Cylinda
& Mavenoid

Cylinda’s Customers Resolve 31% of Troubleshooting Issues on Their Own

Cylinda is a Swedish home appliance company that has manufactured laundry and kitchen appliances since the 1950s.
Mavenoid's Impact
  • 31% self-service resolution rate
  • Self-service support for 15+ Products
  • ~950 resolutions per month

Challenge:
A growing volume of customer requests for a diverse product range

Cylinda faced two major challenges: 1) A diverse range of home appliance products required support agents to have a breadth of knowledge, and 2) repetitive troubleshooting requests were eating up their agents’ time, preventing them from focusing on customers with unique issues.

Cylinda needed a way to not only reduce the predictable support tickets, but also to enable service agents to quickly access a knowledge base of solutions across their wide range of products.

“Mavenoid enables us to provide high-quality troubleshooting to our customers without delay, whilst also providing knowledge within our service department in ways we couldn’t before.”
Tobias Hagberg
Regional Manager, Cylinda Service

Key features implemented

Decision support
AI-powered decision support displays probable solutions to agents during troubleshooting.

Natural language understanding
Type or speak — Mavenoid detects and understands your language.

Resource library
All your knowledge at your agents’ fingertips. Use shortcuts to share resources instantly with customers.

Teachable AI
The system learns from every interaction, and continues to improve on its own.

Solution:
Self-service where wanted. Decision support where needed.

Mavenoid’s self-service solution is purpose-built to handle troubleshooting requests like Cylinda’s. After implementing across a suite of 15 products, the product assistant was able to resolve 31% of sessions without the need for any service agent, allowing them to focus more time on unique and challenging support requests.

Mavenoid has empowered Cylinda to better serve those complex requests by providing context and potential solutions via the decision support feature—reducing the need for agents to dive into manuals while on calls with customers.

Less Chat, More Problem Solving

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Too Complex for Chatbots
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