Manager, Customer Analytics

What You’ll Do  

We are seeking a Manager of Data Analytics to enhance our customer insights function within a fast-growing SaaS payroll company. This role will be responsible for transforming data into actionable insights to drive improvement opportunities, improve customer retention, and drive upsell revenue. 

The ideal candidate combines strong technical expertise (SQL, data modeling, BI tools) with a deep understanding of SaaS metrics and customer lifecycle dynamics. This leader will build predictive models, define customer health scoring, and partner cross-functionally to drive measurable business impact. 

This role sits at the center of our growth strategy. By identifying why customers leave—and enabling the business to act early—you will directly impact retention, expansion, and long-term revenue. 

What Success Looks Like (First 6–12 Months) 

• A clear, trusted definition of churn and retention across the business 

• Improved early risk detection that leads to a reduction in churn 

• A production-ready churn prediction model with measurable lift 

• A standardized customer health score adopted by Customer Success 

• Executive dashboards that drive decisions, not just reporting 

Key Responsibilities 

Customer Churn & Retention Analytics 

• Identify and quantify key drivers of customer churn across segments 

• Build and maintain churn prediction models using behavioral, transactional, and engagement data 

• Conduct cohort and churned vs. retained analysis to uncover retention patterns and risk signals 

• Translate insights into clear, actionable recommendations for Customer Success, Product, and Sales teams 

Customer Health & Lifecycle Insights 

• Design and operationalize a scalable customer health scoring framework 

• Define leading indicators of customer risk and expansion opportunity 

• Partner with Customer Experience and Success and Operations teams to embed health scores into daily workflows 

Data Integration & Modeling 

• Integrate and model data across core systems: Salesforce, Genesys, Pendo, Qualtrics and Power BI 

• Build scalable data models to support self-service analytics and reporting 

• Ensure data accuracy, consistency, and governance across systems 

Reporting & Visualization 

• Develop executive-level dashboards that track churn, retention, LTV, and customer health 

• Move beyond descriptive reporting to diagnostic and predictive insights 

• Standardize KPI definitions across the organization 

Cross-Functional Leadership 

• Partner with Operations, Customer Experience/Success, Product, Sales, and Finance to align on metrics and insights 

• Influence strategy through data storytelling and business cases 

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