value-metric-design

Skill: Value-Metric Design

The value metric is what you charge per. It is the highest-leverage decision in pricing — a right metric makes expansion automatic; a wrong one caps the company forever. Decide it before the number.

Step 0 — The three tests every value metric must pass

A strong value metric is simultaneously:

1. Value-aligned — it tracks the value the customer captures (not your cost).
2. Expanding — it grows as the customer becomes more successful (so expansion is automatic, not a re-sell).
3. Predictable — the customer can forecast and budget it (no bill shock).

These trade off. The most value-aligned metric is often the least predictable.

Step 1 — Enumerate candidate metrics

List every plausible per-unit: seats, active users, API calls, GB stored/processed, records/contacts, transactions, monetary volume processed, outcomes (resolved tickets, qualified leads), workspaces/projects. Don't pre-filter yet.

Step 2 — Score each candidate through the tree

Run each candidate through ../../knowledge/pricing-decision-trees.md §2. Reject cost proxies. Flag the bill-shock risks. Note which metrics the customer can game down (e.g. deactivating "active users") — those leak revenue.

Step 3 — Resolve the alignment-vs-predictability tension

The usual resolution: a steady metric for the base + a value-aligned metric for expansion. E.g. price the platform on seats/workspaces (predictable) and the consumption on usage (aligned) — the hybrid pattern. Don't force one metric to do both jobs if they conflict.

Step 4 — Run the failure question

"If this product becomes 10× more valuable, does our revenue grow with it?" A metric that answers no caps the business — discard it however convenient it is to bill.

Step 5 — Validate, then set tiers

Hand the chosen metric to willingness-to-pay-research to find the price points, then to packaging-and-tiering to fence the tiers along the metric.

Output

A value-metric recommendation with: each candidate's three-test score, the gaming/bill-shock risks, how the alignment-vs-predictability tension was resolved, and the failure-question result. Name the one metric (or the base+expansion pair) you'd bet the business on.