Nurturing client relationships is an essential part of any customer success role, and the ability to utilize data can make a huge difference when deciding where to direct company time and effort — and how to prevent customers from churning. However, raw data is only as useful as the personal touch added to it.
When it comes to leveraging personal touch and data, Flash might have the answer. Jeff Johnson, chief customer officer at the parking and transportation company, uses data to inform his team when personal interaction is needed to nurture a client relationship. “If our technology and platform are being optimized, we can forecast strong retention percentages,” he said. “However, I believe that active engagement is always the best lead indicator for retention or potential churn.”
If step one is using data to identify customer red flags and step two is personalizing the re-engagement approach, how do companies ensure their process is a well-oiled machine? Built In Austin spoke further with Johnson about how he nurtures data with a personal touch to minimize churn and encourage customer re-engagement and happiness.
What are the key metrics you track when it comes to your customers?
Our team has a few internal key performance indicators (KPIs) that we view as lead and lag measures in effectively monitoring our customer base. Our first and probably most important lead relates to engagement and maintaining a cadence of communication with our partners. We conduct monthly business reviews (MBRs) and expect a 90 percent compliance rate with this rhythm. Effective communication allows us to identify opportunities to optimize our performance and leverage our platform, driving value for our customers. Each of these opportunities relates to growth, support or friction.
Once identified, we track our progress towards resolution and measure a mean time to recovery, which is the second lead indicator for our CS team. Our first lag indicator relates to platform adoption as measured by how much additional revenue we’re creating for our customers. If their business is growing with the support of our technology, we know we’re driving value. Finally, we solicit an NPS once a year, which is a lag indicator that works as a lead indicator for retention percentage and referrals.
Which metrics do you prioritize when identifying accounts that might be in danger of churning?
Aside from the internal KPIs above, we also identify and track a range of KPIs and a true north metric more specific to each customer. We always prioritize these measures when preparing for and conducting MBRs.
While we might have a range of KPIs that we follow, retention and churn are ultimately relationship decisions. That is generally best measured by a customer’s willingness to rhythmically sit down, engage and have a conversation about their business outcomes. Furthermore, we look for engagement between reviews as we track our caseload towards resolution. If we get a strong collaborative effort as we move support, growth and friction opportunities forward, we can feel pretty comfortable that the relationship is stable and strong.
While we might have a range of KPIs that we follow, retention and churn are ultimately relationship decisions.”
How have you used this data to tailor your re-engagement strategy?
There are times when a customer’s own internal priorities and complexities make it difficult to commit to MBRs and we see that in our data. When this happens, we have to determine a path forward to ensure we’re still communicating progress and providing important updates. We recently created a virtual MBR deck delivered via email for one of our most strategic partners purely out of necessity and respect for their business dynamics. It was well-received and resulted in an active dialogue amongst some additional executives that would have been included in the actual MBR. In this instance, our strategy and approach worked, but we always have a bias towards in-person delivery, with virtual delivery being our second preference and only using an emailed MBR deck as a last resort.
