& Mavenoid

Improving Resolution Rates Through a Customized & Innovative Support Approach

Medion is Germany's leading manufacturer of consumer electronics. As a B2C company, with a heavy focus on customers, both in product innovation and development, they struggled with streamlining their support data across the hundreds of products they produce.
The Mavenoid Effect
  • 32% resolution rate
  • 7% escalation rate
  • 71% positive ratings

The challenge:
Scattered support data

Being able to learn and understand their data was essential for Medion to be able to provide the high-quality support that they were aiming for. Additionally, by digitizing and deconstructing their existing data, they could begin to see trends in what their customers were searching for and what channels they were using the most, enabling them to put their customers first and improve self-service resolution rates.

“As a startup with fresh ideas, we could see how creative Mavenoid would be when it came to brainstorming use cases beyond support. They were able to implement our data in a very short time to create a fully fleshed-out solution. Overall they are really amazing and have very easy integrations.”
Thomas Heiermann
Managing Director, After Sales Service, Medion

The solution:
Streamlined data with a customized approach

Instead of choosing a mundane support solution, Medion went the innovative route and chose Mavenoid's Product Assistant. Mavenoid's deep product analysis broke down Medion's data, and with the insights, adjusted their support accordingly by learning what their customers like, dislike, and are looking for in their service.

Medion partnered with Mavenoid because of our customized approach. Throughout the whole implementation process, Mavenoid made it as easy to customized Medion's Product Assistant and be built in the company's native German language. The overall result? A personalized support approach for both Medion's support team and customers, all while tracking the metrics that count.

Key features implemented

Deep product analysis
Historic support data is used to identify common problems and areas best suited for automation.

Natural language understanding
Advanced semantic search allows customers to explain problems in their own words. The system interprets their intent and guides them to the right content.

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

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

Less Chat, More Problem Solving

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too complex for chatbots

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