Reach-splitten (in/out-of-network) er native i LinkedIns post-analytics siden juni 2026, men vises som PROSENT og finnes ikke i CSV-eksporten. Planen antok to manuelle antall; verifiseringen viste prosent, så modellen er ett felt — outOfNetworkPct — og in-network er komplementet. - parseOptionalPercent: egen parser, ikke parseOptionalCount. Komma er desimal (36,5 -> 36.5, aldri 365), og verdi >100 avvises: i én kolonne kan ikke et absolutt antall skilles fra en andel, så svaret er unknown, ikke en gjetning. Blank/ikke-numerisk/negativ -> unknown; ekte 0 beholdes. - Ett lagret halvpart, kryssjekket: In-network godtas og lagres som komplement; et transkribert par som ikke summerer til ~100 (±1 avrunding) forkastes som unknown i stedet for å bli halvveis trodd. - weightedOutOfNetworkPct: impressions-vektet roll-up (avgOutOfNetworkPct, uke + måned). Flatt snitt lar en 50-visnings-post slå en på 10 000; poster uten avlesning ekskluderes, og null vekt gir undefined — aldri 0, aldri NaN. - Reach inngår ALDRI i engagementRate (distribusjon != engasjement). Rapporten leser den som akvisisjon (ut) vs resonans (inn), og sier «ikke ført for denne perioden» framfor å estimere. En reach-innsikt går inn i N15s do-next-kanal. - Step 7c (A2-F11): rapporten tilbyr diff mot brukerens engagement-patterns.md med eksplisitt go — aldri stille skriving, aldri inn i den shippede malen. - Boundary-map (E#9): dwell eksplisitt umålbar, saves partner-gated, reach native men CSV-eksport uverifisert. - Reach-frie importer er byte-identiske med før, på skjerm og på disk. TDD: rødt bevist først (10 feilende), analytics 119 -> 144 tester, tsc ren. test-runner 232 -> 247 (Section 16w, gulv 213 -> 228). Alle suiter grønne. CHANGELOG: N15-oppføringen manglet og er backfilt sammen med N16. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01QxvWAjte7vPcF79QeSRvRJ
138 lines
5.2 KiB
Markdown
138 lines
5.2 KiB
Markdown
# LinkedIn Analytics Data
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This directory contains imported analytics data from LinkedIn CSV exports.
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## How to Import
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1. Go to [LinkedIn Creator Analytics](https://www.linkedin.com/analytics/creator/content/)
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2. Click **Export** to download a CSV of your content analytics
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3. Save the CSV file to `exports/` directory
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4. Run `/linkedin:import` in Claude Code
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### Optional: add per-post saves (manual)
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LinkedIn's CSV export does **not** include saves, and there is no self-serve API
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to pull them — but the per-post save **count** is visible in your native post
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analytics (since ~Sept 2025). To track it, add a `Saves` column to the CSV and
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type the count you read off LinkedIn. The importer picks it up automatically when
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the column is present:
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```
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"Content","Date","Impressions","Reactions","Comments","Shares","Clicks","Saves"
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"My post...",2026-02-10,5000,100,30,15,200,42
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```
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A missing column — or a blank `Saves` cell — leaves saves **unknown** (never
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counted as 0), and saves is **not** folded into the engagement rate (which stays
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comparable to older imports). Saves is the strongest organic engagement signal,
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so the reports surface it as its own line. **Dwell time stays unmeasurable** —
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it is internal to LinkedIn for organic posts, with no count to transcribe.
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### Optional: add the out-of-network reach share (manual)
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LinkedIn splits a post's impressions into **in-network** (people who already
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follow or are connected to you) and **out-of-network** (people who found it
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through recommendations, reshares or search). It sits in your post analytics
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under **Discovery**, beneath the impressions count — a global rollout that began
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in June 2026 — and it is shown as **percentages**, not as two counts. It is
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**not** in the CSV export, and whether it will ever be exported is unverified.
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To track it, add an `Out-of-network` column and type the percentage you read off
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that panel. The `%` sign is optional:
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```
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"Content","Date","Impressions","Reactions","Comments","Shares","Clicks","Out-of-network"
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"My post...",2026-03-10,5000,100,30,15,200,37%
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```
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Details worth knowing:
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- **Either half works.** An `In-network` column is accepted instead and stored as
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its complement (`In-network 63%` → out-of-network 37). Only the out-of-network
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share is kept, because the two halves describe one split — storing both would
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let a record contradict itself.
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- **Both halves are cross-checked.** If you transcribe both and they do not sum
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to ~100 (one point of rounding slack allowed), the reading is discarded as
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**unknown** rather than guessing which cell was misread.
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- **Percent, not a count.** A value above 100 is refused (`unknown`): in one
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column an absolute impression count and a share are indistinguishable, so the
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importer will not guess. A comma is read as a decimal mark (`36,5` → 36.5%).
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- **Unknown is never 0.** A missing column, a blank cell, or a non-numeric cell
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leaves the share unknown. A genuine `0` is kept — nothing left your network.
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- **Not part of the engagement rate.** Reach is a distribution signal, not
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engagement: a high out-of-network share means the post **acquired new
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audience**, while high in-network engagement means it **deepened the audience
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you already have**. Roll-ups are impressions-weighted, so a small post with a
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high share cannot outvote a large one.
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## Directory Structure
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```
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analytics/
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├── exports/ # Place LinkedIn CSV exports here
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├── posts/ # Auto-generated: imported post data (JSON)
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├── weekly-reports/ # Auto-generated: weekly performance reports (JSON)
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└── README.md # This file
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```
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## Data Format
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### Post Analytics (posts/*.json)
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Each file contains a batch of imported posts:
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```json
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{
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"batchId": "batch-...",
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"importedAt": "2026-01-29T...",
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"exportFilename": "content-analytics.csv",
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"dateRange": { "from": "2026-01-13", "to": "2026-01-28" },
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"postCount": 8,
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"posts": [
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{
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"id": "abc123",
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"title": "First 100 chars of post...",
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"publishedDate": "2026-01-28",
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"metrics": {
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"impressions": 4523,
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"reactions": 87,
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"comments": 23,
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"shares": 12,
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"clicks": 156,
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"engagementRate": 6.15
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}
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}
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]
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}
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```
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`metrics.saves` is **optional** — present only on posts where you supplied a
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`Saves` column value (see "Optional: add per-post saves" above). Posts without
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it omit the field entirely, so older imports round-trip unchanged.
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### Weekly Reports (weekly-reports/*.json)
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Generated via `/linkedin:report`. Contains:
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- Summary metrics (totals, averages)
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- Top and underperforming posts
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- Week-over-week trends
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- Performance alerts (spikes, drops)
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## CLI Usage
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The analytics CLI can also be invoked directly:
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```bash
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# Import a CSV export
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ANALYTICS_ROOT=./assets/analytics node --import tsx scripts/analytics/src/cli.ts import <filename>
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# Generate weekly report
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ANALYTICS_ROOT=./assets/analytics node --import tsx scripts/analytics/src/cli.ts report --week 2026-W05
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# Analyze trends
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ANALYTICS_ROOT=./assets/analytics node --import tsx scripts/analytics/src/cli.ts trends --period month --metric impressions
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```
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## Privacy
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All data in this directory (except this README) is gitignored. Your analytics data stays local.
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