AI Agent Retention & Churn Cost Calculator
Estimate how much customer churn, support surge, and reactivation spend cost when an AI agent delivers bad experiences.
Scenario presets
Retention inputs
Estimates are directional. Last updated: 2026-07-08. See notes.
Monthly agent-attributed churn cost
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Churned users / month
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Cost per failed session
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Projected period cost
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Lost MRR / month
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Lost gross margin / month
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Lost LTV / month
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Support surge cost / month
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Reactivation cost / month
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Goodwill / refunds / month
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Monthly cost breakdown
| Cost line | Monthly | Share |
|---|---|---|
| Lost gross margin from churn | — | — |
| Support surge | — | — |
| Reactivation campaigns | — | — |
| Goodwill / refunds | — | — |
| Maintenance labor | — | — |
Sensitivity: failure rate vs monthly churn cost
| Failure rate | Monthly churn cost | Churned users / mo | vs current |
|---|---|---|---|
| — | |||
Verdict
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Frequently asked questions
What does this calculator estimate?
It estimates the monthly cost of AI-agent-driven churn: lost MRR, lost LTV, extra support tickets, reactivation campaigns, goodwill credits, and ongoing maintenance. It also shows what happens if you reduce the failure rate.
How is agent-attributed churn calculated?
We estimate failed sessions per month, then apply a churn-likelihood percentage to users who experienced at least one failure. This is added to the baseline monthly churn to show the incremental churn likely caused by agent failures.
What counts as an agent failure?
Any session that ends with a wrong answer, harmful output, escalation, or user-reported dissatisfaction. Use your own support-survey or escalation rate as the failure percentage.
Does this include baseline churn?
Yes, we separate baseline churn (users who would leave anyway) from incremental churn attributed to agent failures. The headline cost is the incremental portion.
Why do I need MRR and LTV?
MRR gives the immediate monthly revenue lost. LTV shows the total long-term value destroyed when a customer churns. Both are needed for a complete business-case view.
How can I use the sensitivity table?
It shows how churn cost changes at different failure rates. Use it to justify investment in prompt engineering, guardrails, human review, or a better model.
Estimates are directional. Churn attribution is probabilistic: not every bad experience leads to churn, so we model a churn-likelihood multiplier based on the number of failed agent sessions a user sees.