How Our Support Team Decreased Our Average Customer Wait Time by Nearly 80% — In Under Three Months

Customer support

“Customer Success” is one of the most straightforwardly named business functions. You want your customers to succeed.

Straightforward — but not always easy.

When I took ownership of our support team here at Yext, I observed a handful of instances where customers called our support line and experienced long wait times. Hanging out in hold limbo is the opposite of a great experience — and I knew right away that we had to rectify that.

Support volume changes all the time, and you need to have the ability to flex coverage during those busiest times. Here are three simple strategies I used reduce our phone wait time that will help your business scale and stay nimble:

1. Identify & Establish Industry Standard KPIs

The first step in reducing call wait time and improving your support experience is to understand industry standard KPIs — and how your company compares.  In my research, I prioritized two KPIs to track: average wait time and abandon rate.

Average Wait Time (AWT), also known as Average Speed of Answer (ASA), is the average time an inbound call spends waiting in queue or waiting for a callback if that feature is active in your Interactive Voice Response (IVR) system. The standard is 7 seconds for Information & Technology companies, based on TalkDesk’s 2020 TalkDesk Contact Center KPI Benchmarking Report.

Abandon Rate is the percentage of inbound phone calls made to a call center or service desk that is abandoned by the customer before speaking to an agent. It is calculated as abandoned calls divided by total inbound calls. Abandon rates have a direct relation to waiting times. The standard is 10% for Information & Technology, based on TalkDesk’s 2020 TalkDesk Contact Center KPI Benchmarking Report

But simply identifying KPIs isn’t enough if you aren’t actively managing them. To address this, we also built out real-time intraday reporting directly in our Contact Center focusing on AWT, tracking the longest wait time in the queue that day. This allowed managers to proactively identify instances where a call wait time exceeded our goal and dig into the individual call flow to learn more. 

2. Optimize Contact Center Call Queue Logic

My next step was to gain a deeper understanding of our customers’ experience when calling into one of our support lines. Then, I could educate our team about how their status in our telephony platform might affect that customer journey. 

For example: one simple way to create a better experience is establishing logic based on Agent Status.  When some agents are unavailable due to team meetings and the like, we can trigger a message that immediately asks a customer for a call back number, instead of just leaving the customer on hold.  

We also found it critical to offer customers the opportunity to leave a callback number when there is a wait, and we experimented with the timing of that offer. Currently, we first offer this at the three-minute mark, and then again every 60 seconds afterward. Why three minutes? We identified that our customers’ average Abandon Rate lands at 3 minutes 57 seconds. (That’s part why it pays to track your Abandon rate!) 

Lastly, we added voice overs that point customers to our self-service materials, webinars, and email support contact information to remind the individual of their options within our omnichannel support strategy. Self-service options are critical to serving customers needs: Dimension Data says that 73% of customers prefer to use a company’s website for support, and according to Parature, 84% of customers want to resolve their own issue using search, before raising a support ticket or calling customer service. (Learn more about that here.)

3. Review of Our Workforce Management Strategy

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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