How we optimized our customer support to ensure quality at scale

The best any support team can hope for is to prepare customers for success. But when they start asking your advice on how they can do the same, you know you’re doing something right.

Our customer support team has worn a number of hats down the years. We’ve been consultants for clients upgrading or adopting new products; we’ve scrambled to fix technical issues outside our own products; we’ve even traveled hundreds of miles to tackle things like school firewall issues. From time to time, we also managed to provide technical support for our own products 😉.

We’ve done all that and more because our customers are our partners. That’s the way we’ve seen it since the start. Whenever they needed our expertise to overcome a roadblock we’ve given it to them, knowing that when they grow, we grow.

During Learnosity’s early days, I made a conscious decision to build a team that would be comfortable with hat-swapping, easily switching between pre-sales and post-sales responsibilities. 

As a smaller company, this was totally necessary. It gave us a natural gatekeeper against misselling or over-selling what Learnosity offered. Anyone involved in pre-sale technical support provided post-sale technical support too, since:

1. they’d already built a relationship with the customer,
2. they were best-placed to help customers understand what the product could do for them, and 
3. continuity builds trust. 

But that kind of above-and-beyond, one-to-one support becomes unsustainable down the line. As client numbers went up and we looked to expand the team by bringing in new hires, we realized the old way had gone from being a growth accelerator to a growth inhibitor. 

For one thing, recruiting people who could easily switch between the two roles became nigh-on impossible. Even within the team, people were naturally leaning toward one role or the other for any number of reasons – personal and professional. It wasn’t impacting the quality of our day-to-day support, but we knew things had to change or it would only be a matter of time before it would.

As client numbers went up and we looked to expand the team by bringing in new hires, we realized the old way had gone from being a growth accelerator to a growth inhibitor.

What does effective support look like at scale?

We kicked off the discovery phase of the restructuring process by asking ourselves one question: “What does effective support look like for a company with 200+ clients?”

Given we had around 90 or so enterprise-size clients at the time, this helped us frame our thoughts around scalability over the longer term. It also opened up a broader conversation with key stakeholders from the technical and business sides of the company.

Same principles, better process

Those internal conversations helped us identify a few key goals to build our team structure around:

• Empowered
  Given that our customer support team spanned multiple countries and timezones, we knew that any structure we put in place needed to empower everyone on the team to make the best decision they could with the information they had. The goal was to make this as autonomous as possible to help remove any bottlenecks caused by the time-lag of relying on people or functions in other timezones.

• Robust
  Similarly, we wanted to create a team structure with leadership, succession, and subject matter expertise built-in at multiple levels. This would help reduce the burden and reliance on a couple of “key people” by improving how we disseminated knowledge, experience, and ability across regional teams. 

• Scalable
  While working with our “large company” model in mind, we still wanted to maintain a pragmatic approach as we moved forward. For example, some functions that would later be self-sufficient at scale were – for now – still part of the day job for the support or technical business development teams. However, we wanted to make sure that we could easily handle those functions even as we grew by having a deep reservoir of knowledge that our teams or new hires could draw from.

We were lucky to have a knowledgeable and conscientious group of people on the team who relished the chance to specialize in the areas they preferred.

Following multiple rounds of consultation, we decided that we needed to do two things to succeed:

First, we needed to split the customer support team into two separate but closely related functions: namely, pre-sale and post-sale technical support. 

Second, we decided to break post-sales technical support into a geographically located, team-based structure to reduce bottlenecks in day-to-day decision making.

We were lucky to have a knowledgeable and conscientious group of people on the team who relished the chance to specialize in the areas they preferred. This helped us maintain the same customer-focused mentality we’d cultivated over the years, whereby we saw our success (both as a team and a company) and that of our customers as effectively two sides of the same coin.

When you work with that kind of mentality, your efforts are more likely to make your customers happy:

The implementation support team is amazing. Any time we ran into a snag, they found a way out for us.

Mark Kaplan, BARBRI Director of IT.
Read the full case study here

Tracking success

Without having an effective way of tracking success, however, there’s no way of telling whether any team restructure is actually working. To make sure our team split was having the desired impact, we introduced a number of KPIs that would help us clearly measure the internal and external facets of the two functions.

• Are hiring and onboarding better?
  We defined “better” here as being easier/less time consuming to find candidates, match them to strongly defined roles, and onboarding time. We found that with our last round of expansion, all new team members were brought up to speed and could contribute exceptionally quickly (it also helped that they were a great bunch of people to begin with 💪!). This was quite a large expansion (roughly a 50% increase in headcount), so it had real potential to disrupt our output for a period of time. Thanks to the steps we’d taken, we managed to easily avoid this.

• Are we more efficient?
  The name of the game is to always improve efficiency. One of the KPIs we track is support agent-to-client ratio. This helps us identify whether we’re being efficient with the resources we have. Over time, we’ve moved the dial on that ratio from 1:8 to 1:15 while maintaining the same quality of customer support. We removed bottlenecks (“empowered”), shared information more effectively (“robust”), and – by increasing team specialization – reduced context switching (“scalable”).

• Are we maintaining output quality?
  To make sure we didn’t fall into the “efficient but not effective” trap (i.e. our numbers looked great but the quality of support deteriorated), we looked closely at quantitative information such as response times for support ticket requests; resolution times for informational or solution-focused queries; and times for escalating and resolving bugs. We also kept tabs on qualitative info – the anecdotal feedback we regularly receive from clients.

Planning for change is easier than predicting it

To restructure our customer support effectively we had to anticipate where we’d be as a company based on our current trajectory. That doesn’t mean we’re now future-proof, but we’re confident we’ve laid the groundwork for growth while maintaining and even improving on the high-quality support we’ve always offered our customers.

Feature image courtesy of Jason Leung|Unsplash.