Recently, John Bonini sat down with our CEO, Pete Caputa, for an episode of the Metrics & Chill podcast. Pete and John talked about how the customer support team at Databox cut down median first response time for our in-app and website chat.
If there’s one thing we think we’re good at, it’s helping agencies, business owners, and individuals save time, money. Unfortunately, we weren’t always getting back to our users in a timely manner when they had a question. During the conversation, Pete talked about how, for close to a year, the response time of our Customer Success team was 3 hours, and how we finally improved it in one week with one simple change.
A survey we ran earlier this year of 28 support pros, gave us some ideas on reducing response time. But, this one change wasn’t obvious to us for a long time, despite major investments in building a bigger team, training and management.
Read on for more details, or listen to the full episode here:
The Metric: Median First Response Time (Median FRT)
Prior to the team rolling out website chat a few years ago, we solely used HelpScout’s email ticketing system to respond to customers. And while this communication channel has proven over the years to be great, chat seemed like the next big opportunity for the team to leverage in order to enable clients to reach out to them easier, and quicker.
At the initial stage, response time was good, but over time, the volume of chats increased greatly and the team took on other responsibilities too. It became harder for the team to respond quickly.
“We just didn’t feel like we had enough people in there to pull it off.”
As a result, one of the ways Caputa would go on to tackle this was to hire more people, “Currently, there are more than 70 people working at Databox, with a little more than half working in sales support and marketing, and of which 12 manage chats.
“We tend to hire people in that support role as a way to train them.” So, as we promoted people to other roles and brought in new people, we had the added problem of constantly training them. During several periods, we thought that the issue was training. So, we invested a lot more in our training material and program.
We also Invested a lot in our knowledge base. Put simply, this was done “because it allows us to respond quickly without sitting there and writing a book every time.” But it also took a big investment to get it started, including “taking one of our best people and having them work on that for a quarter.”
All of these things took time, of course. In the meanwhile, response time stayed high too. We kind of just accepted it as fact.
The Opportunity to Reduce Median First Response Time (Median FRT)
For the Databox team, this metric was particularly important because:
- Most users tend to block out time to learn about the product and build their dashboards, and oftentimes, they need real-time answers to their questions.
- A lot of our sales opportunities come from chats
So, what’s the one simple thing we did to reduce response time?
“We simply established hours for people to be in charge [of chat]. This way, we always had a few people who were responding right away, not distracted by their other responsibilities. When they aren’t “in charge of chat, they can execute their other responsibilities, such as building dashboards for users and reaching out to new or trial users to offer setup assistance.”
This change also allowed us to establish a “12-hour coverage [window] for chat.”
“We know that chat drives deal volume.”
With nearly 5,000 signups monthly and 2,500 customers, the team is pretty busy chatting with both free users and paying customers. But, the bulk of our chat interactions are done upfront with new users, while customers just need to make tweaks to their dashboards on a roughly quarterly basis.
Which then makes the majority of support interactions (about 70%) with new users–and getting them set up quickly.
As a result, chat is a major driver of new deals for our sales team.
And in fact, this change in response time also shows signs of helping us generate more deals.
Proving that is the fact that the team saw “about a 10% increase in deal volume from chat in the same month they saw a decrease in median response time, of which 35% of those end up becoming customers.”
“Since Customer Lifetime Value (CLTV) currently hovers between $4,000 and $5,000, that 10% increase in deal volume equates to about an extra $20,000 gained in ARR.”
“It’s not just the speed [of individual support reps responding]. We just need more support people [in order to cover more hours in the day].”
In order to reduce response time even more, Databox is hiring support and sales people on different continents so as to be able to cater to our clients 24/7. Since this metric is a median response time for all chats and that includes chats we get outside of our working hours, the only way we’ll reduce it further is by staffing support 24/7.
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