How to scrape Twitter profile data without an API

Twitter is a popular social media platform for sharing daily updates with over 300 million users worldwide.

This makes Twitter a valuable data source for finding sentiments about your own brand, and your competitors, for discovering new customers, influencers, trends, and more.

Our Hexomatic Twitter profile data automation  will  help you scrape Twitter profile data in seconds including: 

✅ Date of the Twitter profile creation

✅ Profile description

✅ Profile ID

✅ Profile location

✅ Profile name

✅ Pinned tweets

✅ Profile image

✅ Whether the profile is protected or not

✅ Profile URL

✅ Username

✅ Whether the profile is verified or not

✅ Whether the profile is withheld or not

✅ Followers count

✅ Tweets count

✅ Profile listed count. 

By gathering this information, you will be able to use all the potential of Twitter to find new leads, influencers, competitors, etc.

A list of prospects can be automatically created based on their location, or a list of influencers can be created with their stats such as followers, tweets, images, etc.

Then you can contact your potential leads or influencers directly via Twitter using their profile URL or ID.

In this short tutorial, we will walk you through how to scrape Twitter profile data on autopilot using Hexomatic without needing to program in python or using any API.

Step 1: Create a new workflow

To get started, create a new workflow from data input. 

Step 2: Add the Twitter usernames or IDs to scrape

Next, add the Twitter usernames or IDs to scrape. You have two options to proceed: add a list of usernames/IDs manually by choosing the Manual paste/List of inputs option or by uploading a CSV file, containing the usernames/IDs.

Step 3: Add the Twitter profile data automation

Add the Twitter profile data automation, selecting data input as the source. Select your endpoint (Username/Id), then choose the preferred fields to be captured from the drop-down menu. 

After filling in all the required fields, click Continue.

Step 4: Run or schedule the workflow

You can run the workflow or schedule it.

Step 5: View and save the results

Once your workflow has finished running, you can then review your data in the Results Preview and export it in CSV or Google Sheets.

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