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Case Study

Establishing Trust in the Videogame Market

Automated deal aggregator powered by scraping and NLP.

Challenge

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.

Solution

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

Technology

  • 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.

Results

10,000+

product pages

checked for price every hour

100-200

best deals

presented to the users

5-10

minutes

of human maintenance / day

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