feat(linkedin-thought-leadership): v1.0.0 — initial open-source import
Build LinkedIn thought leadership with algorithmic understanding, strategic consistency, and AI-assisted content creation. Updated for the January 2026 360Brew algorithm change. 16 agents, 25 commands, 6 skills, 9 hooks, 24 reference docs. Personal data sanitized: voice samples generalized to template, high-engagement posts cleared, region-specific references replaced with placeholders. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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# Poll Strategy Guide
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LinkedIn polls generate high impressions but their effectiveness is declining in 2026 due to overuse. Strategic polls still work — generic ones don't. This guide covers when polls are worth it, how to design them, and what to do with the results.
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## Poll Effectiveness (2026 Status)
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**Reach multiplier:** 1.64x average (down from 2.1x in 2024)
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**Trend:** Declining. LinkedIn is reducing poll distribution to combat low-quality engagement farming.
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**Verdict:** Use sparingly (1-2 per month maximum). Make every poll count.
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**Why polls still work when done right:**
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- They create a low-friction engagement action (one click)
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- Results generate curiosity and return visits
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- Follow-up posts based on poll data perform well
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- They provide genuine audience research data
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**Why most polls fail:**
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- Generic questions that don't teach anything
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- No follow-up content using the results
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- Overuse (more than 2 per month gets penalized)
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- Options that are obviously "right answer" bait
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## When to Use Polls (and When Not To)
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### Use a Poll When:
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- You genuinely want audience data to inform future content
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- The question reveals a surprising split in your audience
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- You're testing a hypothesis before writing about it
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- You want to start a conversation about a controversial topic
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- You plan to create follow-up content from the results
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### Don't Use a Poll When:
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- You just want easy engagement (engagement farming)
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- The answer is obvious (everyone will pick the same option)
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- You have no plan for the results
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- You've posted a poll in the last 2 weeks
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- The topic doesn't relate to your expertise areas
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**Test:** Before posting a poll, ask: "Would I write a follow-up post about these results regardless of the outcome?" If no, skip the poll.
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## Poll Design Principles
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### Question Types That Work
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**1. Industry Trend Poll**
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**Pattern:** "Where is [industry topic] heading?"
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**Works because:** People want to see if their prediction matches the crowd.
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```
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What will be the biggest AI adoption barrier in 2026?
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○ Data quality and governance
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○ Talent and skills gap
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○ Integration with legacy systems
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○ Organizational resistance to change
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```
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**2. Experience-Based Poll**
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**Pattern:** "What has been your experience with [specific thing]?"
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**Works because:** People engage with questions about their own reality.
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```
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How is your team using AI assistants today?
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○ Daily — integrated into workflow
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○ Weekly — specific tasks only
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○ Experimenting — no clear process yet
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○ Not using — waiting to see
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```
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**3. Contrarian Poll**
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**Pattern:** "Unpopular opinion check: [bold claim]"
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**Works because:** People love proving they agree or disagree with bold takes.
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```
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Hot take: Most "AI strategies" are just PowerPoint decks.
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○ Agree — execution is the gap
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○ Disagree — strategy matters first
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○ Partially — both are needed
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○ It depends on the organization
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```
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**4. Decision-Point Poll**
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**Pattern:** "If you had to choose between [A] and [B]..."
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**Works because:** Forces a choice, which triggers emotional engagement.
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```
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If you could only invest in ONE AI capability this year:
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○ Copilot for productivity
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○ Custom AI agents
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○ Data platform modernization
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○ AI literacy training for all staff
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```
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**5. Knowledge-Test Poll**
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**Pattern:** "What percentage of [thing] do you think [outcome]?"
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**Works because:** People want to test their knowledge against reality.
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```
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What % of enterprise AI projects make it to production?
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○ Less than 20%
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○ 20-40%
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○ 40-60%
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○ More than 60%
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```
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### Question Types to Avoid
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- **"Do you agree?"** — Too simple, no conversation value
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- **"What's your favorite X?"** — Fun but no professional insight
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- **"Yes/No/Maybe"** — Binary polls generate no discussion
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- **"Rate X on a scale"** — Not how polls work on LinkedIn
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- **"Which is better: [obvious winner] or [obvious loser]?"** — No real debate
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## Poll Configuration
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### Duration
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- **1 day:** Creates urgency, good for time-sensitive topics
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- **3 days:** Sweet spot for most polls — enough time for reach, short enough for relevance
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- **1 week:** Only for broad audience research questions
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- **2 weeks:** Too long — results feel stale, engagement drops off
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**Recommendation:** Default to 3 days. Use 1 day for breaking news or controversial takes.
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### Number of Options
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- **2 options:** Only for true binary choices (rare)
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- **3 options:** Good for clear categories
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- **4 options:** Best default — covers the spectrum without overwhelming
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**Tip:** Always include one option that's slightly unexpected or provocative. This drives comments.
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## Caption Strategy
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The caption is more important than the poll itself. A poll without context is engagement farming. A poll with a strong caption is audience research.
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### Caption Structure
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```
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[1-2 sentences of context: why you're asking this]
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[The insight or observation that led to the question]
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Vote below, and I'll share what I'm seeing in [your context] in the comments.
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#[topic] #[niche]
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```
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### Caption Template
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```
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I've been talking to [N] [audience members] about [topic] this month.
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The split in perspectives is surprising. [Brief observation about what you're seeing.]
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Curious if LinkedIn reflects the same pattern:
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[Poll renders here]
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I'll share what the data shows from my conversations once the poll closes.
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```
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### Caption Rules
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- **300-400 characters** (not too long — the poll takes visual space)
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- **Always provide context** for why you're asking
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- **Promise a follow-up** to incentivize voting
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- **Don't reveal your own answer** in the caption (kills curiosity)
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## Follow-Up Strategy
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The real value of a poll is what you do after it closes. Plan your follow-up before you post the poll.
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### Follow-Up Post Template (24 hours after poll closes)
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```
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[N] people voted on my poll about [topic].
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The results: [brief summary]
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What surprised me: [unexpected finding]
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Here's what this means:
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[3-5 insights based on the results + your expertise]
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The bigger lesson: [connect to your thought leadership angle]
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What do you think — did the results match your expectation?
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```
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### Follow-Up Actions
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| Result Pattern | Follow-Up Action |
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|---------------|-----------------|
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| Clear winner (70%+) | Post about why the consensus is right (or wrong) |
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| Even split (40/60) | Write about why this divide exists |
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| Surprising result | Share context that explains the unexpected outcome |
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| Low engagement | Don't follow up — the topic didn't resonate |
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### Follow-Up Timeline
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1. **During poll:** Reply to commenters, add your own perspective in comments
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2. **Poll closes:** Screenshot the results
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3. **Next day:** Post follow-up with analysis and insights
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4. **Week after:** Reference the poll data in related content ("Last week, 68% of you said...")
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## Poll Frequency Rules
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| Frequency | Effect |
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|-----------|--------|
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| 1 per month | Optimal — each poll feels intentional |
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| 2 per month | Acceptable — space them 2+ weeks apart |
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| 1 per week | Too much — reach penalty, audience fatigue |
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| Multiple per week | Algorithm suppression, looks like engagement farming |
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**Calendar rule:** Never post polls in consecutive weeks. Alternate with text, carousel, and story posts.
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## Quality Checklist
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Before posting a poll, verify:
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- [ ] The question relates to your expertise areas
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- [ ] No obvious "right answer" among the options
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- [ ] You have a follow-up post planned
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- [ ] Caption provides context (not just the question)
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- [ ] Duration is set (default: 3 days)
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- [ ] You haven't posted a poll in the last 2 weeks
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- [ ] At least one option is slightly provocative or unexpected
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- [ ] The results will be genuinely useful for your audience
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