linkedin-studio/references/analytics-tools-guide.md
Kjell Tore Guttormsen e38f71f418 fix(linkedin-studio): N24.5 — mekanisk gjeldssveip (plugin.json, CHANGELOG-dublett, de-niche, KTG, Step 9-nøkler) [skip-docs]
Fem grep-lokaliserte gjeldsposter fra STATE FUNN, pluss to anti-erosjons-lints
som gjør to av dem terminale i stedet for gjenoppdaget en gang til.

1. .claude-plugin/plugin.json description — v4.0.0-arvet release-notat med
   historiske tellinger («→ 19 agents», «→ 27 commands», «→ 29 commands»)
   erstattet av en beskrivelse av hva pluginen ER. Dette er teksten /plugin
   viser. Ingen tellinger i teksten: de drifter, og CHANGELOG.md eier historikken.

2. CHANGELOG hadde TO «## [0.6.0]»-overskrifter (2026-07-17 = ekte, 2026-02-07 i
   halen). Halens datert om til «## [0.6.0-legacy]». Sjette gangs gjenoppdagelse
   — derfor lint, se punkt 6.

3. De-niche: 7 «thought leader»-treff utenfor commands/ rettet — README (mot
   kommandoens egen frontmatter-ordlyd), skills/linkedin-networking (2:
   FUNN-listen navnga bare :9, men :185 var samme defekt), analytics-interpreter,
   analytics-tools-guide, collaborations-guide, linkedin-visual-style.
   BEVISST BEHOLDT: de 5 blocklist-linjene, de to negative eksemplene
   (opportunity-generation, det ironiske sitatet i video-strategy-guide), og
   network-builder:562 — et WebSearch-uttrykk som treffer hvordan ANDRE
   merker seg selv, allerede paret med «Creator».

4. Hardkodet «KTG» i generisk operatør-tiltale fjernet. FUNN navnga tre linjer i
   language-reviewer; klassen var 21 linjer over 4 agenter, newsletter.md,
   edition-state-templaten og specifics-bank sitt renderte NN-kilder.md-artefakt.
   BEVISST BEHOLDT som proveniens: CHANGELOG, tests/fixtures/* (de ER KTGs
   faktiske redaktørrunde, kalibreringsfasiten), adopter-notatene som ærlig
   flagger KTG-interne verktøy (contract-gate, specifics-bank), «KTG
   cover-directive» og «answers KTG's question» — attribusjon, ikke tiltale.

5. Step 9 persisterte tre nøkler templaten aldri deklarerte: randsoneGate (N9),
   hookForge + personaSweep.deling (N24). Nå deklarert i BÅDE artikkel-shapen og
   _doc. Additivt, schemaVersion forblir 1. _doc.hookForge bærer N22-invarianten
   videre: en variant har målt lengde / krok-type / kroppsspor og ALDRI en
   predikert engagement-score.

6. To nye ubetingede lints (Section 16aa), begge mutasjonstestet mot de FAKTISKE
   filene, ikke bare mot self-testen:
   - CHANGELOG-dublettvakt (+ in-memory non-vakuitets-self-test som skiller en
     ekte dublett fra en bevisst «-legacy»-overskrift)
   - Step 9-nøkkeldeklarasjon (shape + _doc)
   Mutasjon 1 (gjeninnfør dubletten) → rødt. Mutasjon 2 (fjern hookForge fra
   shapen) → rødt. Mutasjon 3 (fjern _doc.randsoneGate, fila fortsatt gyldig
   JSON) → rødt. Restaurert → grønt.

Ti suiter grønne: test-runner 300 → 303 (floor 281 → 284) · trends 300 ·
analytics 202 · hooks 191 · brain 134 · editions 72 · render 63 ·
specifics-bank 45 · tests 35 · contract-gate 33.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017vMLTF7J13jJmgqwwJyivt
2026-07-31 21:46:35 +02:00

8.2 KiB

Analytics Tools Guide: Finding YOUR Edge

The mechanics in the main skill represent baseline knowledge - what works on average. Your edge comes from discovering what works specifically for YOUR audience, YOUR content, and YOUR domain.


The Critical Distinction

  • Generic advice: "Post at 8am on Wednesdays" (average across all users)
  • YOUR pattern: "My audience engages most at 2pm on Tuesdays and 7am on Fridays" (specific to you)

Generic advice gets you to baseline. YOUR patterns get you to exceptional.


Free Tools to Discover YOUR Patterns

1. LinkedIn Native Analytics (Essential - Start Here)

Access: Your profile → Analytics & tools → Analytics

What to Track Weekly (15 minutes)

Post Performance:

  • Which posts got highest engagement (likes, comments, shares)?
  • Which topics performed best?
  • Which formats worked (story vs. framework vs. data)?
  • What length generated most engagement?
  • Which hooks stopped the scroll?

Timing Patterns:

  • When did YOUR best-performing posts go live?
  • What day of week shows highest engagement FOR YOU?
  • What time of day gets fastest first-hour response?

Audience Demographics:

  • Who is actually engaging? (Industry, seniority, location)
  • Is this your intended audience or a different cohort?
  • What titles/roles engage most?
  • Where are they geographically?

Follower Growth:

  • Which posts drove follower spikes?
  • Are you gaining followers from target audience?
  • What topics attract new followers vs. existing audience?

Action: Create a Simple Tracking Doc

After each post, note:

  • Topic, format, hook type, length
  • Post time and day
  • Engagement after 1 hour, 24 hours, 1 week
  • Comments quality (superficial vs. substantive)
  • Any patterns you notice

After 10 posts, you'll see YOUR patterns emerge. After 30 posts, you'll know exactly what works for YOUR audience.


Purpose: Catch emerging topics in your domain BEFORE they're mainstream.

  • Search for topics in your expertise area
  • Look for "Rising" queries (interest growing rapidly)
  • Filter by region if your audience is location-specific
  • Compare related terms to see what's gaining vs. declining

Exploding Topics (explodingtopics.com - free tier)

  • Shows topics with exponential growth in search volume
  • Filter by category relevant to your domain
  • Catch signals 3-6 months before they're saturated

How to Use

  • Weekly 15-minute scan of your core topics
  • When you spot rising trend, create content WHILE it's still fresh
  • You're now ahead of the documentation curve
  • This is how you stay above average

Example: If you notice "AI agents" search volume growing 400% month-over-month, create content NOW. By the time it's in mainstream LinkedIn advice (6 months later), you've already established authority.


3. Reddit + Niche Communities (Weekly Engagement)

Why This Matters

LinkedIn content is filtered and polished. Reddit discussions are raw and unfiltered. The real problems, frustrations, and questions live in niche subreddits BEFORE they become LinkedIn posts.

Strategy

  • Find 3-5 subreddits in your domain (e.g., r/artificial, r/MachineLearning, r/DevOps)
  • Lurk daily, post rarely
  • Watch for recurring questions, debates, frustrations
  • These become your content ideas

What You're Mining

  • Problems people actually have (not problems you think they have)
  • Language people actually use (not industry jargon)
  • Debates with strong opinions (contrarian angles)
  • Questions that get asked repeatedly (unmet need)

Content Creation from Reddit

  1. Spot recurring frustration in subreddit
  2. Develop your perspective on it (based on your expertise)
  3. Create LinkedIn post addressing it
  4. You're solving a real problem before it's "average advice"

Examples:

  • r/datascience discusses "model deployment frustration" weekly
  • You write: "Why 80% of ML models never reach production (and what to do about it)"
  • You're addressing real pain point, not generic "AI is transforming business"

4. Personal Knowledge System (Daily Practice)

Purpose: Connect non-obvious dots that create unique insights.

Free option: Obsidian (obsidian.md) Paid option: Notion ($10/month)

How It Generates Exceptional Content

Most content is obvious because it draws from single sources. Exceptional content connects ideas from disparate domains.

System

  1. Capture insights from your work daily (what you learned, observed, struggled with)
  2. Tag by theme/topic
  3. Review weekly to spot connections
  4. Non-obvious connections = unique perspectives

Example of Unique Connection

  • Note from AI project: "Stakeholders resist AI because it feels opaque"
  • Note from cooking: "People trust recipes with step-by-step photos"
  • Connection: "Why AI adoption needs 'recipe thinking' - making the black box transparent through step-by-step explanation"

This insight didn't exist in "AI best practices." It came from connecting two unrelated domains. That's exceptional content.

Weekly Practice

  • 10 minutes daily: Capture 2-3 observations from your work
  • 30 minutes weekly: Review notes, spot connections, generate post ideas
  • This systematic practice generates 10-20 unique content angles per month

5. Structured Experimentation (Ongoing)

The Difference Between Average and Exceptional

  • Average: Follow documented best practices
  • Exceptional: Test hypotheses to discover what works next

Experimentation Framework

Hypothesis: "My audience engages more with vulnerability-based hooks than data-based hooks"

Test: Create 2 posts on same topic, different hooks

  • Post A: "I failed at implementing AI. Here's what I learned."
  • Post B: "73% of AI projects fail. Here's why."

Measure: First-hour engagement, comment quality, saves

Learn: Document which worked and why

Iterate: Apply learning to next test

What to Test

  • Hook types (vulnerability vs. data vs. contrarian vs. question)
  • Content structure (story vs. framework vs. list)
  • Length (1,200-1,800 characters optimal range)
  • Posting times (your 8am vs. 2pm vs. 6pm)
  • Topic angles (tactical vs. strategic vs. philosophical)
  • CTA types (question vs. invitation vs. challenge)

Track in Simple Spreadsheet

Post Topic Hypothesis Variables Results Learning
AI adoption Vulnerability hooks work better Hook type A vs B A: 45 eng, B: 23 eng Vulnerability wins for this audience

After 10 experiments, you know YOUR audience better than any generic advice can tell you.


Integration: From Tools to Edge

Month 1-3: Establish Baseline

  • Post consistently (3x/week minimum)
  • Track everything in LinkedIn Analytics
  • Note YOUR patterns
  • Build knowledge capture habit

Month 4-6: Discover YOUR Edge

  • Identify YOUR best-performing topics/formats/times
  • Begin structured experimentation
  • Mine Reddit/communities for real problems
  • Connect dots in knowledge system

Month 7+: Operate at Edge

  • Post based on YOUR data, not generic advice
  • Catch emerging trends before they're mainstream
  • Create content from unique connections
  • Test new hypotheses continuously

The Compounding Effect

  • Month 1: You're learning mechanics (baseline)
  • Month 3: You understand YOUR patterns (above average)
  • Month 6: You're discovering insights from practice (exceptional)
  • Month 12: You're systematically generating unique perspectives (recognized expert)

Remember

These tools don't make you exceptional. They reveal the patterns and signals that help you develop YOUR unique insights. The actual edge comes from:

  • Your real work and experience
  • Your unique combination of expertise
  • Your authentic perspective
  • Your willingness to experiment

Use these tools to avoid reinventing known patterns while you discover unknown ones.


Tool Investment Guidance

Start Free (Months 1-3)

  • LinkedIn Analytics (essential)
  • Google Trends (weekly)
  • Reddit (weekly)
  • Obsidian (daily notes)

Consider Paid (After 3+ months consistent posting)

  • Shield or Taplio (~€50/month) for deeper analytics
  • Focus on ONE paid tool maximum
  • Most value comes from free tools + consistent usage, not expensive software