How to extract IG data from followers and followers

In this example, we’ll show you how to collect leads (email addresses, phone numbers, usernames, and the “About” text) from Instagram user pages. This method leverages undocumented features of the Instagram API and is recommended for use with a secondary or non-primary account. Download the free trial version of LetsExtract to test this mode for yourself.

1. Launch LetsExtract Contact Extractor and select Mode #1 (for Instagram Scraper).

   

2. Log in to your Instagram account via the built-in browser. If you’re having trouble logging in or the page won’t load, try using a VPN or proxy. Once you’ve successfully logged in, navigate to the account page whose followers (or following) you want to scrape. For example, the page might look something like this:

   

3. Now click the “Extract followers” (or “Extract following”) button. Wait a few minutes while the program collects the accounts. Once the process is complete, you’ll see the extracted accounts in the list on the right-hand side:

   

   This method of collecting Instagram user IDs is safe. You can extract as many IDs as you need and save them into a separate file by clicking the “Copy IDs” or “Copy All” button (great for pasting directly into Excel). Once you hit the “Go to contact extraction” button, the data collection process will begin—but keep in mind that this part of the process may get your account banned if not handled carefully. To avoid issues, it’s best to collect data slowly and rotate accounts. If your account does get blocked, restart the search by clicking on the “Add IDs manually” button and adding the IDs of accounts that haven’t yet been processed.

4. The extraction process will then begin. You can monitor its progress in the “Queue” tab, and the results will be displayed in the “Results” tab.

   

   

5. Now it’s time to save your results! Click the “Export” button:

   

   You can export the collected contacts as a CSV, Excel, or text file, customizing the fields and headers for export. In our example, we managed to get the following results in just a few minutes of scraping: