joinus.team · Workflow & Planning
3 items
Bulk export LinkedIn job applicants to Joinus.team, Google Sheets, or CSV with automated data extraction End copy‑paste. Start hiring. Joinus.team LinkedIn Applicant Exporter pulls every Easy Apply candidate from a LinkedIn job post and turns them into clean, shareable data in seconds. Focus on interviews, not spreadsheets. Key actions * Instant capture: name, email, phone, location, experience, education, photo, profile link. * One‑click export: CSV, Google Sheets, JSON, or direct push to Joinus.team ATS. * Side‑panel preview: watch candidates appear live while you stay on the page. * Notes & status: tag and organise before you export. * Free and private: local processing, no account, no tracking. Five‑step workflow 1. Install the extension. 2. Open any LinkedIn **Job Applications** page. 3. A side panel opens on the right and auto‑extracts each candidate. 4. When the list is complete, click **Export**. 5. Choose CSV, JSON, Google Sheets, or push to Joinus.team ATS. Done. Why recruiters install Pain → Time lost → Exporter fix • Copying 50 profiles → \~4 hours → < 4 minutes • Spreadsheet cleanup → 20 min → 0 s • Sharing with team → 5 min → Instant Who loves it * In‑house recruiters juggling many roles. * Agencies drowning in Easy Apply résumés. * Solo founders hiring their first team. * HR pros who still live in Excel. Privacy & trust * All work stays in your browser. * No login. No cookies. No servers. * GDPR‑ready. * Open‑source code on GitHub. Roadmap * Filters by skills, location, experience. * Bulk status updates. * Time‑saved analytics. Install now. Free up your day and hire smarter.
Feb 24, 2026
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Media assets
Screenshots and videos on the listing.
Has promo video
Whether the listing includes at least one video.
Languages
Declared language locales.
Developer website
Listing exposes a developer website URL.
Contact email
Listing exposes a contact email.
Keyword in name
Case-insensitive substring match in the name.
Keyword in description
Case-insensitive substring match in the description.
Keyword occurrences in description
Count of case-insensitive occurrences in the description.
Category user-count percentile
Share of same-category extensions with fewer users (null if unknown).
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