How ChurnVision Works
From data upload to actionable retention playbooks—see how teams move through the ChurnVision workflow with smooth, privacy-first automation.
Local-first privacy
Model training and data processing stay on your machine. Nothing leaves without your approval.
Fast predictive insights
Go from raw HR spreadsheets to ranked risk lists and cohort trends in minutes, not weeks.
Actionable simulations
Experiment with Atlas interventions to see how salary, coaching, or training shifts change churn odds.
Automated data hygiene
Our pipelines normalize, clean, and validate your inputs so you can focus on decisions, not prep.
Step 1: Upload HR Data
Start by uploading your employee data in CSV or XLSX format. ChurnVision processes this data locally on your desktop—your information never leaves your machine during training. We provide a sample template to help you format your data correctly.
Required Fields
These fields are essential for basic churn prediction functionality.
- •HR Code (employee_id)
- •Full Name
- •Department
- •Position (role/title)
- •Employee Cost / Latest Performance Rating
- •Status
- •Manager ID
- •Tenure
- •Termination Date
Recommended Fields
These fields enhance prediction accuracy and provide deeper insights.
- •Tenure Start Date
- •Contract Type
- •Salary / Base Pay
- •Total Compensation
- •Performance Score
- •Engagement Score
- •Absenteeism Days
- •Promotion History
- •Team ID
- •Location / Site
- •Remote Status
- •Last Review Date
- •Disciplinary Actions
- •Training Hours
- •Overtime Hours
- •Commute Time
- •Satisfaction Survey Items
Step 2: Train Models Locally
Once your data is uploaded, ChurnVision trains prediction models directly on your desktop. Our optimized models and data pipelines ensure a typical first run completes in just a few minutes. System resource usage is lightweight—the training process runs efficiently in the background.
Local Processing
All model training happens on your machine. Your data never leaves your desktop, ensuring complete privacy and security.
Step 3: Review Predictions & Organizational Risk
StarterAfter training completes, you'll see employee-level risk scores with simple labels (Low, Medium, High), an organization-level risk snapshot with overall risk index and trend visualization, a team/department heatmap showing where risk is concentrated, and top risk drivers. Use these insights to prioritize follow-ups, explore specific teams, and export basic reports.
Employee-Level Risk Scores
Organization Risk Snapshot
Team/Department Heatmap
Engineering
Sales
Marketing
HR
What to do next:
- Prioritize follow-ups with high-risk employees
- Explore teams showing elevated risk patterns
- Export basic reports for stakeholder sharing
Step 4: Advanced Features
ProPro and Enterprise tiers unlock powerful capabilities: Explanations, AI Assistant, and Atlas simulations.
4A: Explanations
ProUnderstand why each employee is at risk. Explanations provide model-driven reason codes and feature attributions for individual employees and entire cohorts. See exactly which factors—compensation, manager relationship, workload, growth opportunities—are driving churn risk.
Example Explanation
Sarah Chen (High Risk: 87) — Risk drivers: Low engagement score (-35%), No promotion in 24 months (-28%), Below-market compensation (-22%), Recent manager change (-15%).
4B: AI Assistant
ProAsk targeted questions about any employee, team, or your entire organization. The AI Assistant pulls context from model outputs to provide precise answers, summaries, and actionable checklists. Get insights instantly without building complex queries.
AI Assistant
Analyzing your workforce data
More example questions:
- "What are the top 3 drivers of churn for engineers in the R&D department?"
- "Show me engagement trends for new hires over the last 6 months."
- "Compare retention risk between remote and on-site employees."
- "Generate a summary of high-risk employees who haven't been reviewed recently."
4C: Atlas Simulations
ProTest hypothetical actions before implementing them. Atlas lets you simulate interventions like salary adjustments, training programs, manager coaching, or schedule flexibility. Preview projected impact on churn over a 12-month horizon to make data-driven retention decisions.
Salary Adjustment
Increase base salary by 15%
Projected 12-month churn reduction: 42%
$45,000 annual
-38% average risk score
Capabilities by Tier
Starter
- Predictions + org risk overview
- Basic filters/exports
- Employee-level risk scores
- Team/department heatmap
Pro
- Everything in Starter, plus:
- Explanations (reason codes per employee)
- AI Assistant (ask questions)
- Atlas simulations (test interventions)
Enterprise
- Everything in Pro, plus:
- Advanced cohort explanations
- Priority AI Assistant access
- Extended Atlas simulation horizon
Ready to get started?
Join the waitlist to reserve your spot when the next onboarding cohort opens.