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← Statistics glossary

metric tree

Also called: driver tree, KPI tree, metrics tree, metric decomposition

A breakdown of a top metric into the input metrics that drive it, so each team can see which lever it moves.

A metric tree starts from one top metric (a north star or a revenue line) and splits it, level by level, into the input metrics that produce it, until each leaf is something a team can act on directly. It answers two questions: "what should my team move?" and "why did the top number change?".

There are two ways to split a node, and a good tree uses both:

  • Multiplicative: a rate chain, where the top equals the product of its factors. For subscription revenue:

New Plus revenue=MAU×paywall viewersMAU×trialspaywall viewers×paidtrials×price\text{New Plus revenue} = \text{MAU} \times \frac{\text{paywall viewers}}{\text{MAU}} \times \frac{\text{trials}}{\text{paywall viewers}} \times \frac{\text{paid}}{\text{trials}} \times \text{price}

  • Additive: a sum of parts, such as revenue = monthly plans + yearly plans, or active groups = flats + couples + trips + other.

To build one, write the top metric's exact definition, split it so the parts multiply or add back exactly to the parent, stop when a leaf has a clear owner and can move within weeks, and note which leaves you can actually measure today. A tree whose parts don't reconcile with the top is a mind map, not a metric tree.

The tree earns its keep in diagnosis. When the top metric moves, compare each factor period over period: in a multiplicative tree the relative changes multiply, so you can see which factor explains the move instead of arguing about it. It also shows trade-offs: pushing one leaf (more paywall views) can pull down the next (a lower trial rate).

Example

Halves tracks new Plus revenue from first monthly payments (monthly plan, $5). Maya sees it fall from May to June while MAU grows, and walks down the tree:

Factor
May
June
Change
MAU
40,000
45,000
×1.125
Saw the paywall (share of MAU)
8% → 3,200
8% → 3,600
×1.00
Started a trial (share of viewers)
6.25% → 200
5% → 180
×0.80
Paid after the trial
40% → 80
40% → 72
×1.00
Price
$5
$5
×1.00
New Plus revenue
80 × $5 = $400
72 × $5 = $360
×0.90

Check: 1.125 × 1.00 × 0.80 × 1.00 × 1.00 = 0.90, i.e. revenue −10%, matching $360 / $400.

Everything else held or grew, so the whole drop sits in one leaf: the trial start rate fell by a fifth (5% / 6.25% = 0.80). That points the investigation at the paywall screen itself (a new design shipped on 3 June) rather than at marketing, which actually did its job.

Common mistakes

  • Parts that don't reconcile. If the factors don't multiply or add back to the top metric, the tree can't explain any change.
  • Leaves nobody owns. A leaf without a team or a lever is decoration; keep splitting or merge it.
  • Mixing denominators. "Trial rate" must be trials per paywall viewer at every level, not sometimes per MAU.
  • Ignoring links between leaves. Pushing more users to the paywall often lowers the trial rate; read neighboring factors together.
  • Too deep, too early. Twenty leaves you can't measure are worse than five you can; grow the tree as tracking improves.