20 DigitalGenius Case Studies

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Read 20 Case Studies from users in the Information Technology and Services industry to get the most important information that is specific to your business.

  • Aylesbury Vale Reduces Costs and Drops Response Times by 50% with DigitalGenius
  • Brooks Brothers® Resolves 20% of their tickets within 3 months of launching with DigitalGenius
  • Coursehero resolves 20% of support tickets with DigitalGenius AI
  • There has been a 50% decrease in average handle time at Freelatics
  • G-Star Resolves 40% of their total volume with DigitalGenius Automation
  • Imagine Learning Reduces Customer Service Handling Time By 70% With DigitalGenius
  • KLM Transforms Social Customer Service with DigitalGenius AI
  • Magoosh Uses Digitalgenius to Reduce Customer Support Queue by 50%
  • On Running Outpaces Competition with 60% of All Queries Resolved by DigitalGenius
  • Packlink - Customer Case Study
  • Quiksilver resolves 65% of all tickets within two weeks of launching DigitalGenius
  • 80% of Cancellations and Refunds Fully Resolved
  • Our Platform Fully Resolves 15% of Seratos Support Tickets
  • Skullcandy Resolves ~60% of Tickets fully resolved by DigitalGenius
  • Automates over ⅓ of German enquiries with 99% Accuracy in 6 weeks
  • Automates over ⅓ of German enquiries with 99% Accuracy in 6 weeks
  • StarOfService Saw a 46% Reduction in Average Handling Time (AHT) After Implementing DigitalGenius.
  • Digitalgenius Powers 40% of the Perfume Shop Tickets, Boosting CSAT, AHT and FCR
  • Volcom resolves 27% of their ticket volume with DigitalGenius Automation within 4 weeks.
  • Zip is saving the equivalent of 1.5 Full Time Agents with Autopilot

About DigitalGenius

DigitalGenius brings practical applications of deep learning and artificial intelligence into customer service operations of leading companies. Its Human+AI Customer Service Platform combines the best of human and machine intelligence enabling companies to deliver on increasing customer expectations. At its core are deep-learning algorithms, which are trained on historical customer service transcripts and integrated directly into the contact center’s existing software.

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