Resetting Metric Benchmarks with AI in Support
Why is it important to reset metric benchmarks when using AI?
Resetting metric benchmarks is crucial as AI automates more interactions, leaving only complex issues for human agents. As AI takes over simpler tasks, metrics like handle times, resolution times, and one-touch resolution rates may increase. This shift requires managers to adjust their expectations and benchmarks to reflect the new reality where human intervention is reserved for more challenging cases.
By resetting these benchmarks, companies can better assess the performance of their support teams and ensure that they are meeting the new standards set by AI integration.
More related questions
What are the top benefits of using AI in gaming customer support?
AI in gaming customer support primarily reduces agent email and chat volume. By implementing AI, gaming companies have experienced a significant decrease in the volume of emails and chats that agents need to handle. This allows agents to focus on…
How are gaming companies using AI for automation and deflection?
Gaming companies use AI to automate repetitive tasks and deflect common customer queries. By focusing on automation, these companies can reduce the time agents spend on basic transaction tasks, allowing them to concentrate on more complex cases. AI…
What advice do AI early adopters in gaming have for others?
AI early adopters in the gaming industry emphasize the importance of investing in quality content. Since AI bots rely on existing content and training data, ensuring that your help content is accurate and comprehensive is crucial. Additionally,…
How can gaming companies improve their AI-driven customer support content?
Improving AI-driven customer support content involves leveraging machine learning cues to refine and update help articles. Gaming companies should focus on identifying content that needs attention and making specific improvements, such as updating…
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“It now resolves 71% of queries (over 35,000 every month), meaning more time solving complex issues and improving UX.”
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