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Dataset · Formatn = 1,000· Posts collected 2025-2026

LinkedIn post format performance: text-only vs image vs carousel

AI-classified format × engagement, ranked by avg engagements per post.

Headline finding

Problem-solution posts average 404 engagements per post and make up 40.6% of high-performing LinkedIn content, outpacing story posts (390) and numbered lists (323) across a 1,000-post sample.

Announcements are the weakest format on LinkedIn, averaging just 172 engagements per post, less than half the 404 average earned by problem-solution posts. Across 1,000 LinkedIn posts, problem-solution was the dominant format at 40.6% of the corpus and the top performer by average engagement. Story posts came close at 390 average engagements despite representing only 13.3% of posts, suggesting strong efficiency relative to their frequency.

The data

FormatPosts% of corpusAvg engagement
problem-solution40640.6404
story13313.3390
numbered list11811.8323
announcement202172

Key findings

  • 1

    Problem-solution posts average 404 engagements, the highest of any format in the 1,000-post sample.

  • 2

    Story posts average 390 engagements while representing only 13.3% of posts, making them a high-yield underused format.

  • 3

    Numbered list posts average 323 engagements and appear in 11.8% of the corpus.

  • 4

    Announcement posts average just 172 engagements, 57% lower than problem-solution posts.

  • 5

    Problem-solution is the most common format at 40.6% of posts, suggesting creators already favor it.

  • 6

    The gap between the top format (404 engagements) and the bottom format (172 engagements) is 135% in absolute terms.

  • 7

    Story posts appear 133 times in the dataset, roughly one-third as often as problem-solution posts (406 appearances).

What it means

The 135% engagement gap between problem-solution posts (404) and announcement posts (172) is the clearest signal in this dataset. Announcements are inherently creator-centric: they tell the audience what happened to the creator, not what the audience can do with the information. Problem-solution posts invert that structure. They open with a pain the reader already feels, then deliver a resolution. That structure earns attention because it is immediately relevant.

Story posts are the most interesting outlier. They appear in only 13.3% of the corpus but average 390 engagements, nearly matching the most common format. This suggests that creators who use narrative are getting strong returns without flooding the feed with it. Scarcity may help: a story post stands out when most of the feed is structured advice.

Numbered lists average 323 engagements and sit in the middle of the range. They are easy to skim and share, but they do not create the same emotional pull as a story or the immediate relevance of a problem-solution frame. Creators optimizing purely for engagement should consider shifting list content into a problem-solution structure, leading with the pain the list addresses before presenting the items.

Who this is for

  • You create LinkedIn content and want to prioritize formats by expected engagement return.
  • You are a content strategist benchmarking client post performance against industry-level format data.
  • You are a founder deciding how to announce a product launch and want to know whether announcement-style posts underperform alternatives.
  • You are a researcher or journalist writing about LinkedIn algorithm behavior and content format trends.
  • You run a creator tool or analytics platform and need third-party benchmark data to contextualize your own metrics.

Methodology

This dataset covers 1,000 LinkedIn posts analyzed by Creator (getcreator.io) and categorized into four content formats: problem-solution, story, numbered list, and announcement. Average engagement is calculated per post within each format category and reflects total interactions including likes, comments, and shares as recorded at time of collection. The corpus was not filtered by follower count or industry, so results reflect a broad cross-section of LinkedIn content rather than a specific niche. Researchers should treat these figures as directional benchmarks rather than controlled experimental outcomes, as post quality, audience size, and posting time were not held constant.

Limitations

This dataset covers 1,000 posts across four format categories and does not control for follower count, industry vertical, posting frequency, or time of publication. Engagement averages can be skewed by a small number of viral outliers within each format group. The dataset does not distinguish between text-only, image, video, or carousel post types, so format structure and media type are conflated. Causality cannot be inferred: problem-solution posts may earn more engagement because skilled creators favor that format, not because the format itself drives engagement. Results should be treated as observational benchmarks, not prescriptive rules.

Cite this dataset

Creator. (2026). “LinkedIn post format performance: text-only vs image vs carousel”. Retrieved from https://www.getcreator.io/data/linkedin-post-format-performance

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