1. Traditional, manual ways to export LinkedIn data

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1.1 Export your personal LinkedIn data archive

1. Sign in to LinkedIn on desktop.
2. Click the Me icon in the top-right, then choose Settings & Privacy.
3. In the left sidebar, open Data privacy.
4. Under How LinkedIn uses your data, click Get a copy of your data.
5. Choose either specific data types (for example, Connections, Messages, Profile) or Download larger data archive for everything.
6. Click Request archive and confirm your password if prompted.
7. LinkedIn will email you a link to download your archive (minutes for small exports, up to 24 hours for full archives). The link is active for 72 hours.

Official help: https://www.linkedin.com/help/linkedin/answer/a1339364

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Pros:

• Simple and native.
• Good for periodic full backups of your activity.

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Cons:

• Not real-time; manual every time.
• ZIP file must be downloaded and unpacked before use.

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1.2 Export your LinkedIn connections

1. Repeat steps above to reach Get a copy of your data.
2. Select only Connections.
3. Request archive.
4. When the email arrives, download the CSV; it contains first and last name, profile URL, company, position and connection date (emails only when allowed by their privacy settings).

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Pros:

• Quick way to move your network into a CRM or Google Sheets.

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Cons:

• Missing emails for many contacts due to privacy controls.
• Requires manual clean-up before importing into Sheets.

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1.3 Export LinkedIn Page analytics (for company pages)

If you admin a LinkedIn Page:

1. Go to your Page on desktop.
2. Open the Analytics tab and choose Visitors, Followers, Leads or Content.
3. Use the date filters you care about.
4. Click Export to download a CSV of the selected analytics.

Page data portability overview: https://www.linkedin.com/help/linkedin/answer/a6202377

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Pros:

• Essential for content and campaign performance tracking.

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Cons:

• Separate exports per tab and date range.
• Still a manual, recurring chore.

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1.4 Copy data directly from UI

For very targeted research (a short list of profiles or posts), you can:

• Open each profile or search result.
• Manually copy names, roles, company, profile URLs and paste into Google Sheets.

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Pros:

• Highly controlled and compliant for small volumes.

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Cons:

• Painfully slow and error-prone at scale.

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2. No-code automation methods with Google Sheets

When you are tired of repeating the same clicks, you can let lighter automation do the lifting without writing code.

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2.1 Use Google Sheets to clean and normalize exports

Once you download LinkedIn CSV files, import them into Google Sheets:

1. Open Google Sheets and create a new spreadsheet.
2. Go to File > Import > Upload and select your LinkedIn CSV.
3. Choose Insert new sheet so you keep raw data separate.
4. Use built-in tools like Cleanup suggestions, Trim whitespace and Remove duplicates (under Data menu) to tidy the dataset.

Docs on importing data: https://support.google.com/docs/answer/3093335

You can then:

• Create filter views for segments (for example, job title, industry).
• Use QUERY, FILTER or PIVOT TABLE to build dashboards.

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Pros:

• No code required.
• Easy to share with sales, marketing or founders.

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Cons:

• Still requires you to remember to import new CSVs regularly.

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2.2 Connect Sheets to email for semi-automated importing

Use tools like Zapier, Make or n8n:

1. Trigger: New email in your inbox from LinkedIn with subject containing "your LinkedIn data archive is ready".
2. Action: Download the attachment to Google Drive.
3. Action: Append or overwrite rows in a Google Sheets tab with parsed CSV content.

Docs: Google Sheets API via Zapier overview https://zapier.com/apps/google-sheets/integrations

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Pros:

• Removes the manual download and import step.
• Great for recurring exports (for example, weekly connections file).

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Cons:

• Parsing CSVs in no-code tools can be fiddly.
• Still relies on LinkedIn emails and basic rules; complex workflows are hard.

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2.3 Use no-code scrapers for very small jobs

Some compliant browser extensions or cloud scrapers can pull public data into a CSV that then syncs with Google Sheets. These can help collect a small search result page of leads.

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Pros:

• Fast to get started.

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Cons:

• Easy to break when LinkedIn UI changes.
• You must verify compliance with LinkedIn terms yourself.

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3. Scalable, automated exports with an AI agent

This is where an AI computer agent, such as one running on Simular Pro, changes the game. Instead of wiring together dozens of brittle rules, you let a desktop-grade agent behave like a power user.

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3.1 Agent-driven LinkedIn archive to Google Sheets workflow

High-level flow:

1. You describe the goal in natural language: for example, "every Friday, export my LinkedIn connections and refresh the Leads tab in this Google Sheet".
2. The Simular AI agent signs into LinkedIn on a dedicated desktop environment.
3. It navigates to Me > Settings & Privacy > Data privacy > Get a copy of your data.
4. It selects Connections, requests the archive and waits for the confirmation email.
5. When the email appears, it opens the link, downloads the CSV, and saves it to your Google Drive.
6. The agent opens Google Sheets, imports or overwrites the connections sheet, applies your standard clean-up and formulas, and logs the run.

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Pros:

• Fully hands-off once configured; production-grade reliability even across thousands of steps.
• Transparent execution: every click and field is visible and auditable.
• Works across desktop, browser, email and Sheets without new APIs.

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Cons:

• Requires initial onboarding and testing of the agent.
• Best suited when export frequency is weekly or higher.

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3.2 AI agent for LinkedIn Page analytics and campaign reviews

Another pattern:

1. The agent logs in as your Page admin.
2. It cycles through Analytics tabs (Visitors, Followers, Content).
3. For each tab, it applies standard filters (last 30 days, specific regions or seniority).
4. It downloads CSVs, imports them into a central Google Sheets workbook and updates pivot dashboards for marketing and leadership.
5. Optionally, it writes a brief narrative summary of key changes week-over-week directly into a Docs file or Slack channel.

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Pros:

• Turns LinkedIn Page data into a living marketing control panel.
• Saves your team from repetitive export work and manual chart updates.

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Cons:

• Needs clear guardrails on which Pages and time ranges to use.

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3.3 Multi-dataset exports for operations and HR

For recruiting or operations leaders, the agent can:

• Export Job Applications, Job Seeker Preferences and Messages.
• Map each record into candidate pipelines in Google Sheets.
• Tag sources, roles and stages so your team only reviews prioritized candidates.

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Pros:

• Centralizes fragmented LinkedIn hiring data into a single sheet.
• Great for agencies or fast-growing teams handling many roles.

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Cons:

• You should validate that exported categories match your internal compliance rules.

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By moving from manual exports, to light no-code, to a truly autonomous AI agent, you keep full control of what LinkedIn data you use while reclaiming hours each week and dramatically improving the freshness of your Google Sheets insights.

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