Establishing Trust in the Videogame Market

Automated deal aggregator powered by scraping and NLP.


VidaPlayer, a leading videogame reseller in Spain and Latam, was exploring affiliate marketing as a new revenue stream that would be synergic with its core e-commerce business. The company also wanted to address the uncertainty around video game pricing and a growing number of scam sites.

Not unlike other online deal platforms, VidaPlayer was heavily dependent on human labour (community-driven websites) and/or vendor-specific API/data feed integrations (price comparison websites), both of which make them difficult to scale. Both designs also inevitably lack a systematic approach to price monitoring - the future was clearly data-driven.


Build an automated deal platform that automatically identifies top-selling products in given categories, discovers them on market’s leading e-shops, monitors their prices, identifies the best deals and publishes them on various channels, such as website and social media.

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System Architecture


  • Most of the system is built using Python.
  • Scraping components use Scrapy framework.
  • Product matching engine uses a combination of pre-processing, term weighting, document vector similarity comparison and domain-specific rules. Experiments with neural networks have shown promising results and are likely to be implemented at larger scale in the next phase.
  • Internal UI components were built using Elm language.
  • All components are hosted on AWS infrastructure, and where possible, they run as serverless Lambda functions.



product pages

checked for price every hour


best deals

presented to the users



of human maintenance / day

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