Social profile scraper into Google Sheets

What it is

This n8n workflow logs the recent posts of a social profile in a spreadsheet. You send n8n’s built-in chat the link of a LinkedIn, YouTube, Instagram or X profile. GPT-4o mini reads the link and picks the network, and that network’s Apify scraper fetches the posts: 20 from LinkedIn and X, 30 reels from Instagram, 10 videos and 10 shorts from YouTube. The scraped items are checked against the rows already in your spreadsheet, and the new ones go into that network’s tab. Two more branches watch the Instagram and YouTube tabs for new rows. OpenAI transcribes each reel, a second Apify actor fetches each video’s captions for GPT-4o to join into one text, and both transcripts are written back into their rows.

Who it suits

Marketers, researchers and creators who follow other accounts and want the posts in a sheet they can sort and search. It only reads public profiles: nothing is posted or changed on any network.

You need some n8n: importing a file, adding three credentials and swapping placeholders in 17 nodes, plus a spreadsheet of your own with four tabs. If that is new and you would rather not learn it, skip this one. The page it came from estimates 13 minutes, which assumes the accounts and the spreadsheet already exist.

Where to use it

Any n8n you run will do, as long as it can reach Apify, OpenAI and Google.

• n8n Cloud: import the file into a new workflow there
• Your own n8n server: the same file, the same steps
• Google Sheets: sort, filter and chart the posts, or search the transcripts
• A second workflow: the rows can feed a summary or a list of content ideas

Setup

Get it saves a zip with workflow.json and Mindket’s setup notes in your downloads folder. Have these ready before you import it.

1. In n8n, create a workflow, open its menu, choose Import from File and pick workflow.json.
2. Add an OpenAI credential and select it in OpenAI Chat Model, OpenAI and OpenAI1.
3. Add a Google Sheets credential and select it in the 12 Sheets nodes. They are the four Add Records nodes, the four Find nodes, Update IG Sheet Transcript, Update YT Sheet Transcript and the two Trigger: Row Added nodes.
4. In those nodes, swap YOUR_SHEET_ID for your spreadsheet’s id. Swap YOUR_IG_REELS_TAB_ID, YOUR_YOUTUBE_TAB_ID and YOUR_X_TAB_ID for the ids of those tabs. The LinkedIn nodes use gid=0, the first tab.
5. In the Authorization header of LinkedIn Scraper, YouTube Scraper, Instagram Reel Scraper, X Scraper and Generate Transcript, swap <YOUR_APIFY_TOKEN> for your Apify token and keep the word Bearer and its space.
6. In Generate Transcript, swap YOUR_APIFY_PROXY_GROUP in the body for the name of the proxy group you chose.
7. Save, open the chat from the editor and send one profile link as a test. Then press Publish, because the two Sheets triggers only run on a published workflow.

The page it came from tells you to create an Apify credential and pick it in an Authentication section. The file holds no such setting, so the token goes in the header fields. If you would rather keep it in a credential, create an HTTP Header Auth credential, select it in those five nodes and delete their Authorization header.

How to use it

Open the chat from the editor and send one link per message: a profile for LinkedIn, Instagram or X, a channel for YouTube. The scraper waits for Apify to finish, and the posts appear in that network’s tab. Within a minute the Sheets trigger sees the new Instagram or YouTube rows and starts their transcripts, one row at a time, and the Transcript column fills in. A video or reel that is already in the sheet is not added again.

Example

A message sent to the chat:

https://www.youtube.com/@examplechannel

The classifier answers YouTube, and YouTube Scraper sends this to its Apify actor. Its body also holds a list of switches, all off, which is left out here.

{
  "maxResults": 10,
  "maxResultsShorts": 10,
  "sortVideosBy": "NEWEST",
  "startUrls": [
    { "url": "https://www.youtube.com/@examplechannel", "method": "GET" }
  ]
}

Each new video becomes a row in the YouTube tab with its title, link, views and likes. Then Generate Transcript fetches its captions, OpenAI1 joins them and the Transcript column of that row fills in.

For newcomers and experts

If you are new. n8n draws a workflow as boxes joined by lines, and each box, a node, does one job. This file holds three small workflows side by side: one starts from the chat and scrapes, and two start when a sheet gets a new row. Send one link first, read that run under Executions, then publish. Each node shows what it received and what it sent, which is where a wrong token or a missing tab id turns up.

For experts. The four networks follow one pattern. Only Instagram and YouTube get a transcript.

Each branch has a Find node that looks the link up in the sheet. A Merge node (Merge3 for LinkedIn, Merge1 for YouTube, Merge for Instagram, Merge2 for X) combines it with the scraped items on url. It keeps the ones with no match and passes them to Add Records. On the YouTube branch, If2 also drops any item without an id.

Good to know

Each run spends money on two services, and it reads other people’s accounts.

• Billing: Apify bills every scraper run, and OpenAI bills the classifier, the reel transcripts and the caption join. A first run on a busy Instagram profile can transcribe 30 reels
• One link per message: the classifier has four categories and no fallback for anything else
• What each actor expects: LinkedIn Scraper sends the message as company_name and Instagram Reel Scraper sends it as username. Try each network once with a real link and read what the actor returned. If one rejects a full link, send what it asks for
• Long videos: OpenAI1 gets a video’s whole caption list in one request, so a long video costs more and a huge one may exceed the model’s limit
• Terms and privacy: scraping can break a network’s terms, and the sheet will hold other people’s names, posts and follower counts. Check the terms and keep the spreadsheet private
• Two checks for your first run: the LinkedIn check compares url, while the scraper’s items carry post_url, so it may keep every post. Add Records to LI Sheet then updates a repeat in place. And Update IG Sheet Transcript reads url from Download IG Reel, whose output is the downloaded file. Confirm the transcript lands on the right row, and if it does not, read url from Loop Over Items
• Publish first: the two Sheets triggers do nothing until the workflow is published
• Merge order: keep the sheet lookup on the first input and the scraper on the second if you rewire a Merge
• Actors: the file names each Apify actor only by its id, in the node’s address. Open each id on Apify to see what it is and what it costs
• Keys: the Apify token sits in header fields of five nodes, so it travels with any export of the workflow
• Repairs: the file pointed Find YT Rows, Find IG Rows and Find X Rows at a template copy of the spreadsheet, a different file from the one the other nodes write to. Mindket points every Sheets node at YOUR_SHEET_ID. It also replaced the author’s Apify proxy group in Generate Transcript with YOUR_APIFY_PROXY_GROUP
• Credentials: the JSON holds none, and nothing from its author’s account