Technologies Involved:
PYTHON
postgresql
ANGULAR
Web Apps
Project Description

Autobait is an innovative LinkedIn campaign automation tool that streamlines and optimizes your LinkedIn marketing efforts. With the power of Selenium and Python core scripts, Autobait enables efficient data scraping, allowing you to gather valuable information from LinkedIn profiles. The tool offers a range of features, including auto-follow, auto-connection requests, connection list management, and the ability to like posts. By automating these tasks, Autobait saves you time and effort, allowing you to focus on building meaningful connections, expanding your network, and engaging with relevant content on LinkedIn.

 

Scope Of Work

Our scope of work for the Autobait project is to provide an efficient and user-friendly LinkedIn campaign automation tool. We have completed the UI/design and development phase of the project. Our goal is to enhance your LinkedIn marketing efforts by utilizing the power of Selenium and Python core scripts for data scraping from LinkedIn profiles. The tool includes features such as auto-follow, auto-connection requests, connection list management, and post-liking. With Autobait, we aim to maximize your reach, optimize your LinkedIn marketing strategy, and help you achieve your business goals effortlessly.

 

Our Solution

By leveraging the finest technologies and implementing best practices, we provided a reliable and effective LinkedIn campaign automation tool. Our solution helped save time and effort by automating repetitive tasks, allowing the client to focus on building valuable connections, expanding their network, and engaging with relevant content on LinkedIn. Here are the services we provided and the technologies we utilized:

  • Implemented the Python/Django and Angular frameworks for this project. These frameworks are known for their ease of use and their ability to deliver high-quality results.
  • To ensure smooth data scraping from LinkedIn profiles and to avoid being banned, we integrated proxy support into the tool. 
  • Implemented strategies to manage IP addresses and proxies effectively. 
  • Incorporated time intervals between requests to LinkedIn to prevent overwhelming the platform and avoid detection. 
  • Developed automated scripts in Python to handle various campaign features, such as auto-follow and like posts on LinkedIn. These scripts, integrated with the Angular front-end and powered by a PostgreSQL database, enable seamless execution of campaign actions.

 

 

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