Metric Catalog & Taxonomy — Starter Kit

A practical, interactive starter kit: clear naming conventions, a reusable calculation-spec form you can submit into a shared catalog, governance checklist, rollout pattern, and an 8-metric example catalog to help teams name, define, and link metrics to outcomes and owners.

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Metric Catalog & Taxonomy — Starter Kit

Welcome — Why a Metric Catalog Matters

If multiple teams measure the same idea differently, people argue about numbers instead of improving outcomes. A lightweight, shared metric catalog prevents that by making definitions, owners, calculations, and expected signals explicit. This starter kit helps you stop metric proliferation, align measures to outcomes, and create clear ownership so your organization can act with confidence.

What this Starter Kit Gives You

  • Simple naming conventions and taxonomy to reduce duplicate metrics.
  • Clear metric types (north-star, leading, lagging) and when to use each.
  • An owner map pattern so every metric has a responsible steward.
  • An interactive calculation-spec form you can copy or submit to a central catalog.
  • An example catalog with 8 practical metrics across product, ops, sales, and support.
  • Governance checklist and rollout tips to keep the catalog healthy.

Start with a Hunger — Link Each Metric to an Outcome

Every metric in the catalog should answer: what decision or outcome does this support? Capture that connection in one sentence next to each metric. When a number changes, the team should be able to explain which decision or customer outcome it informs.

Naming Conventions & Taxonomy (Make duplication hard)

Use a predictable, human-friendly key for each metric. Consistency makes searching and governance easier.

  1. Structure: domain.component.metric_name_unit
    Example: product.activation_rate_pct or ops.mttr_minutes
  2. Lowercase and underscores: product_feature_xxx not ProductFeatureX.
  3. Include unit only when helpful: append _pct, _minutes, _count, _usd.
  4. Avoid synonyms in names: pick canonical words (use 'conversion' not both 'signup_rate' and 'conversion').

Keep a short tag set for the domain: product, ops, sales, support, finance, marketing. Use those as the first token to group metrics.

Metric Types — Choose the Right Signal

  • North-star: the primary outcome-oriented measure you want to maximize over time (strategic).
  • Leading: early indicators that predict future north-star movement (actionable).
  • Lagging: outcome or result measures that confirm impact after the fact (diagnostic).

Prefer a small set of north-stars (1–3) and several leading indicators teams can act on quickly.

Metric Owner Map (Who looks after the metric?)

Assign at least one Owner (primary responsible) and one Steward (data/technical contact). Optionally include Interested Parties for visibility.

Owner responsibilities:

  • Ensure the metric definition remains correct.
  • Lead reviews each cadence (weekly/biweekly/monthly depending on cadence).
  • Propose changes and communicate impacts to stakeholders.

Calculation Spec Template (use the interactive form below)

Use consistent fields so anyone can reproduce the value. Below the guidance you'll find an interactive form where you can draft and submit a metric entry to your catalog. If you prefer working offline first, copy these fields into a document and then paste them into the form.

Example Catalog — 8 Practical Metrics

Below are example entries you can adapt. Each row shows the key, type, brief definition, owner, and outcome link.

Key Type Display Owner Outcome Link
product.daily_active_users_count North-star Daily Active Users (DAU) Head of Product Indicator of product engagement and monetization opportunity
product.feature_adoption_pct Leading Feature adoption (%) Product Manager Predicts retention if adoption increases
ops.mttr_minutes Lagging Mean Time to Repair (minutes) Ops Manager Reflects operational reliability and customer impact
ops.change_failure_rate_pct Lagging Change failure rate (%) Release Engineer Shows release quality and risk to uptime
sales.conversion_rate_pct Leading Sales conversion (%) Sales Manager Early signal for revenue pipeline health
sales.avg_deal_size_usd Lagging Average deal size (USD) Sales Ops Measures revenue quality and targeting effectiveness
support.first_response_minutes Leading First response time (minutes) Support Manager Better response predicts higher customer satisfaction
support.nps_score Lagging Net Promoter Score Head of Support Outcome measure of customer loyalty and referral likelihood

Governance & Lifecycle — Keep the Catalog Healthy

  1. Adopt a review cadence: monthly for operational metrics, quarterly for strategic metrics.
  2. Change process: proposed edits submit a short rationale and expected impact; owner triages and schedules changes for the next review.
  3. Archive rather than delete: keep historical definitions with effective dates to avoid calculation surprises.
  4. Publish a canonical CSV or small web page and ensure dashboards reference the catalog keys (not ad-hoc SQL names).

Common Pitfalls & How to Avoid Them

  • Too many metrics: teams track everything. Limit dashboards to the few signals that support current decisions.
  • Overloading north-stars: a north-star should be outcome-focused, not a proxy for vanity metrics.
  • Undefined calculations: undocumented SQL or ETL transformations cause disputes. Use the interactive Calculation Spec fields.
  • No owner: metrics without owners drift or become stale. Assign a primary owner and a data steward.

How to Roll This Out (Practical Steps)

  1. Pick a pilot: select 2–3 teams and import their top metrics into the interactive catalog using the form below.
  2. Run a short alignment workshop: confirm definitions, identify duplicates, assign owners.
  3. Publish the catalog and update one dashboard to use canonical keys. Validate values with owners for two cycles.
  4. Expand gradually and add governance once the pilot succeeds.

Next Improvements — Where interactivity helps

Converting metric definitions into a structured, savable catalog enables search, lineage, owner notifications, workload tracking, and programmatic dashboard integration. Below you can draft a definition and submit it. Platform capabilities can later support bulk import, CSV export, and automated linkage to dashboards and metric lineage.

Quick Checklist Before You Finish

  • Does each metric have a single canonical key and clear owner?
  • Is the calculation reproducible from the information provided?
  • Is the metric linked to a decision or outcome it supports?
  • Have you set a review cadence and change process?

Use this starter kit as a living resource: adapt the taxonomy, evolve your targets, and keep ownership explicit. When teams stop arguing about definitions and start using the same language and numbers, decision speed and quality improve.

Use the domain.component.metric_unit pattern, e.g. product.activation_rate_pct. Lowercase and underscores recommended.
Human-friendly name, e.g. 'Activation rate (%)'.
Choose the type of signal this metric provides.
What decision or outcome does this metric support? Keep to a single clear sentence.
Describe the event or state measured so a non-technical stakeholder understands it.
Be precise: list numerator, denominator, time window, and the formula. Include grouping or smoothing rules if relevant.
How often should this metric be computed and reviewed?
Provide target and simple traffic-light thresholds, e.g. green >=25%, yellow 15–25%, red <15%.
Person or role accountable for the metric's definition and review.
Where is the data produced, who maintains ETL or instrumentation?
Comma-separated list of teams or roles to notify about changes.
List tables, events, ETL jobs, APIs and effective dates. Be specific (e.g. events_db.activation_event_v2; analytics_pipeline.activation_rollup).
Exclude test accounts, timezone, known instrumentation gaps, or planned changes that affect historical comparability.
Select relevant domains to group the metric.
Choose how frequently the owner should validate this metric definition and thresholds.
Archiving preserves historical definitions rather than deleting them.
If unsure, search the catalog or flag for the owner to resolve duplicates.
When proposing edits, explain why and how results/decision-making will change.
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