Introduction

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Replies per Resolution (also known as, Replies per Ticket and Agent Touches per Ticket) is a metric that shows how many times a customer support agent replies to a customer before their issue is resolved. It's similar to Median Handling Time and provides a good indication of the effort an agent has put into resolving a case and often the effort exerted by a customer. 

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There can be a big difference between how customers perceive tickets closed with very few replies vs. those with many responses. Often, the fewer responses and faster Resolution, the better, but it depends on the nature of each interaction. 

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How to interpret Replies per Resolution?

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You will often find that your Customer satisfaction (CSAT) score and Median Resolution Times tend to decline as the number of Replies per Resolution increases. 

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Very high Replies per Resolution could indicate your agents are overly chatty with users or that they respond to customers unprepared with incomplete information. Monitoring and training can quickly solve this to ensure everyone in the team knows what's expected and how to talk with customers.

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It's also a good idea to look at how overall Ticket Volume and Median First Response Times impact Replies per Resolution. If your team's too focused on responding quickly, it could result in unnecessary back and forth with customers. 

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How is Median Replies per Resolution calculated?

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The Mava analytics page will calculate this for you; we take the Median number of Agent Replies across all of an agent's Resolved tickets.

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Why should you track Replies per Resolution?

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Replies per Resolution is just one of many resolution effort metrics' (other examples include Median Handling Time) that help measure a team's ability to handle different kinds of support scenarios efficiently. Your objective should be to target a sensible number based on the complexity of your product/service.

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It should not be viewed in isolation, as focusing too much on this metric might worsen CSAT metrics, as agents try to be too economical with replies, or might not build a good rapport with the user seeking support. 

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Conclusion

Median Replies per Resolution is a valuable metric to assess the effort support agents and end users exert before a support ticket is resolved and is similar to Median Handling Time.

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You will often find that your Customer satisfaction (CSAT) score and Median Resolution Times tend to decline as the number of replies per resolutions increase. 

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The metric should be viewed in the context of other data, especially CSAT, and you should be careful about optimizing for  any one metric to avoid unintended problems in other areas. Complex tickets that require lots of back and forth will always occur; that’s why Mava displayed a median vs. average number, to avoid complicated cases skewing the data. 

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If you want to speak to the Mava team about supercharging your web3 customer support or improving your customer support data and analytics then head over to the Mava website and book a demo with the team. 

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