How to export LinkedIn saved posts to Excel or Google Sheets

Create a full-content CSV with LinkedIn Bookmark Exporter

LinkedIn itself does not provide a full-content spreadsheet export for bookmarks. A working sheet needs the complete post text, author, source URL, dates, and other source fields so you can evaluate records without reopening every post.

1. Install LinkedIn Bookmark Exporter Chrome Extension
2. Open LinkedIn Saved Items → Saved posts and articles.
3. Open the extension, select CSV, and start the export.
4. Leave the page open while the extension auto-scrolls and collects the saved history.
5. Download the completed CSV and spot-check a few long posts, old posts, and URLs.

Rename the untouched download linkedin-saved-posts-2026-08-28-raw.csv. Make a separate working copy for filters and annotations. If something is accidentally sorted, deleted, or overwritten later, the raw file remains your recovery point.

Import CSV into Excel without garbled text

1. Open a blank workbook.
2. Use Data → From Text/CSV instead of double-clicking when you need control over encoding.
3. Select the exported file and choose UTF-8 if Excel asks for file origin or encoding.
4. Confirm that the delimiter is comma and that multiline post text remains inside one record.
5. Load the data, select it, and create a table with headers.
6. Turn on text wrapping for the post-text column and freeze the header row.

If an author such as “José” appears with broken characters, stop and re-import with UTF-8. Do not manually repair names: the same encoding error can affect every non-English character and emoji in the file.

Import CSV into Google Sheets

1. Create a new spreadsheet.
2. Select File → Import → Upload.
3. Upload the CSV and import it into a new sheet.
4. Confirm comma separation and automatic text conversion.
5. Freeze row one and choose Data → Create a filter.
6. Restrict sharing before adding private research notes.

Do not paste thousands of lines directly into the first cell. CSV import understands quoted commas and line breaks; paste operations are more likely to split long posts incorrectly.

A small schema that supports real retrieval

Avoid calculating value from engagement alone. Likes and comments can be useful sorting signals, but a popular post is not necessarily accurate or relevant to your project.

Three views worth creating

• Inbox: Status is blank. This is the review queue.
• Active research: Status is Keep and Topic matches the project at hand.
• Used: Status is Used. This shows which bookmarks have actually contributed to a decision, article, campaign, or conversation.

These views are deliberately plain. A spreadsheet becomes useful when it reduces retrieval time, not when it contains the most elaborate dashboard.

Clean the sheet without damaging evidence

If a URL contains tracking parameters, create a separate normalized URL column for comparison instead of changing the preserved source value.

Append future exports carefully

Each run of LinkedIn Bookmark Exporter is a fresh snapshot, so importing the whole file into the master sheet will create duplicates. Use this sequence:

1. Run a new CSV export and save it with that day’s date.
2. Import it into a temporary tab rather than the master table.
3. Compare each source URL against the master sheet.
4. Append only rows whose URLs do not already exist.
5. Preserve your manual Topic, Status, and Why saved columns.
6. Record the last successful export and import date.

For a more note-centered setup, compare Notion and Obsidian. To understand the source-file choices first, read the complete LinkedIn export guide.