Symptom: North Star is vague or has no unit.
Cause: Defining the top metric in words only.
Fix: Add a one-sentence definition and unit (e.g. users, %, $). Set cadence (daily/weekly/monthly).
Technical SEO
Title, meta description, canonical, OG, Twitter, BreadcrumbList, FAQPage, WebApplication schema.
KPI Tree Builder (Free)
This tool is for product and business KPI trees and metric decomposition (mapping goals to KPIs and breaking a North Star into drivers), not org charts or decision trees. Build cause-effect trees with definitions, units, formulas, and a scenario calculator.
- Two modes: KPI Tree (Goal → Strategy → Tactics → KPIs) and Metric Tree (North Star → drivers with add/multiply/ratio). Tree and Grid views.
- Scenario calculator in Metric Tree: set leaf values, compute parents, sensitivity. Quality checks: definitions, units, orphans, depth/width, vanity.
- Import CSV, export CSV/MD/JSON/PNG/SVG, share URL, Print/PDF. Three loadable examples. No login.
No login. Autosave in browser. Shareable URL.
No login. Autosave in browser.
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Scenario calculator
Set leaf values; parents compute for add/multiply/ratio.
North Star
Root: —
Stakeholder summary (copy)
North Star definition, top drivers, what to monitor weekly.
CSV template: metric_id, metric_name, metric_type, definition, unit, direction, cadence, owner, data_source, baseline, target, notes, tags. Edges: from_metric_id, to_metric_id, relationship_type, weight, formula_notes.
How it works
- Choose mode: KPI Tree (Goal → Strategy → Tactics → KPIs) or Metric Tree (North Star → drivers with formulas). Add metrics and relationships (add/multiply/ratio). Toggle Tree or Grid view; use search and zoom.
- In Metric Tree mode, use the scenario calculator: set values for leaf metrics and see parent values computed. Run sensitivity (+10%) to see how the North Star moves. Use Quality checks for missing definitions, orphans, depth/width, and vanity metrics.
- Import CSV from the template, export CSV/MD/JSON/PNG/SVG, share URL, or Print/PDF. Autosave in browser. Load one of three examples (B2C app, B2B SaaS, Marketplace). Clear resets local state.
KPI tree vs metric decomposition tree
A KPI tree (Goal → Strategy → Tactics → KPIs) aligns high-level goals to actionable KPIs in a hierarchy. Use it when you need to cascade company or team goals. A metric decomposition tree (North Star → drivers → sub-drivers) breaks one top-level metric into drivers with mathematical relationships (add, multiply, ratio). Use it when you have a North Star and want to model how inputs drive it and run scenarios.
How to pick a North Star and define it properly
Choose one metric that best reflects product success for your stage (e.g. Weekly Active Users, revenue, or a quality index). Define it in one sentence with a clear unit (users, %, $) and cadence (daily/weekly/monthly). Avoid vanity metrics at the top: the North Star should be actionable and something the team can influence. Document the definition in the tree so stakeholders share the same meaning.
Leading vs lagging indicators
Lagging indicators measure outcomes after the fact (revenue, retention). Leading indicators predict or precede them (signup completion, feature adoption). Include at least one leading driver per path so you can act before lagging results are in. Tag leading metrics in the tree so weekly check-ins focus on the right signals.
Common patterns for decomposition (add, multiply, ratio)
Add: parent = sum of children (e.g. total sessions = session type A + type B). Multiply: parent = product (e.g. GMV = orders × AOV, or revenue = users × conversion × ARPU). Ratio: parent = one child divided by another (e.g. conversion rate = conversions / visitors). Use these when the relationship is quantitative so the scenario calculator can compute values. For qualitative or custom logic, use custom with formula notes.
Pro tips
- Pick one North Star and define it in one sentence with unit and cadence. Avoid vanity metrics at the top.
- Decompose with add/multiply/ratio where possible so the scenario calculator can run. Use custom + formula notes when the relationship is qualitative.
- Every metric must have definition, unit, and direction (higher_is_better / lower_is_better). The quality panel will flag missing fields.
- Keep tree depth under 5 and children per node under 8 so the tree stays readable and check-ins stay focused.
- Tag at least one leading indicator per path so stakeholders know what to watch before lagging results are in.
- Use Grid view to audit definitions and owners; use Tree view to present cause-effect and run scenarios.
- Import CSV from the template to bulk-edit metrics, then re-import or paste. Export CSV for planning tools and Markdown for stakeholder updates.
- Mark draft metrics so they are not flagged as orphans. Clear the draft flag when the metric is connected.
- Sensitivity (e.g. +10% on a leaf) shows how much the North Star moves. Use it to prioritize which drivers to improve first.
- Export PNG/SVG for slides; use Print/PDF for a one-pager. Stakeholder summary and metric dictionary are in the Markdown export.
Common mistakes
Symptom: Scenario calculator shows 'not computable'.
Cause: Edges use custom or mixed relationship types, or leaf values are missing.
Fix: Use add/multiply/ratio where the math applies. Enter values for leaf metrics and ensure one path is fully computable.
Symptom: Too many nodes; tree is unreadable.
Cause: Adding every possible metric.
Fix: Cap depth at 5 and children at 8. Merge similar drivers or move detail to the metric dictionary.
Symptom: Orphan nodes flagged.
Cause: Metrics not connected to the tree.
Fix: Connect each metric with an edge (parent → child) or mark as draft until placed.
Symptom: Leading vs lagging unclear.
Cause: All metrics are outcome-based.
Fix: Tag at least one leading indicator per branch (e.g. signup completion, feature adoption) that predicts the lagging result.
Symptom: Export PNG/SVG is clipped.
Cause: Tree is large or zoom is off.
Fix: Use Fit to screen before export. Ensure no node is placed at negative coordinates.
Symptom: Grid and tree get out of sync.
Cause: Editing in one view without the other updating.
Fix: Both views read the same state; edits in the side panel or grid update the tree. If not, refresh or re-load the example.
Symptom: Stakeholder summary is empty.
Cause: North Star or drivers not set.
Fix: Set the root metric and top drivers. The Markdown export builds the summary from the tree; add custom bullets in the export if needed.
FAQ
Is this for product KPI trees or org charts?
This tool is for product and business KPI trees and metric decomposition (mapping goals to KPIs and breaking down a North Star into drivers). It is not for org charts or decision trees. You build cause-effect and driver trees with definitions, units, and optional formulas.
What is the difference between KPI Tree and Metric Tree mode?
KPI Tree mode structures goals as Goal → Strategy → Tactics → KPIs. Metric Tree mode structures a North Star metric with drivers and sub-drivers and supports add/multiply/ratio formulas and a scenario calculator. Use KPI Tree for goal alignment; use Metric Tree for North Star decomposition and sensitivity.
How does the scenario calculator work?
In Metric Tree mode, enter values for leaf metrics (metrics with no children). The tool computes parent values when edges are add (sum), multiply (product), or ratio (e.g. A/B). Sensitivity shows how much the root changes if a leaf changes by a given percentage. Custom or mixed relationship types show as not computable.
What are leading vs lagging indicators?
Lagging indicators measure outcomes after the fact (e.g. revenue, retention). Leading indicators predict or precede them (e.g. signup completion, feature adoption). The quality panel encourages at least one leading driver per path. Tag metrics so stakeholders know what to monitor weekly.
Can I import my metrics from CSV?
Yes. Use the CSV template (metric_id, metric_name, metric_type, definition, unit, direction, cadence, owner, etc.). Optionally add a second sheet or file with from_metric_id, to_metric_id, relationship_type, weight, formula_notes for edges. Import loads metrics into the tree; add relationships in the builder or via the edges file.
Why does the quality panel flag orphans?
An orphan is a metric with no parent and no children—disconnected from the tree. Connect it with an edge to a parent or child, or mark it as draft until you place it. Orphans make the tree inconsistent and the stakeholder summary incomplete.
What export formats are available?
Export CSV (grid of metrics; edges optional), Markdown (stakeholder summary plus metric dictionary), JSON (full state for backup or integration), and PNG/SVG snapshot of the tree. Use Print or PDF from the browser for a one-pager. All exports are client-side; no data is sent to a server.
How do I add a relationship between two metrics?
Add an edge from the parent (the metric that is the result) to the child (the input). Choose relationship type: add (parent = sum of children), multiply (product), ratio (e.g. two children, parent = first/second), or custom with formula notes. Optional weight scales the child contribution for add.
Is the KPI Tree Builder free?
Yes. The tool is free, runs in your browser, and requires no login. You get two modes (KPI Tree and Metric Tree), tree and grid views, scenario calculator, quality checks, and CSV/MD/JSON/PNG/SVG export. Autosave uses local storage; shareable URL reconstructs your full tree.
What is the maximum tree size?
The tool is designed to support at least 300 metrics and 400 edges without noticeable lag in search and zoom. For very large trees, use search to jump to a metric and collapse branches to keep the view fast. Export and share work regardless of size.
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Last updated: 2026-03-05
- 2026-03-05: Launched KPI Tree Builder with KPI Tree and Metric Tree modes, tree/grid views, and scenario calculator.
- 2026-03-05: Quality checks: missing definition/unit/direction, orphans, depth/width, vanity, leading/lagging guidance.
- 2026-03-05: Export CSV/MD/JSON/PNG/SVG; shareable URL; 3 loadable examples (B2C, B2B, Marketplace).