Methodology in brief. First-party LinkHub data: 657,786 real LinkedIn comments whose impressions and replies were measured. We segment by a simple criterion: does the comment contain a question mark "?" or not. We report, per comment, average replies, average impressions and average likes. Complemented by public industry studies, cited and dated. The analysis is correlational, not causal — see the honest reading in §2.
Key takeaways
- A comment that asks a question gets +23% more replies: 0.86 replies on average versus 0.70 for a comment without a "?". (LinkHub, n = 657,786)
- The same question-comment also generates +40% more impressions: 242 on average versus 173. Conversation drives redistribution.
- Likes barely move (0.94 vs 0.90): the question acts on conversation, not on passive applause.
- Only ~9% of comments contain a question — a simple and widely underused lever.
- Caveat: correlation ≠ causation. A relevant question works; a throwaway question tacked on at the end does not.
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1. Question vs no question: the numbers
Across 657,786 real comments, we split two populations: those containing a question mark "?" and those that do not. The contrast is sharp on conversation and reach, near-zero on likes.
| Comment type | Avg. replies | Avg. impressions | Avg. likes | Sample |
|---|---|---|---|---|
| With "?" (≈9%) | 0.86 | 242 | 0.94 | 57,417 |
| Without "?" | 0.70 | 173 | 0.90 | 600,369 |
| Gap | +23% | +40% | +4% | — |
Reading. Asking a question in your comment is associated with +23% more replies (0.86 vs 0.70) and +40% more impressions (242 vs 173). On likes, the gap is marginal (+4%): the question does not generate more passive approval — it generates conversation. That is exactly the lever the algorithm rewards most (see our comments vs likes study and the LinkedIn algorithm mechanism in 2026).
2. Why a question earns more replies (and more impressions)
The chain is mechanical:
- The question calls for an answer. Aimed at the post's author or other commenters, it creates a soft conversational obligation: people answer a question more readily than a statement. Industry studies confirm it: a question format acts as a natural "call-and-response" (Sprout Social, 2026).
- Replies trigger redistribution. When a discussion thread forms under a comment, LinkedIn pushes it beyond the initial audience → hence the +40% more impressions observed. Conversation is the fuel for reach — the same mechanic applies to replying to the comments on your own posts.
- Methodological honesty. Our data is correlational. Buffer, across 72,000 posts, is also transparent: conversational content is observed to perform better, without strictly proving causation (Buffer, Jan 2025). A good question-comment is above all relevant: it is not the magic "?", it is the question that genuinely opens the discussion. A question forced in artificially ("Right?") will not reproduce the effect.
3. Should you always end your comment with a question?
No — and that matters. The measured effect (+23% replies) comes from real questions that extend the post's idea or sincerely engage the author. A few guideposts:
- A question that adds an angle > a bland closed question. "How do you handle this when the client says no?" beats "Do you agree?". For phrasings that work, see our comment examples and the method to write a good comment.
- Pair it with useful length. A comment that is too short has no room for a good question; see our study on comment length and impressions.
- Relevance first. The "?" is only a proxy. What matters is opening a real conversational loop — the one the algorithm redistributes.
That is exactly what LinkHub helps with: spot the right posts and write a relevant comment — one that asks the right question when it helps — with personalized AI comments, always approved by you before publishing.
4. The most underused lever
The most striking finding: only ~9% of comments contain a question. The vast majority assert, congratulate or summarize — without ever re-opening the conversation. Yet the re-opening is what turns a comment into a discussion, and a discussion into reach.
On your next comments, the experiment is easy to reproduce: when the topic allows, end with a sincere question and watch the reply count. To go further, browse our other LinkedIn data studies.
FAQ
Does asking a question in a LinkedIn comment really get more replies? Yes: across 657,786 comments, those containing a "?" get 0.86 replies on average versus 0.70 without a question — that is +23%.
And on impressions? Question-comments generate +40% more impressions (242 vs 173). The conversation triggered pushes the algorithm to redistribute.
Is this causation? No, it is correlation. A relevant question opens a conversational loop; a throwaway question tacked on at the end does not reproduce the effect.
Should you end every comment with a question? No. The effect comes from real questions that extend the post. Favor relevance over reflex.
How do I find the right posts to ask these questions on? Through feeds targeted on your prospects and creators in your niche. See our AI profile recommendation.
Sources & methodology
- LinkHub dataset — 657,786 comments with measured impressions and replies, segmented by the presence of a "?" (with: 57,417; without: 600,369). Correlational analysis.
- Buffer — Replying boosts engagement by 30% (72,000 posts, Jan 2025) · Sprout Social — LinkedIn algorithm 2026
About the author
Founder of LinkHub
Yannis writes about social selling, LinkedIn comments and visibility. He builds LinkHub, the extension that helps you attract qualified clients through your comments.
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