Inbound marketing on LinkedIn starts with a post and ends with a conversation. In between sit the people who commented on or reacted to that post — a list warmer than anything a search can produce, and one most teams never work because it lives in a notification feed. ICP scoring turns that list into an order: who gets a hand-written reply today, who is worth a follow-up sequence, and who stays on the content-only list.
This guide covers what a LinkedIn inbound motion actually captures, what a 0–100 ICP score reads from a profile, the engagement signals worth tracking alongside it, and a six-step loop you can run every week without inventing a benchmark to justify it.
What Inbound on LinkedIn Actually Captures
Be precise about the source, because it shapes everything downstream. Inbound on LinkedIn means post engagement: the commenters and reactors on a post you published. It is not web traffic, not who looked at your profile, and not a form on a landing page. When you point an inbound campaign at a post, the tool watches that post and captures everyone who comments or reacts, as they arrive, with name, title and company attached.
That scope is narrower than the phrase "inbound marketing" usually implies, and the narrowness is the point. Every person on the list did something in public, under content you chose, on a topic you chose. A reaction says the topic landed. A comment says it landed hard enough to write about. Neither is a buying decision — but both are evidence a cold list never carries, and both arrive attached to a full LinkedIn profile you can grade.
Capture is broad; the automation is not. Everyone who engages with the post becomes a lead you can see and score, but the campaign only fires on a comment that contains one of your Action Words. That comment gets an automatic reply, and what happens next depends on the relationship. If the commenter is already a connection, the DM goes out. If they are not, the public reply is the connect-first template, which asks them to send you a connection request — and the DM sends once you accept it. That is a small mechanic with a useful side effect: the person who wants your template becomes a connection in order to get it, so the post ends up widening the list of people you are allowed to message.
The content that draws the right engagers is the usual mix: a specific problem your buyers recognise, a short account of how you solved it, a question that invites disagreement. For scoring, the format matters less than the audience a post attracts, so write for your ideal customer profile rather than for reach. A post that pulls two hundred reactions from students is worth less than one that pulls twenty from operations leads at the companies you sell to.
What an ICP Score Reads From a LinkedIn Profile
An ICP score is a fit score: a number from 0 to 100 describing how closely one person resembles the customers you already win. It is not an intent score. Intent — the fact that this person engaged, and how — is separate evidence the inbound campaign already holds, and keeping fit and intent on separate axes stops a strong comment from the wrong buyer being read as a hot lead.
A useful score reads the whole profile rather than three company fields. The inputs worth weighting:
- Title and seniority. Whether the headline matches the roles that buy from you, and whether the title holds budget or only influence. Two people at one perfect-fit company can sit forty points apart on this alone.
- Industry and company size. The company-level shape of your best customers — sector, headcount band, geography. Necessary, and nowhere near sufficient on its own.
- Work experience. Past roles at companies like your customers, progression into decision-making positions, and tenure. Someone who has held the buying role twice before knows what they are evaluating.
- Skills and endorsements. The listed skills and the peers who vouched for them — revenue operations, SaaS implementation, whatever your buyer personas actually do all day. Endorsements are a weak signal individually and a reasonable one in aggregate.
- Network. Who they are connected to and who they follow. A profile wired into the companies and people your ICP orbits is more likely to be one of them.
- Activity. What they post and comment about generally, not only under your content. Someone writing about the problem you solve is closer to a buyer than someone whose feed is unrelated.
Sendpilot's ICP Scoring reads all of these — the headline fields plus skills, endorsements, network, experience and activity — and returns a 0–100 score on every captured lead automatically, rescored as new data arrives. Scoring spends the same monthly credit balance as enrichment, the lead database and the lead extractor — 800 credits per connected LinkedIn account per month, which is 800 on Launch, 4,000 on Growth and 20,000 on Agency. Sales Navigator filters keep their job: they decide who is on a list. The score decides who on that list goes first, which is a different question and one a filter cannot answer.
Engagement Signals Worth Tracking Alongside the Score
Once fit is a number, the engagement itself becomes the second axis. These are the signals an inbound campaign can actually observe, starting with the one that starts the automation:
- A comment containing your Action Word. You asked people to type a word to get the guide, the template or the teardown, and they did. That is a request, and it is the only signal that starts the automation: the campaign replies to the comment, and the DM follows for connections.
- A substantive comment. A question, a description of their own version of the problem, a mention of a use case or an implementation detail. The richest evidence a profile field cannot supply.
- Repeat engagement across posts. Someone who reacts to three posts in a month is following your work. The pattern is worth more than any single reaction, and an inbound campaign per post is how you see it.
- A reaction. The quietest signal and the most common one. Reactors usually outnumber commenters, and they are worth seeing rather than ignoring — but a reaction starts nothing on its own. The high scorers among them are outbound work: a connection request first, a message after it is accepted.
Read the two axes together. High fit plus a substantive comment is the lead a rep answers by hand today — in the thread, and by DM if you are already connected. If that comment carried an Action Word and the person is outside your network, the campaign has already posted the connect-first reply, and the DM sends once you accept the request. High fit plus a reaction earns a connection request from an outreach campaign, and a message once it is accepted. Low fit plus a great comment gets the automatic reply if it carried the Action Word, and a courteous answer in the thread if it did not — but no rep time beyond that: generous in public, selective about who a person answers. Low fit plus a reaction goes on a content-only nurture list. None of those decisions needs a benchmark; they need a threshold you chose on purpose.
A Six-Step Loop: From Post to Scored Pipeline
- Publish for your ICP, on a schedule. At least weekly: a problem your buyers recognise, a how-we-solved-it, a question that splits the room. Queue the week in Post Scheduler so the cadence survives a busy Tuesday.
- Point an inbound campaign at the post. Pick the post, set the Action Words a comment has to contain, and write all three templates: the reply for connections, the connect-first reply for everyone else, and the DM. From then on every engager is captured as they arrive — no notification-watching, no export.
- Let the score rank the follow-up. Each captured lead is scored 0–100 against your ICP as it arrives, and the score decides what happens next: which leads a person answers by hand, and which transfer into an outreach campaign. Set a threshold — 80 and above is a sensible starting band for the top tier — and make it decide that hand-off rather than decorate a spreadsheet.
- Reply automatically, DM your connections. A comment carrying the Action Word gets a reply from a randomisable template, so twenty replies do not read identically. If that commenter is already a connection, the DM sends with their first name in it. If they are not, the reply asks them to connect first and the DM waits until they do. Keep the DM short and about their comment, not about you.
- Hand the top band to a person, or to an outreach campaign. Top scorers with a substantive comment get a follow-up a rep wrote. The rest transfer into an outreach campaign for a connection request, a message or a voice note, inside the per-account limits Sendpilot enforces.
- Sync, then compare posts. Push qualified leads to HubSpot or Slack, which are the native integrations, or to anything else — your own CRM, Zapier, n8n — through webhooks, the API and the MCP server on Growth and up. Then compare posts by the share of engagers that qualified — the number that tells you which topics reach your ICP, as opposed to which topics reach the most people.
For the mechanics of step four in detail — reply templates, DM timing, dedupe against running sequences and the guardrails that keep it human — the comment-to-DM automation guide covers the whole flow.
How to Measure It Without Inventing Numbers
Four figures, all of which the inbound campaign reports or you can count by hand:
- Engagers captured per post — commenters and reactors, by name.
- Qualified share — the percentage of engagers scoring above your threshold. The single best measure of whether a post reached your ICP rather than an audience.
- DM reply rate, split by score band — if the top band replies no better than the bottom, the model or the message is wrong, and you want to know which.
- Conversations that became meetings — and which post each one came from.
Resist setting targets before you have a month of data. Engagement-to-lead rates vary too much by audience and offer to borrow from someone else's deck; in our experience the useful comparison is your own posts against each other, and qualified share is the number that moves when the topic is right. Then reconcile monthly: pull the top-scoring engagers and the meetings you booked and check that the two overlap. When they stop overlapping, the ICP definition needs work, not the content.
Where Sendpilot Fits
This loop is what Sendpilot's inbound campaigns are built to run. Point a campaign at a post and set the Action Words; every engager is captured and scored 0–100 by ICP Scoring from the whole profile. A comment carrying an Action Word gets an automatic reply from your templates, and the DM goes to the people you are already connected to — everyone else gets the reply that asks them to connect first, with the DM following once you accept. Leads that clear the threshold transfer into an outreach campaign for a connection request, message or voice note, and every reply lands in Unibox next to your outbound threads, so nobody is answering from three inboxes.
Inbound campaigns and ICP Scoring are included on every plan: Launch for a solo operator ($79/month, or $66/month billed annually), Growth for a small team, Agency for client work. Plans are priced per LinkedIn account — never per user. See /pricing for the grid, or start a free trial and point the first campaign at the post you published this week.
Frequently Asked Questions
What does inbound marketing on LinkedIn capture?
The people who engage with a post you published. An inbound campaign is pointed at one post, watches its engagement and captures each engager as they arrive, with the profile attached; the automation itself fires on a comment carrying one of your Action Words. It does not identify website traffic, capture form submissions or track who viewed your profile — those are different products with different data.
Does an ICP score measure intent?
No. The score measures fit — how closely a person resembles your best customers, read from title, seniority, industry, company size, skills, endorsements, network, experience and activity. Intent is the engagement itself: the comment, the Action Word, the reaction, the pattern across posts. Keep them as two axes and decide the first touch from both, so a perfect-fit reactor and a low-fit commenter each get the response they earned.
Does the automatic DM reach people I am not connected to?
No. The DM only goes to people you are already connected to. A commenter outside your network gets the connect-first reply on the post instead — a public answer asking them to send you a connection request — and the DM sends once you accept it. That is why the two reply templates are worth writing separately: one delivers what was asked for, the other has to be good enough to earn the request.
What score threshold should trigger a personal reply?
Start with 80 and above for the hand-written tier and adjust after a month, not before. The right threshold is the one where the band above it books meetings at a visibly better rate than the band below; if the two bands perform the same, the model is not separating fit yet, and the fix is the ICP definition rather than a lower cut-off.
