are a VP of Sales." It referenced the specific post they engaged with, and where possible their own comment. That reads like a continuation of a discussion they were already in, not a cold pitch. Intent gets you noticed, relevance gets you accepted**.

Reading the reply rate 58 replies from 344 sent is 16.86%. Measured against the people who actually accepted the connection, it is 23%. Both framings are fair, and both are strong for a first touch. The messages were personalized to the post, which is the single biggest lever on reply rate. When the first line proves you actually paid attention, people answer.

We are sharing this on purpose. It is easy to publish only the metrics that flatter a campaign. The honest version is more useful, and it makes the acceptance and reply numbers more trustworthy, not less.

What we would change next

A few things we would test to push the funnel further:

Offer and call to action. The interested count, 15, is the group that raised a hand. A clearer next step for them, whether a resource, a demo, or a booking link, would likely convert more of them.

Follow-up cadence. These numbers are largely first touch. A second, well-timed message referencing the same post usually lifts replies.

Weighting commenters higher. Commenters gave us their own words. Leaning harder on that text in the opener is an easy win.

How to run this yourself

You do not need a big stack. You need a source of relevant posts, a way to pull the people who engaged, a scoring step, and a sending step within safe limits.

1. Collect a handful of posts in your niche that got real engagement with Periodix Actions.
2. Pull reactors and commenters with Periodix Actions.
3. Pre-filter, then score each person against your ICP with AI.
4. Draft a note that references the post, and send on a schedule.
5. Measure acceptance and reply, then iterate on the opener and the offer.

Ready to try it? Start a free trial and turn post engagement into a lead pipeline.