Customers expect you to answer a live channel (e.g. phone) a lot more quickly than they would expect you to respond to an email, for example. A customer who chooses to call wants real-time support, whereas a customer who emails is already expecting at least a window of time before they receive a response. That's why we schedule our agents with channel-specific SLA's in mind. With phone being our only live channel, we adhere to a tight SLA, where agents consider phone their top priority. Next, scheduled callbacks and 1:1 training are time-bound so they are considered the next priority. Finally, requests submitted via email or form tend to have the most flexibility in urgency and are typically more complex in nature, so that's where we have set the broadest SLA.
We then took a deeper look at call center data to understand our peak call hours. We analyzed call volume per support line, hour of the day, day of the week, and more. From this analysis we were able to identify the minimum number of representatives needed at any time on each phone queue, helping us increase efficiency and reach more of our high-need callers.
Lastly, we designed and deployed emergency coverage plans, including cross-training across the team and breaking down silos so that more team members were equipped to answer phones in case of absences and conflicts.
After making these adjustments, we reduced our average wait time by nearly 80% from the previous quarter. Today, our team is trending at an average wait time of 16 seconds versus an identified standard of 20 seconds across call centers!
The biggest learning through all of this is to remember that managing a customer support center is unpredictable. You will never be able to predict the precise call volume on a given day but I've found that…
Data is your friend
Intraday monitoring is invaluable
The best cure for staffing emergencies is a contingency plan in the first place
Strategies are not set in stone, so be nimble
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