LinkedIn automation

We've built an internal LinkedIn automation system that combines comment driven visibility, outbound connection funnels, and reply routing. In the first month and a half the system delivered consistent awareness, a 30 percent connection acceptance rate, reply rates above 21 percent, and around 20 inbound project requests, while saving more than 10 hours of manual work per week.

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Context and challenge

As a B2B agency, LinkedIn is one of the most important channels for new relationships and deals, yet meaningful engagement is time heavy and easy to neglect. Manually searching for relevant posts, writing thoughtful comments, tracking who has replied, and following up with leads from long Sales Navigator lists quickly becomes unmanageable.

The goal was to create a repeatable system that keeps founders visible in the right conversations, runs outbound connection and messaging flows automatically, and ensures no promising reply is missed, all while freeing up time for actual client work.

Strategy and system

The strategy focused on three pillars:

1. Engagement automation: A workflow scrapes relevant posts in the niche, drafts context aware comments, and logs them into Google Sheets, turning daily commenting into a structured, low effort task that builds credibility and trust.

2. Outbound funnel: Using Sales Navigator and HeyReach, the system sends around 750 connection requests per month to founders, CEOs, COOs, CMOs, and similar roles. If a prospect accepts, a follow up message is sent a few hours later; if they do not, the system views their profile after two days and then triggers an InMail, covering several touchpoints without manual tracking.

3. Reply routing and posting: When a lead or contact replies, n8n workflows detect it, stop further automation for that person, assign the lead to the responsible founder, and notify them. Another workflow scrapes replies to IH’s comments, writes suggested answers, and surfaces them in a sheet so human replies can be published quickly.

All of this runs alongside regular LinkedIn posting, turning the founder profiles into always on acquisition assets rather than occasional activity bursts.

Stack and automation depth

The system uses Sales Navigator and HeyReach for outreach and safety limits, n8n as the orchestration layer, Apify for scraping posts, Google Sheets as a lightweight database, and OpenAI plus Claude APIs to generate comment drafts and suggested replies.

Most of the heavy lifting is automated: discovering posts, drafting comments, updating sheets, sending connection requests, follow ups, profile views, and InMails, as well as routing replies and stopping sequences when people respond. Human effort focuses on publishing comments, tailoring conversations with interested prospects, and running experiments on new message angles.

Results so far

In roughly six weeks, the automation has sent about 750 connection requests per month, with a connection acceptance rate around 30 percent. Every accepted profile, plus non acceptors, moves through the follow up logic, and reply rates are already around 21.2 percent, with roughly half of those replies being positive or neutral enough to continue the conversation.

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Alongside outbound, the comment and posting engine has driven strong visibility, with over 333,000 impressions from comment driven interactions in just one month and many new conversations started directly from those threads. The system has generated around 20 inbound requests for projects in IH Social Media’s niche, showing that consistent, high quality engagement brings the right people into the inbox without pushy pitching.

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Why this matters for B2B companies

For an average B2B founder or sales team, this kind of automation replaces hours of repetitive work every week: there is no need to manually hunt for relevant posts, think up comments and replies one by one, or maintain giant spreadsheets of who has accepted, been messaged, or needs a follow up. Instead, the system handles discovery, sequencing, and tracking, while people only step in where human judgment adds value.

The result is more consistent visibility, more conversations with the right prospects, and a smoother path from LinkedIn interaction to real pipeline, all without adding full time headcount. For B2B businesses that rely on relationships and trust, automating the busywork around LinkedIn makes the channel viable at scale instead of an afterthought.