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PANEL DISCUSSION: THE ART OF

Achieving 4.5 CSAT While Resolving 2X the Industry Avg. of Tickets per Agents 

The Recipe for Social Quantum’s Modern Support Journey

 

Key takeaways ?

  • How to increase your CSAT to more than 4.5 whilst leveraging bots and automations.
  • How to improve your agents capacity to more than double of the industry average to 1600 tickets resolved per agent per month.
  • How to leverage the latest and greatest support innovation to provide a state of the art in-app Modern Support Journey.
  • How to excel at your product innovation flywheel leveraging the power of support data and build products your customers will love.
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Webinar Social Quantum

 

About the webinar

Join Social Quantum’s Head of Support, Gennadiy Korzhevsky, for a panel discussion revealing the secret ingredients of their recipe for the ultimate customer experience!

Social Quantum is a Helpshift customer dedicated to customer support innovation and excellence. They have successfully deployed the latest Helpshift features to provide the highest level of service to their customers and to continually build great products. Social Quantum continues to leverage innovative support features including integrating Smart FAQs, answering app store reviews quickly via their support dashboard, providing support to their community within Discord, integrating complex bots and automations – they are providing the full Modern Support Journey.

Social Quantum has been able to provide a fast resolution to their players, resulting in a 90% self-service rate and a time to first response of 1h52 (when the industry benchmark is 24h). Simultaneously, they’ve seen an exceptional average CSAT score of 4.5. Not only have they produced enviable KPIs, they’ve seen these results while increasing efficiency across their support operations, their agents being able to answer twice the industry benchmark of tickets per agents (1600 per month). Utilizing AI-powered bots to scale support operations, Social Quantum’s volume of tickets increased by 100%, yet the number of agents remained the same.