LinkedIn Connection Message Templates: 11 Examples That Work

This is our library of LinkedIn connection message templates: what to write in the 300 characters you get with a connection request, grouped by the scenario that triggered the outreach. It deliberately covers copy only. Limits, warmup, automation caps, and how not to get your account restricted live in our LinkedIn outreach safety guide — read that first, because the best-written note in the world does not help a restricted account.

One safety fact matters enough to repeat: volume is the enemy. We cap LinkedIn sends deliberately low, so every request has to count. That is the entire philosophy behind these templates — few, specific, and impossible to mistake for a bot.

A connection note is not a cold email. You have roughly 300 characters, the recipient sees it next to your face and headline, and the accept decision takes about two seconds. That two-second read answers three questions: do I recognize the context, does this person seem real, and will accepting cost me anything?

So the structure is fixed: context → common ground → soft close. Name where you crossed paths (their post, a shared event, their company showing interest in your space), add one line of who you are only if your headline does not already say it, and close with a low-pressure ask to connect. No links, no calendars, no “quick call”.

The commonly reported acceptance rate for targeted requests is roughly 20–40% — and in our experience the spread is explained almost entirely by targeting, not copy. A perfect note to the wrong person loses to a mediocre note to someone who just engaged with your topic. That is why every scenario below starts from a signal, the same logic as our signal-based selling guide.

The internet is full of confident answers here, in both directions. The truth: the research is mixed. Several practitioner tests have found blank requests accepting at similar or even slightly higher rates than requests with notes — likely because a bad note (generic flattery, an instant pitch) performs worse than no note at all, and most notes are bad. Other tests find a specific, relevant note wins. Nobody has clean, large-scale public data, so treat any precise percentage you read with suspicion.

Our position: optimize for the conversation, not the accept. A blank request maximizes accepts but tells you nothing about intent — many people accept everything. A specific note filters: the people who accept it already know why you are here, which makes the first DM warmer and the reply rate on that DM higher. Since our caps keep volume low anyway, we would rather have 20 accepts that expect to hear from us than 30 that do not.

The strongest scenario we have: visitor identification shows an ICP-fit company on your site, you find the likely buyer, and you connect while the interest is fresh. The rule from our warm outbound playbook applies double on LinkedIn: cite category interest, never the browsing log — homework reads well, surveillance gets you reported.

Template 1 — the warm-visitor note. For the likely buyer at a company your site identified this week:

Hi [first name] — noticed some interest from [Company] in the [category] space recently, and you looked like the person closest to it. We live in that world at [our company]. Would be glad to connect.

Template 2 — the evaluation-stage note. When the signal suggests active evaluation (repeat visits, comparison content). Even lighter touch, because they are mid-decision and defensive:

Hi [first name] — I work on [category] at [our company]. If [Company] is looking at tools in this space, happy to be a straight-answers contact (including where we’re not the right fit). Either way, good to connect with people thinking about [topic].

Template 3 — the no-pretext direct note. When you have a real reason to reach out but no event or content hook. Honesty outperforms a manufactured pretext:

Hi [first name] — no clever pretext: I’m with [our company], we help [their role]s with [pain], and [Company] fits the profile of teams we do our best work for. Connecting in case it’s ever useful — no pitch coming either way.

Content engagement is the most human-looking trigger on the platform — connecting with someone over a post is what LinkedIn is nominally for. Two directions: they published something, or they engaged with someone else’s post you are monitoring.

Template 4 — they published a post. Reference the argument, not just the existence of the post:

Hi [first name] — your post on [topic] made a point I don’t see often: [their specific argument, paraphrased in a few words]. We see the same thing with [their role]s we work with. Would be glad to connect.

Template 5 — they commented on a relevant post. The intent-signal classic — someone engaging in your category conversation:

Hi [first name] — saw your comment on [author]’s post about [topic]. Your take matched what we keep hearing from [their role]s. I spend my days in that space at [our company] — always glad to connect with people thinking about it.

Template 6 — they liked or reshared. Weaker signal, so the note leans on the topic rather than their (nonexistent) argument:

Hi [first name] — noticed we were both in the audience for [author]’s post on [topic]. It’s the problem I work on at [our company], and I try to know the people who care about it. Open to connecting?

Template 7 — genuine mutual connection. Only when the mutual would actually vouch for you — LinkedIn shows shared connections, and a false-familiarity claim is checkable in one click:

Hi [first name] — we both know [mutual], who I worked with on [context]. Your work at [Company] on [area] keeps coming up in that circle. Would be glad to connect.

Template 8 — same community or group. Shared membership is weak but real common ground:

Hi [first name] — fellow member of [community]. Your intro mentioned [detail], which overlaps with what we build at [our company]. Figured we should be connected here too.

Template 9 — same event or webinar. Send within a day or two while the context is warm:

Hi [first name] — also at [event] this week. [Speaker]’s point about [topic] was the highlight for me; it’s close to what we work on at [our company]. Good to connect while it’s fresh.

Template 10 — they are speaking or presenting. Reaching out before or just after they speak flatters without flattery:

Hi [first name] — saw you’re speaking at [event] on [topic]. It’s exactly the problem space we work in at [our company], so I’ll be listening. Would be glad to connect ahead of it.

Template 11 — the job-change note. For a past user, champion, or relevant buyer who just moved. Two to four weeks in beats day one:

Hi [first name] — congrats on the move to [Company]. Teams usually rethink [category] in the first quarter of a new [role], and that’s our corner of the world at [our company]. Would be glad to connect either way.

InMail is LinkedIn’s paid message-a-stranger product — Sales Navigator includes 50 InMail credits a month, and InMail can reach people you are not connected to. The connection request is free, but it is a two-step motion: they must accept before a real conversation starts. (One exception: members with an Open Profile can be messaged without a connection or a credit.)

Our default is the connection request. It is free, it builds a network that compounds, and an accepted connection converts to an open-ended conversation instead of a one-shot message. InMail earns its cost in one niche: executives who accept almost nothing but do skim InMail. Even then, expectations should be modest — hedge any InMail benchmark a vendor quotes you.

The accept is the beginning, not the win. Send the first DM within a day or two while your face is recognizable, keep it to two or three sentences, and ask about their situation before describing yours. If the conversation goes anywhere, offer to move to email — more room, better for links, and it keeps your LinkedIn volume low.

For where LinkedIn fits next to email in a full sequence — and when each should lead — see our email vs LinkedIn comparison. And if writing eleven variants per prospect sounds like a job, that is the part an AI SDR automates: ours drafts the note from the actual signal and holds it for your approval.