Sneaker Bot for Copping Limited Editions

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  • Date Published
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Our client wanted to build a sneaker bot to monitor the market and purchase highly coveted pairs on sneaker sites quicker than humanly possible.

With the booming popularity of the sneaker culture, nabbing limited-edition drops online has become almost impossible. Today, it’s a race not only among hardcore sneakerheads competing in inserting their card details on a release day fastest but also against consumers using automated software — bots.

Bots, designed to make the checkout process instantaneous, have in fact become an essential part of this culture. Our client wanted to build their own high-performance sneaker bot that would be able to monitor the market and purchase highly coveted pairs on sneaker sites quicker than humanly possible. They turned to ITRex developers who had experience in building such tools.

The Project

ITRex’s task was to:

  • Create a proof of concept to validate the technical feasibility of the software product.
  • Build the bot that would be able to scrape targeted websites and buy sneakers on release days through automated checkout, including mass-entering online queues using proxies to avoid an IP ban.


An automated data scraping and ecommerce system designed to patrol the market of limited sneaker drops and collabs, and buy in parallel pairs using different IPs when timing is critical. The bot’s key features are:

  • Allows the user to design and schedule data scraping projects.
  • Performs scraping via the hosts’ API, if available, or a test automation tool.
  • Extracts product information, from style numbers to prices, sizes, and colors, from web pages.
  • The scraped data is stored locally in structured formats for further use in shopping projects.
  • Automatically fills in user authentication forms on a marketplace on a release day.
  • Automated add-to-cart scenario.
  • Automated checkout process.
  • Makes purchases with a stored credit card or PayPal.
  • Automatic IP rotation and geolocation targeting using proxies to appear as multiple buyers.