Can Metrics Tree model cohorts and retention curves?

Yes. Metrics Tree supports cohort creation, retention curves, retention impact on cohort totals, churn nodes, and simulation across days, weeks, months, and years.

Can I run what-if analysis?

Yes. Metrics Tree includes sensitivity analysis, goal seek, benchmark thresholds, and Monte Carlo simulation to explore uncertainty and identify key drivers.

Features

Model unit economics as a visual system, not a spreadsheet maze

Q: What makes Metrics Tree different from spreadsheets?

Metrics Tree makes metric dependencies visual and interactive. Product teams can connect KPIs as a graph, inspect drivers, simulate time-based changes, and explain results more clearly than in static spreadsheets.

Metrics Tree gives product managers, founders, growth teams and analysts a visual canvas to connect KPIs, simulate assumptions, and explain how changes in one metric propagate through revenue, conversion, retention and profitability.

Launch Metrics Tree Explore templates

Home / Features

Visual metric tree builder

Create metrics as draggable nodes and connect them with dependency types like contributes, numerator, denominator, multiplier and inverse. Show how KPIs are formed and explain the logic to stakeholders in minutes.

Source and churn simulation

Add source nodes for periodic inflows and churn nodes for decreases. Configure daily, weekly or monthly frequency and run the simulation over time to observe downstream impact on core product and revenue metrics.

Cohorts and retention curves

Enable cohorts for product metrics and connect a retention curve. Model how each new cohort decays over time while total value is calculated as the sum across active cohorts.

Retention curve editor with draggable control points
Cohorts breakdown table
Retention applied per cohort age

Cumulative and periodic metrics

Build cumulative metrics such as revenue, ad costs, GMV or gross margin. Configure update frequency (day/week/month) for more realistic subscription and billing simulations.

Driver Explain and Sensitivity Analysis

Understand what changed a metric on the last tick and which inputs move it most. This is especially useful for product reviews, growth planning and prioritization.

Driver share by impact
Sensitivity heatmap for top drivers
Validation hints for broken/incomplete formulas

Goal Seek and Monte Carlo

Reverse-plan targets like Revenue or ROI and estimate what driver values are needed. Run Monte Carlo scenarios using random ranges to inspect volatility and P50/P90 outcomes.

Built for PM and growth workflows

Metrics Tree combines exploratory modeling with presentation-ready visuals. Teams can use it to align on KPI definitions, communicate tradeoffs, and test scenario assumptions before building dashboards or launching experiments.

Feature FAQ

What makes Metrics Tree different from spreadsheets?

It makes the dependency graph visible. You can see which upstream metrics affect a result, inspect lines and nodes on canvas, and communicate assumptions visually to non-analysts.

Can I model retention and churn together?

Yes. Use retention curves for cohort-based persistence and churn nodes for absolute or relative decreases. Both can be used in the same simulation graph.

Can I save and share my setups?

You can use Local Storage as a guest or sign in to save cloud projects. Admin-only data connector features are gated and hidden from regular users until fully released.