You Can’t Manage What You Don’t Measure: Using Data to Minimize Churn

Leveraging data may be the difference between retaining a customer and watching them walk away.
Written by Rachael Millanta
February 9, 2022Updated: February 9, 2022

For a moment, imagine being able to prevent a customer from leaving before they’ve even made the decision to go. It’s a fantasy that two Chicago tech companies are interested in making a reality. 

According to UserIQ’s 2019 Benchmarking Report, 67 percent of the companies whose customer issues were “always resolved” reported a churn rate of under 10 percent. With more tech companies and platform options available to customers than ever before, minimizing churn should be a top priority across the industry.

But what if you could anticipate customer issues and prevent churn by leveraging key data and metrics?

“Our ability to re-engage clients always comes back to the why,” said Ethan Abrams, an enterprise strategic team lead at Braze. “The why, combined with a data-driven approach, allows our customer success team to get ahead of potential churn and increase our stickiness with the client.”

Alex Manich, manager of customer adoption at Buildout, agreed that understanding clients through data is essential. “Because we have a data monitoring tool, we have the ability to identify our key contacts or stakeholders at a company, as well as when those stakeholders leave or change.”

With the goals of minimizing churn and staying “sticky” in mind, finding the right metrics to measure the wants, needs and red flags of customers is important. Built in Chicago spoke further to Abrams and Manich to learn about the specific metrics they track — and how it’s led to happier customers.

 

Ethan Abrams
Enterprise Strategic Team Lead • Braze

 

What are the key metrics you track when it comes to your customers?

It’s imperative that our customer success team has a pulse on how our customers are using Braze — both for accurate revenue and headcount forecasting. There are many elements that go into tracking this pulse and they land in either the quantitative or qualitative bucket. 

For quantitative metrics, NPS scores provide direct and immediate feedback as to how a specific end user feels about the platform and service. Though they often cannot provide the reason for their score, the data does allow our team to trigger additional actions based on whether they are a detractor, neutral or promoter.

For qualitative metrics, the CSM sentiment score is an input we rely on to get a qualitative view on how the CSM feels about the relationship with their client and their likelihood to renew with us at a given point in time. The score ensures we are taking a step back to evaluate our customer relationship at a consistent cadence and helps identify areas of opportunity or risk that we need to act on.

 

Which metrics do you prioritize when identifying accounts that might be in danger of churning?

There are many inputs that go into identifying accounts that might be in danger of churning. These inputs currently roll up into the classifications of customer engagement, platform value, business health and consumption. Certain key metrics we prioritize are the account’s product usage pacing, number of technical support tickets submitted and which features of the platform they are utilizing. From there, we focus on those areas with the highest impact on our overall business, prioritizing accounts that have the highest current contract value and those that will have the largest opportunity for growth down the line. These are not purely automated quantitative reports and intentionally include a level of subjectivity.

Our ability to re-engage clients comes from truly understanding their needs and goals, and it always comes back to the why.”

 

How have you used this data to tailor your re-engagement strategy?

Consumption is often a major factor when it comes to growing the overall business. The CS ops team has built automated notifications that are sent to the CSM and customer success leadership at key points in a contract if the client is over or under-pacing. These alerts kick off internal conversations with the entire cross-departmental account team to find ways to re-engage and bring additional value to the client. Our ability to re-engage clients comes from truly understanding their needs and goals, and it always comes back to the why. Why are they under-pacing? Are there internal factors? External headwinds? The why, combined with a data-driven approach, allows our customer success team to get ahead of potential churn and increase our stickiness with the client. 

 

 

Alex Manich (he/him/his)
Manager, Customer Adoption • Buildout, Inc.

 

What are the key metrics you track when it comes to your customers?

We use a tool called Totango to track our customer behaviors and monitor customer health based on those behaviors. Some of those metrics are things you would expect, like the total number of active users, license utilization and number of active days, but we also wanted to make sure we’re creating custom metrics that really capture whether our customers are getting value from Buildout.

We work closely with teams across the company to ensure that we really understand what our ideal customer looks like. One of the areas we focus on is the relationships between different user behaviors. An example of this is Buildout’s marketing software that automates document creation for our commercial real estate partners. We understood that an ideal customer would be creating at least one document for every listing that they added to the tool. Because we have both of those data points, we’re able to create a custom metric looking at that ratio and build it into our health profiles.

We work closely with teams across the company to ensure that we really understand what our ideal customer looks like.”

 

Which metrics do you prioritize when identifying accounts that might be in danger of churning?

The above-mentioned document-to-listing ratio is a very important and reliable indicator of churn. Tools like Totango allow us to not just track that value, but also changes in that value over time. Additionally, because we have a data monitoring tool, we have the ability to identify our key contacts or stakeholders at a company, as well as when those stakeholders leave or change. All of these metrics in combination influence our real-time health monitoring.

 

How have you used this data to tailor your re-engagement strategy?

We’ve implemented a number of different playbooks that trigger automatically when certain criteria is met. Our CSMs are notified of lost champions in real time and are immediately given a playbook of tasks to identify a new champion, train them and monitor their long term usage. Any account that falls into this category becomes high-touch until we’re convinced we’ve adequately mitigated the risk.

Any client of ours that has two consecutive weeks of poor health will also trigger a playbook for high-touch outreach. Ideally, we’d like to see this deployed less and less as we continue to leverage our data to reduce risk prior to an account falling to red health.

 

 

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