User research project exploring the various support desk that exists across CN to understand if one or more of them could be improved by deploying a support chatbot as well as the various automation systems that come with it.
The manager for the main internal service desks came to our team looking for ideas and advice on how to implement chatbot technologies to reduce the number of “simple fix” calls they were receiving.
With such a vague definition of the type of call the chatbot would be handling before transferring the question to a human helpdesk agent my first step was to understand:
- What are these “simple fix” calls about and is it something that needs a chatbot?
- What is the current process and experience of both callers and support desk agents?
- How would a chatbot influence this experience? And how can we make sure it actually helped?
To answer these questions I decided to do some research around the processes and the user needs. Through a contextual inquiry I looked at the current processes by analyzing the support desks conversation trees and by shadowing a clerk during their shift to get a good understanding of the real workflow as well as the amount and length of the calls.
The research phase also looked at statistical analysis of the call center to understand the burden that these “simple fix” calls are imposing on the current resources.
After this research it was my conclusion that because of the low volume of calls combined with the extra complexity from the caller-side that a chatbot would introduce this support desk was not the best candidate for chatbot introduction at CN.
This research also illustrated other avenues of improvement to enhance the support desk workflow and simplify their call handling as well as improvements and bug fixes on the application side to diminish and hopefully remove the needs for these calls entirely.
Eventually this project helped CN and the user research team better understand how to apply chatbot technologies so another service desk that seemed a better candidate was selected to perform a second round of research.