Services
Customer Success
Customer Engagement Health Audit
Assess how actively your customers engage with your product and team to identify who's healthy and who's at risk.
Foundation
The accounts that surprise you with churn usually weren't silent. They were sending signals for 60 to 90 days before they cancelled. The engagement health audit builds a model that reads those signals systematically across your full book of business, not just the accounts your CS team happened to be watching. The goal is to replace reactive churn management with a system that tells you which accounts need attention before they express dissatisfaction.
Accounts that are about to churn usually show warning signs for 60 to 90 days before they actually cancel. They stop opening emails. Their usage drops. Their champion goes quiet. They stop responding to QBR invitations. When you look back at the data after a churn event, the signals were there. The problem is that nobody was watching.
Most CS teams manage account health through a combination of intuition, QBR cadence, and whatever the CSM happens to notice in their daily work. That works for the accounts CSMs have time to pay attention to. It fails for everyone else, which in most companies is the majority of the book of business.
What we do
We build a health scoring model from your actual account data: product usage patterns, email engagement, support ticket frequency and sentiment, QBR participation rates, and CRM activity logs. We validate the model against historical churn data to confirm which signals actually predict disengagement.
We also analyze your current CS coverage model to identify which accounts are receiving attention and which are invisible until something goes wrong.
For context on what this type of analysis typically surfaces, read what engagement patterns predict churn months in advance.
Deliverable
A customer engagement health model with validated scoring criteria, a health score for every current account, a coverage gap analysis showing which at-risk accounts are underserved, and intervention playbooks for different health score levels.
Outcome
CS teams that see risk coming instead of reacting to it. Interventions that happen while there's still time to change the outcome. A health model that improves over time as more data accumulates.
How Stratum Group Cut Reporting Time by 50% and Detected Churn 60 Days Earlier — cut decision time by 50% and started detecting churn 60 days earlier.
See how it worked in practice: Harbor Group reduced churn by 34%.
Best Fit
For CS teams managing more accounts than they can give individual attention to, where churn keeps surprising them. Also appropriate before building any automated health scoring in your CRM or CS platform, since the model needs to be validated against your specific data before it gets automated.