For customer success managers, reliable data is like a good pair of glasses. It can bring fuzzy elements of the client experience into sharp focus.
The team at RealWork Labs experienced this illuminative impact firsthand after data revealed that their mobile platform was being inconsistently adopted by the home service professionals employed by their clients. The customer success team responded swiftly, designing an eight-week program to encourage and enable field technicians’ participation.
“Within weeks, we witnessed higher usage rates of these technicians,” said Micah Kasdan, VP of customer success. “These insights and data inform each phase of the customer journey moving forward.”
RealWork Labs is one of three Austin-based companies dedicated to using data to accurately monitor account health. Buoyed by actionable insights, these customer success managers are better able to address their clients’ needs and proactively work to ensure contract renewals.
They have valuable advice to share for customer success professionals hoping to leverage data to nurture long-lasting client relationships.
Transportation logistics company project44 provides real-time supply chain visibility that goes beyond shipping tracking.
What are the key metrics that project44 uses to track its customers?
We excel at tying complex supply chain data together into concise metrics for our customers. The North Star metric for customer success managers at project44 is consumption. Our consumption metric measures the percentage of shipments tracking relative to our customers’ annual contracted volume.
We are committed to obsessing over our customers and delivering value; driving consumption allows us to do just that.
We are committed to obsessing over our customers and delivering value; driving consumption allows us to do just that.”
Which metrics do you prioritize when identifying accounts that might be in danger of churning?
In order to delight and surprise our customers at every step of our partnership, the number one data set we actively review is their qualitative feedback. Quantitatively, we look at different customer engagement metrics, including the frequency of users logging into our platform, the volume of shipments being initialized month over month and trends in consumption percentages.
These metrics give us a valuable pulse check on account stickiness and overall health. The last piece of the churn puzzle is monitoring our customers’ satisfaction with our product. Here, we look at the number of open support and engineering tickets, along with the recorded resolution times, as strong indicators of our team meeting their support needs.
Together, project44 customer success managers work to find solutions, ensure customers are being heard and brainstorm ways to enable our customers to get the most out of their partnership with project44 and our products.
Ultimately, customers are delighted when shipments are tracking properly and any bottlenecks that come up are solved expeditiously. We help facilitate this by getting the right information to our customers before they even know they need it.
Give an example of how you used this data to tailor your re-engagement strategy or improve customer relationships.
We are continuously reviewing consumption data with our customers, at which point we explore the quality of the data being pushed by each carrier, the party that is transporting the customer’s goods. To showcase the insights from this data for our customers, we build carrier scorecards and root cause analysis dashboards. These products integrate and present large amounts of tracking data from many different carriers.
During a recent customer review session, my team used data from those products to explain the carrier discrepancies in their network. Using the intel gauged from our product, we were able to relay to our customer that the issues stemmed from carrier communication errors, such as API connectivity issues, invalid telematics details and other output errors from their transportation management system.
Our analysis enabled the customer to lead tactical, data-driven conversations with these carriers directly, allowing the carriers to make necessary adjustments. Over the subsequent few weeks, we noticed the quality of the data coming in from these carriers significantly improved, which therefore enhanced our customer’s consumption metrics and overall experience.
General contractors, plumbers and other home service professionals use RealWork Labs’ mobile platform to communicate with customers and generate new business.
What are the key metrics that RealWork Labs uses to track its customers?
At RealWork Labs, we are heavily focused on two types of metrics: app usage and key customer events. As an early-stage tech company, we have the luxury of staying laser-focused on user adoption. This is easily measured with a finite number of key indicators.
At our core, our platform creates a flywheel effect, leveraging job site posts (our customers’ stories) and online reviews (their customers’ opinions). When these activities are maintained, we help drive business growth for our accounts, which creates further stories and reviews. Wash, rinse, repeat.
Knowing these simple dependencies, we are able to define our key performance indicators. Once we map the customer journey, our leading and lagging indicators become clear. Our team guides each customer through a measured onboarding experience. We have actionable usage metrics from our customers in week one, allowing our team to focus the appropriate attention on each individual account.
We have actionable usage metrics from our customers in week one, allowing our team to focus the appropriate attention on each individual account.”
Which metrics do you prioritize when identifying accounts that might be in danger of churning?
Because we know how user activity impacts our return on investment, we know the key metrics of accounts that pose the highest churn risk. Customer-generated content and their customers’ online reviews are the strongest indicators. Our most engaged accounts generate the most usage events, which generates consistent ROI.
In working with our business intelligence team, we have been able to correlate an ideal amount of weekly user activities associated with our longest and stickiest relationships. This makes it easier to identify accounts that are at higher risk with relative ease. It also informs the goals we set for the customer success team. When we are successfully consultative, we help customers achieve the best outcomes.
Give an example of how you used this data to tailor your re-engagement strategy or improve customer relationships.
When we explore individual accounts with risky indicators, there is almost always a correlation with buy-in that diminishes over time. This is why we are currently focused on improving our customer onboarding experience.
Like many startups, we are solving an old customer problem with a new solution. This means that we need customers to understand the solution as well as the importance of their own contributions toward it.
In the past, our team focused the majority of its attention on the business owners who signed the initial contracts. We have a lot of small and medium-sized business profile accounts, so it is expected that owners will be heavily involved in platform usage. We started to see data indicating that field technicians who worked for our customers were adopting product usage at inconsistent rates.
In addition to building strong initial relationships with the owners, we now run an eight-week program designed to encourage and enable field technicians’ participation. We report progress to the owners across this phase to keep everyone engaged and active. Within weeks, we witnessed higher usage rates of these technicians. These insights and data inform each phase of the customer journey moving forward.
Dealerware operates a SaaS platform for automotive dealerships and manufacturers.
What are the key metrics that Dealerware uses to track its customers?
We track the health of our customers in two ways. The first is through a net promoter score survey that is sent on a rolling basis to users twice a year through our web application. These responses indicate overall user satisfaction with our product and help inform our product roadmap. Monthly, we review responses with our product team, which allows them to incorporate that feedback directly into their planning strategy.
The second way we track customer health is through an internal score combining weighted key metrics divided into four categories: onboarding, usage, support and sentiment. Within those categories, we track metrics including customer effort score, 30- and 60-day health check-ins, change in vehicle volume (we’re in automotive fleet management), change in contract creation, ticket volume and ticket frequency.
We also employ a product analytics tool to capture usage and behaviors that factor into the customer’s overall health. Combined, we have a constant pulse check on customer health and product sentiment within the first few months of usage.
We have a constant pulse check on customer health and product sentiment within the first few months of usage.”
Which metrics do you prioritize when identifying accounts that might be in danger of churning?
Every quarter, as a part of strategic planning with our account management team, we review health and discuss trends, metrics and outcomes to inform whether or not we are tracking and acting on the right data to help prevent churn and increase customer satisfaction.
Through those conversations and analyses, we’ve landed on three primary risk indicators. The first indicator is active users. Are users logging into our platform on a regular basis? How many and how frequently? The second is the percent change in a user’s “vehicles under management.” If we see vehicle counts reducing at a rapid pace, that’s an indication they are actively exiting our platform or experiencing their own business challenges.
Our last indicator is based on our personal relationship and experience with the customer. If the customer expresses concern, frustration or product fit issues, any member of the customer success team can manually tag their account with a “risk” tag. Tagging the account as a known risk immediately triggers internal action from our account management team to run a churn mitigation playbook.
Give an example of how you used this data to tailor your re-engagement strategy or improve customer relationships.
The data we capture in our 30- and 60-day check-ins is vital to engaging at-risk customers early in their Dealerware journey. Each user receives a survey asking, “Are you enjoying using Dealerware?” A simple “thumbs up” or “thumbs down” response allows us to take action immediately.
If a user selects “thumbs down,” then we consider them an at-risk account. The survey data is fed back into our customer success platform, which triggers a call to action for our implementation manager to intervene as we strive to deliver a positive initial experience.
In addition, we automatically send an email to the customer, personalized from our implementation manager, probing into their dissatisfaction and offering solutions and additional training. The implementation manager will then follow up and schedule any calls needed to make sure the customer risk is addressed.
This combination of automated and manual intervention has been successful in addressing churn risks.
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