Linkedin Post Report

LinkedIn Post Report

Take an Apify "LinkedIn profile posts" export — a CSV or XLSX scrape of one person's LinkedIn posts, anywhere from 50 to 5,000+ rows — and produce a decision-ready report on what's actually working, so the user can tell this person what to double down on and what to drop. Treat this as a serious analytics deliverable, not a quick summary.

If no file is attached, ask for it before doing anything else.

Handle these quirks of the export format

The obvious columns lie. Read them correctly:

• The type column says "post" for every row — ignore it. Derive each post's FORMAT from which media columns are populated: if document/* (e.g. document/title, document/totalPageCount) is filled → carousel/document; else if postVideo/* → video; else if article/* → shared article/link; else if postImages/0/url → image; otherwise → text-only.
• Engagement per post = engagement/likes + engagement/comments + engagement/shares. Reaction mix lives in engagement/reactions/N/type and /count (like, empathy, praise, funny…) — use it to read emotional register. Post text is in content; the author's handle and the post link are in linkedinUrl.
• There's no date column, but the timestamp is encoded in the activity ID (engagement/id, also the number after "activity-" in the URL): take it as a 64-bit integer and shift right 22 bits for Unix milliseconds (date = id >> 22, then ÷1000). Use this to build the timeline for cadence and best-day/time.

Quantitative pass

Compute the quantitative stats across ALL posts in code so the numbers are exact. Define an outlier as a post whose engagement is some multiple of its baseline, and state the multiple you used.

Qualitative pass

Do the qualitative read on the standouts — top and bottom performers, every outlier, and a representative sample of the middle. Don't infer what a post said from its numbers, and for visual posts don't judge from the caption alone: actually OPEN THE MEDIA and look at it.

• Download and view the image (postImages/N/url) and the video thumbnail (postVideo/thumbnailUrl).
• For carousels, pull the on-slide wording from document/transcribedDocumentUrl (or document/manifest/transcribedDocumentUrl) and view the cover/slide images (document/coverPages/.../imageUrls, document/manifest/perResolutions/N/imageManifestUrl).
• For every winning visual post, describe what's literally on it — the on-image or first-slide text and hook, the visual style (candid photo, selfie, screenshot, data chart, quote/text card, diagram, meme), the layout — and tie those visual choices to why it performed.
• Quote the hook and link the post every time.

What the report must deliver

With specifics and real examples:

1. Bottom line first — in 3-4 sentences, what's working and what should change.
2. What FORMAT wins (text / image / carousel / video / article) — average and median engagement and sample size per format, flag any format that looks strong but rests on only a few posts, and for the winning visual formats spell out what the strong images/slides actually look like.
3. What ANGLE / hook / topic wins — cluster posts into the angles this person actually uses (personal story, contrarian take, how-to, news reaction, list/framework, hot take, etc.), rank them by engagement, and name the opening-line and first-slide patterns that track with high engagement.
4. The biggest outliers — the posts that massively over- and under-performed their baseline, each with numbers, the hook, the link, what was on the image/slides, and the best read on WHY.
5. Stop / Continue / Start — what to stop (formats, angles, habits that reliably underperform), what to keep, and what to test next — concrete enough to act on this week.
6. Whatever else the data clearly supports and a sharp strategist would want: posting cadence and consistency, best day/time, ideal length, comment-to-reaction ratio (conversation vs passive likes), reaction-mix tells (controversy vs warmth), recurring themes, signs of fatigue or decline, and the single highest-leverage change.

Output: save two new files (don't modify the upload)

1. A written report the user can read top to bottom — clear hierarchy, bottom line up front, no filler, every claim tied to a number or a quoted/linked post.
2. An SOP for the next post, reverse-engineered from the highest outliers: the repeatable recipe spelled out step by step — the hook formula, the winning format and angle, and the visual template (what slide 1 / the image should contain and look like), with real outlier posts as worked examples.

Before calling it done

Ground every finding in the data. If the export lacks what a section needs (e.g. too few videos to judge, or media URLs that won't open), say so plainly instead of guessing. Re-check the headline numbers against the file and confirm every format, angle, and visual claim matches what's actually in the export.