Share

Copy link LinkedInXEmail

A metric is a performance calculation: what is counted or divided, and at what grain. It names its Signal or Metric inputs directly, or points to one versioned Formula that names them; it is never the evidence itself.

What you can do with a metric

• tableMeasurement Plan · Measurement Model
• tableEvidence Plan · Evidence
• tableEvidence Plan · Settings

Its metrics— 51

• Site VisitsCount of visits to the owned site in the period: the base audience measure every site rate sits on top of.
• First-Time Visit ShareThe share of visits from people with no prior visit on record.
• Qualified Visit RateThe share of visits that meet the qualification threshold for the page they land on.
• Content Engagement RateThe share of content views that meet the engagement threshold.
• Video Completion RateThe share of started videos watched to completion.
• Form Start to Submit RateThe share of started forms that are submitted.
• Page Experience IndexA composite standing of a page against the Core Web Vitals thresholds.
• Conversion Flow Completion RateThe share of started conversion flows that end in a confirmed conversion.
• Fulfilment RateThe share of confirmed conversions that were fulfilled rather than cancelled or left undone.
• Assisted-Conversion ActionsThe count of conversion actions that reach a person rather than a system: a call placed, a chat started.
• Account Activation RateThe share of started account registrations that end in an activated account.
• Lead CountThe count of resolved lead inputs at tactic and intended-outcome grain.
• Conversion CountThe count of completed intended outcomes in the period.
• Lead to Conversion RateThe share of resolved lead inputs that produce an intended outcome within its declared attribution window.
• Lead to Modelled Conversion RateThe share of resolved lead inputs that receive a modelled intended outcome within its declared attribution window.
• Reactivation RateThe share of lapsed consumers who return within the win-back window.
• Attributed-Conversion ShareThe share of conversions that arrive carrying a source key.
• Referral Conversion RateThe share of referred sessions that convert, read by the channel that referred them.
• Media CostGross media cost recorded against a tactic.
• Cost per LeadMedia cost divided by resolved leads.
• Cost per ConversionMedia cost divided by conversions.
• Cost per Modelled ConversionMedia cost divided by modelled conversions.
• Attributed RevenueRevenue on conversions joined to one tactic through the CRM. Credit rests wholly on that single touch, so a journey that took several reads as though the last of them produced it.
• Ad ImpressionsPaid media impressions delivered against a tactic.
• Ad ClicksPaid media clicks recorded against a tactic.
• Paid Search EfficiencyPlatform conversions per unit of paid search spend.
• Email Engagement RateThe share of delivered emails opened or clicked.
• SMS Engagement RateThe share of delivered SMS clicked or replied to.
• Offline ReachTotal offline delivery in the period: the nearest reading to reach available where no individual is observed.
• Organic Visibility ShareThe share of tracked queries where the brand holds a top-ranking result.
• Citation RateResponses citing the brand as a source, over responses returned for the tracked query set. Where mention says the brand was spoken about, citation says it was relied on.
• Mention RateResponses containing a brand mention, over responses returned for the tracked query set. The base reading of answer visibility: unmentioned, nothing after it applies.
• Share of VoiceBrand mentions as a proportion of all brand mentions within a defined competitive category. An absolute mention rate cannot say whether rivals moved.
• Video Answer AppearancesCount of tracked queries returning a brand video as an answer.
• Schema CoverageThe share of governed entity properties that the site publishes as structured data.
• Return on Ad SpendAttributed revenue divided by media cost.
• Revenue per LeadAttributed revenue divided by resolved leads.
• Revenue per ConversionAttributed revenue divided by completed conversions.
• Click-through RatePaid media clicks over paid media impressions delivered in the period.
• Retention RateThe share of relationships active at the start of a window that are still active at its end.
• Customer Lifetime ValueExpected revenue from one relationship across the whole of its life, brought back to the present.
• Advocacy RateThe share of consumers who bring at least one other person in.
• ReachThe count of distinct people a placement was delivered to, as against the count of deliveries.
• Visibility MomentumPercentage change in mention rate or share of voice between two defined measurement periods.
• PositionWhere the brand falls in the response as rendered: first entity or later, its rank among listed alternatives, and whether it stands as the recommendation or as one option among several.
• Hallucination RateResponses attributing to the brand a product, claim or association that does not exist, over responses returned for the tracked query set.
• Post-Citation Click-through RateClicks on a citation, over responses in which that citation appeared.
• Lapse RateThe share of relationships active at the start of a window that have no qualifying activity by its end: the fact of leaving, counted where retention counts staying.
• Likely-to-Lapse RateThe share of active relationships a model scores as likely to disengage before any window has run out: risk read ahead of the lapse it predicts.
• FrequencyThe average number of times a placement was delivered to each person it reached: deliveries over distinct people. Too few and the message does not register, too many and the spend is wasted, so it is read against a band rather than in one direction.
• Opt-out RateWithdrawals of permission over deliveries on one channel in the window: the share of people reached who asked not to be reached that way again.

Why it matters

What goes wrong without it, as the commitments that license this kind say it, each standing on its sources.

• Declare measurement grain before calculationA rate means nothing unless everyone agrees what one instance of its numerator and its denominator represents. Marketing reporting fails less often because a number is wrong than because two numbers computed at different grains were divided — sessions over people, clicks over sends — and nothing in the output says so. Declaring the grain first is what makes the calculation reproducible by someone who did not write it.
  Declaring the Grain
• Make outcome quality, calculation method and attribution inspectableAn outcome number is only as good as the inputs, exclusions and window that nobody wrote down. Media measurement standards exist because outcome claims circulate detached from their method, and a figure with no stated method cannot be challenged, reproduced or compared against anyone else's. Keeping what a measure means apart from how it is computed is what makes either one reviewable.
  Outcomes and Data Quality Standards · Declaring the Grain · Measuring Visibility in the AI Era · Data-driven multi-touch attribution models · Causally motivated attribution for online advertising · A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook · Why Three Exposures May Be Enough · Digital Audience-Based Measurement Standards
• A metric exists because a question needs itGoal-Question-Metric was formulated against a specific failure: measurement chosen because a system already produces it, rather than because a stated question needs it. The order it insists on is goal, then question, then measurement. Without the middle term a dashboard grows without limit, and which of its numbers would change a decision stops being answerable.
  The Goal Question Metric Approach · Outcomes and Data Quality Standards · Declaring the Grain · Aligning Organizations Through Measurement: The GQM+Strategies Approach
• A declared path must be walkableEvery other check asks whether a relationship is well formed: typed, bounded, licensed, inverted. None asks whether anything travels it. So the model could pass every check with a verb declared for thirty-eight kinds and asserted by none, and say nothing - which is what happened. A reader meeting that has no way to tell a deliberate absence from an oversight, and neither does the author six months on. The distinction is schema completeness against population completeness: the first was already enforced here and the second had no instrument at all. It matters most where a claim is a chain rather than a link. Performance asserted from delivery alone, with no step that reaches a person, is the specific failure measurement standards exist to prevent, and it is invisible to a check that only reads one edge at a time.
  Shapes Constraint Language (SHACL) · Outcomes and Data Quality Standards
• A move that cannot be counted is a pictureA journey that names its moves and cannot count them is a funnel with arrows: it can be drawn and not measured, which is the failure a state machine was adopted to end. Customer-migration models make the point exactly. A transition rate is the moves out of a condition over the people in it, and the people in it are the fact that put them there; so the events added to give every move a trigger are not extra instrumentation but the missing denominators of rates the model already carried and could not derive. A law that every move has a trigger, satisfied by facts nothing observes, would be the same picture with more arrows.
  Modeling customer relationships as Markov chains · Declaring the Grain · The Goal Question Metric Approach · Counting Your Customers the Easy Way: An Alternative to the Pareto/NBD Model
• A reading names its unit, and the unit fits its formA number without its unit is not a reading. Metrology defines a quantity value as a number and a reference together, and the unit codes exist because a value that travels without its unit is misread at the far end: a rate and a count that print the same figure have said different things, and percent is a name for the number 0.01, not a kind of thing. This model already fixed a KPI's direction and form as facts in the graph; the unit is the third fact of that family. Declaring which forms a unit fits is what a unit ontology does when it binds units to kinds of quantity, and it turns unit-form agreement from a review into a check.
  International Vocabulary of Metrology: Basic and General Concepts and Associated Terms (VIM), JCGM 200:2012 · ISO 80000-1:2022 Quantities and units, Part 1: General · The Unified Code for Units of Measure, version 2.2 · QUDT Ontologies: Quantities, Units, Dimensions and Data Types, release 2.1 · ISO 4217 Currency codes