ds@mcpanalytics.aiA data scientist you can email your data and question to, and get a reliable response. Not AI slop.A data scientist you can email. Not AI slop.
Upload a CSV with a duration, an event flag, and a group. Get Kaplan-Meier curves, median time-to-event with confidence intervals, a log-rank test, and Cox hazard ratios — with censoring handled properly. Free.
Free analyses run on up to 10,000 rows. Larger files are randomly sampled to that size, so sign up to analyze your full dataset.
Estimating survival curves...
Sent to . Inside: Kaplan-Meier curves per group, median time-to-event table, log-rank and Cox hazard ratios, event-timing histogram, R code, and AI insights.
Analyze another fileThe practical guide behind this tool: when it applies, how to read the output, and the traps that make it say the wrong thing.
Real data, the R Markdown that produced every figure, and the numbers checked three ways.
Download it and re-run it yourself: this is what an answer looks like when someone asks you to prove it.
The analysis builds a Kaplan-Meier survival curve for each group — the correct estimate of the fraction still event-free over time when some subjects are censored (still active at last observation). It reports each group's median time-to-event with a 95% confidence interval, runs a log-rank test of whether the curves genuinely differ, and fits a Cox proportional-hazards model to express each group's risk as a hazard ratio versus the largest group — 'this group reaches the event 1.8 times faster.'
Use it whenever the question is 'how long until X happens' and some subjects haven't had the event yet — churn, failure, relapse, conversion, time-to-hire.
Not for data where every subject's event time is fully observed and you only want mean differences (use a group comparison tool), and not for repeated events per subject or time-varying group membership.
Built for: Analysts, product and CX teams, reliability engineers, and researchers working with duration or retention data
Typical data source: Any spreadsheet or CSV with a duration column, an event/churned/failed flag, and a segment column
One duration column, one event flag, one group. For example, customer retention by plan:
Minimum 30 rows · Best with 100-50,000 rows and 1-6 groups
Standard-library analysis: how long until customers churn, machines fail, or patients relapse — with censoring handled properly. Kaplan-Meier survival curves per group, median time-to-event with confidence intervals, a log-rank test of whether the groups truly differ, and Cox hazard ratios that say how much faster one group reaches the event than another. Works on any duration data: map a time column, an event flag, and a group.
Each group's percentage still event-free over time — the curve that drops fastest is the group that churns or fails soonest.
Each group's median time-to-event with a confidence interval; 'not reached' means most of the group was still active at last observation.
The log-rank verdict on whether the curves truly differ, plus a hazard ratio per group saying how much faster it reaches the event than the reference.
When the observed events actually happened — whether risk concentrates early or spreads out over the whole timeline.
Plain-English interpretation of what the numbers mean, what's significant, and what to do next.
How long until my customers churn?
Map months-active as time, a churned yes/no flag as event, and the plan as group. You get retention curves per plan, median lifetime with confidence intervals, and a hazard ratio saying how much faster one plan's customers leave.
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
Run any analysis on your own data: R analyses, interactive reports, AI insights, and PDF export.
Try Free, No Credit CardYour turn
Bring your own data and the question you actually need answered.
CympleData Scientist Send me your data and question, I’ll send you the analytics. ds@mcpanalytics.ai
Tell us what went wrong, in your own words. We capture the page you're on automatically, so no need to describe where you are.