How to Extract LinkedIn Poll Voters

About 22.5% of a B2B contact list decays every year as people change jobs and abandon inboxes, per research compiled by HubSpot. A LinkedIn poll voter list is the opposite kind of data. Every name on it acted this week, and the vote itself signals intent.

Quick answer: to extract LinkedIn poll voters, open a poll you authored, click the vote count, and log each voter with the option they chose. Only the poll's author can see individual votes, so your own poll is the richest source. To do it hands-free, a Simular AI computer agent reads the voter list on LinkedIn's real screen and records names, titles, and choices into your sheet.

A poll such as "What is your biggest RevOps bottleneck?" sorts voters into segments by intent. A VP of Sales sees who picked "pipeline." A marketing director sees who picked "attribution." A tier-1 VC running "How are you funding your next hire?" learns which founders are raising. This guide covers three ways to collect that list: by hand first, then a Simular AI computer agent, then traditional scraping tools.

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Manual, Simular, and scrapers at a glance

Signal math: When 88 of 240 voters pick one option, roughly 37% of the poll self-sorts into a single intent segment, yet logging every voter by hand still runs about 4 hours at a minute each. Derived estimate.

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Which method should you use?

• Fewer than about 50 voters, one poll: collect by hand. The copying takes minutes.
• Recurring polls or hundreds of voters, segmented and refreshed: a Simular AI computer agent. It keeps each vote attached to the voter and runs while you are offline.
• One bulk pull and you accept the risk: an extension, briefly, then uninstall it.

Say a marketing director posts "Which channel drives your pipeline?" and gets 240 votes. The 88 who picked "events" are a segment. Each one just stated a priority, unprompted. Unlike a scraped profile or an event attendee list, a poll captures a choice, not just a name.

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Method 1: Collect poll voters by hand

Read the voter list on your own poll and copy each row into a sheet. Zero ban risk, capped at your typing speed.

1. Open a poll you posted, then click the vote count under the poll.
2. Open each option to see who chose it. Copy the name, headline, and profile URL into a spreadsheet row.
3. Add a column for the option they picked, so the intent stays attached to the person.
4. Import the file into Google Sheets and clean the columns.

Pros: fully within LinkedIn's terms, free, and the vote choice is right there. Cons: you can only read voters on polls you authored, and copying 200 voters by hand runs about 3 hours at roughly 1 minute each.

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Method 2: Hand it to a Simular AI computer agent

Instead of installing anything, you show a Simular agent one pass through a poll, and it repeats it at a human rhythm.

1. Name the poll and the target, for example "keep only voters who are IT directors or founders."
2. Demonstrate one capture: open the poll, click the vote count, open each option, and read a voter into your sheet. The agent learns the fields and the layout.
3. Set a daily pace and the titles to keep. The agent opens each voter, reads the headline, and records the option they chose.
4. Let it run on its cloud virtual machine while you are offline, writing one clean row per voter into your sheet or CRM.

The agent works LinkedIn's own screens the way you do, so there is no browser extension to fingerprint and no third-party API to throttle. It reads the same voter list a person sees, opens each profile at a human pace, and keeps the vote choice tied to the record. You set the limits and approve the steps, and it pauses on anything sensitive so a person stays in the loop. The Simular Pro page covers longer unattended runs.

Pros: full voter lists with intent kept, no extension footprint, and easy to refresh. Cons: a paid plan, roughly 15 minutes of training, and a deliberate pace instead of instant results.

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Method 3: Extensions and scrapers

Tools such as Apollo, PhantomBuster, Evaboot, Waalaxy, Dux-Soup, and Wiza pull data from your logged-in session. Fast, but they carry the detection risk LinkedIn hunts for, and most were built for search results, not poll votes.

1. Add the Chrome plugin, or paste your LinkedIn session cookie into the cloud tool.
2. Point it at a profile list or a search, since few tools read a poll's voter panel directly.
3. Layer on enrichment to attach emails, then save the voter list.

Pros: quick bulk pulls with email enrichment bundled in. Cons: LinkedIn scans for prohibited software and extensions and can flag them almost instantly, and reports describe accounts restricted within about 48 hours. They also tend to drop the vote choice, which is the whole reason to mine a poll.

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Why only the poll author sees the votes

LinkedIn keeps individual votes private on purpose. Only the poll's author can see who voted and which option each person chose. Everyone else sees percentage totals, never names. That single rule is why running your own poll beats hunting through other people's. It also explains why this data is so clean. The voter self-selected. There is no email guess, no title inference, and no stale record, unlike a scraped profile list that erodes as people move roles.

Advanced tactics practitioners actually use:

• Segment by option. Treat each poll answer as its own list. Voters who chose the pain you solve are your warmest tier.
• Cross-reference against your ICP. Keep only voters whose headline matches your target, for example VP of Sales or seed-stage founder, and drop the rest.
• Run recurring polls. One poll a week compounds into a standing intent database, and you refresh it before the 22.5% yearly decay bites.
• Stay human-paced. Opening voter profiles counts as activity, so keep it near the observed safe range of 80 to 200 profile views a day, per community benchmarks.

The common mistakes are consistent. People try to scrape someone else's poll, where votes are private, so there is nothing to pull but percentages. They treat a vote as a yes, when it is only interest, so open with the poll topic and not a demo. They let the list rot instead of refreshing it each quarter. And they reach for an extension the week before a push. Practitioners on Indie Hackers describe the same pattern on repeat: install a scraper, pull a hundred leads, and watch the account get restricted within about 48 hours. The line worth pinning up is simple. A scraped name is a guess about someone. A poll vote is a statement from them.

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Key takeaways

• Only the poll's author sees individual votes, so your own poll is the one place to extract voters and their choices.
• Under about 50 voters, copy by hand. For recurring polls kept fresh, a Simular agent is the safest automated path.
• Extensions are fastest and riskiest, they can trigger restrictions within about 48 hours, and they usually lose the vote choice.
• Segment voters by the option they picked, and refresh each quarter to beat the 22.5% yearly data decay.

The winning pattern: post a sharp poll, read the voters only you can see, and let a Simular Pro agent collect and segment them on its own cloud VM while you are offline. Feed the result into a targeted LinkedIn prospect list, then reach out. The people who build the agent are profiled on the Simular page.