Where to start
A marketplace metric is more than a name and formula. A usable definition fixes the unit of observation, eligible population, time window, numerator event, and denominator rule. If any one of these changes, the quantity has changed even when the dashboard label has not. This is why the dictionary starts with metric cards and interpretation errors rather than benchmarks.
The twenty-five published definitions form a diagnostic chain rather than a KPI checklist. Demand creates an opportunity to match; supply must become eligible and receive qualified exposure; exposure must produce a response; a response must survive to a completed transaction; and a successful experience must lead to repeat behaviour and retention. Each transition metric localises a different failure. Revenue or GMV alone does not reveal where the chain broke.
The working method starts with a decision, not an attractive number. A seller-acquisition decision needs at least a demand-side outcome, exposure distribution, and a guardrail for incumbent supply. A ranking decision needs coverage, response quality, and transaction completion rather than clicks alone. Activation requires time to first qualified supply and a later outcome, not registration. This is an author-defined diagnostic system, version 0.1; it sets no universal thresholds.
A separate study of fifteen definitions from seven listed marketplaces shows why this distinction matters: identically or similarly named measures differ by window, counting unit, and qualifying event. The finding is bounded to the observed sample, but the operating rule is durable: compare definitions and versions before comparing numbers across companies, teams, or periods.
How to measure
- Demand frequency — The observed distribution of intervals between consecutive completed transactions by the same demand-side participant within a micro-market, published as a median and percentiles rather than as an average number of purchases per calendar period.
- Unmet demand share — The share of eligible demand units that do not reach a pre-defined successful outcome before a stated observation window ends.
- Supply-to-demand ratio — The ratio of eligible supply units to qualified demand units within the same preregistered opportunity unit: a micro-market and observation window.
- Seller activation rate — The share of eligible new sellers that reach a pre-defined useful-participation event within a stated window after cohort entry.
- Time to first qualified listing — The elapsed time from a seller entering the cohort to the moment they first create a supply unit that passes eligibility rules and becomes available for matching.
- Listing quality — A construct rather than a single measure: the degree to which a supply unit gives a demand participant sufficient and accurate information to decide. It is measured through a declared model of observable completeness, accuracy, and freshness indicators, published separately.
- Exposure coverage — The share of eligible supply units receiving a preregistered minimum amount of qualified exposure or candidate-set inclusion within the observation window.
- Zero exposure share — The share of eligible supply units that received no qualified exposure and no candidate-set inclusion during the observation window.
- Exposure concentration — The share of all qualified exposure captured by the top decile of eligible supply units, ranked by the exposure they received during the observation window.
- Market thickness — The number of simultaneously active eligible participants on each side within one micro-market during the observation window, reported as a pair of supply and demand counts rather than a single summary figure.
- Fill rate — The share of eligible demand units for which available supply satisfies a pre-defined successful-outcome criterion within a specified window.
- Time to match — The duration between an eligible demand unit becoming available for matching and its first match that satisfies a pre-defined criterion.
- Match quality — A construct rather than a single measure: the degree to which a realised match satisfied the original need of both sides. It is measured through a declared model of several observable indicators, published together and separately.
- Qualified response rate — The share of supply units that received qualified exposure and then attracted at least one demand-side response meeting a preregistered qualification rule within the window.
- Transaction completion rate — The share of confirmed interactions that reach a preregistered successful completion event within the defined fulfilment window.
- Failed transaction rate — The share of eligible transactions, started or confirmed under a preregistered rule, that reach a classified failure state instead of the intended successful outcome within the observation window.
- Cancellation rate — The share of confirmed interactions or transactions cancelled before a pre-defined successful-completion event within a stated window.
- Payment failure rate — The share of payment attempts on confirmed interactions that ended in a decline or technical failure and produced no successful capture within the attempt window.
- Refund rate — The share of completed transactions that were refunded in full or in part within a preregistered window.
- Time to first transaction — Elapsed time from a defined eligible participant or supply unit entering a cohort to its first transaction that reaches the specified terminal success event.
- Buyer repeat rate — The share of eligible buyers with an initial qualified success in a baseline cohort who achieve at least one subsequent qualified success within the defined repeat window.
- Seller repeat rate — The share of eligible sellers with an initial qualified success in a baseline cohort who achieve at least one subsequent qualified success within the defined repeat window.
- Buyer retention — The share of a buyer cohort completing at least one transaction in each subsequent observation period, reported as a retention curve across periods rather than a single number.
- Seller retention — The share of a seller cohort that maintained available eligible supply or completed a transaction in each subsequent observation period, reported as a retention curve across periods.
- Unmatched supply share — The share of eligible supply units that receive no qualified demand signal or valid match within a stated observation window.
Research and publications
- AI in marketplace matching: a conceptual map and research plan — A map of the layers where AI shapes the allocation of supply and demand, separating what an algorithm can improve from what it cannot create.
- Marketplace revenue architecture: from GMV to economic outcome — A framework connecting market activity, monetisation, execution reliability, and variable service cost without treating GMV as revenue.
- How to segment a marketplace into micro-markets — A step-by-step framework for segmenting a marketplace by actual substitutability so aggregates do not hide local scarcity and saturation.
- Seller activation: why registration is not activation — A diagnostic seller-activation framework covering the event chain from registration to eligible supply, first outcome, and repeat activity.
- How public marketplaces define their own metrics — Fifteen metric definitions from the annual reports of seven public marketplaces: identical names describe different quantities.
- State of Marketplace Liquidity: a research protocol — An open protocol for an annual study of marketplace liquidity: units of analysis, measures, data requirements, sensitivity tests, and non-claims.
- Supply without Demand: a research protocol — A protocol for testing when additional supply may weaken matching, supplier economics, or the platform's system outcome.
- Marketplace Health Index: a research protocol — A protocol for evaluating whether marketplace health can be summarised without arbitrary aggregation or false precision.
Frequently asked
Which marketplace metrics should be measured first?
A minimum set should cover both sides and the match itself: unmet demand share, supply receiving no qualified exposure, time to match, qualified response rate, and transaction completion rate. This is a starting diagnostic chain rather than a universal standard. The exact set depends on the marketplace architecture and the decision the team needs to make.
Is GMV enough to assess marketplace health?
Not when the task is to diagnose the growth mechanism. GMV describes the aggregate volume of completed activity but does not reveal unmet demand, supply receiving no attention, allocation concentration, or failures between match and completion. It remains an important business outcome, but it needs transition metrics and micro-market cuts beside it.
Are there universal healthy marketplace benchmarks?
No. Acceptable time to match, normal demand frequency, and even the unit of a successful transaction depend on marketplace model, category, geography, and period. A threshold can be calibrated on first-party data through its relationship with retention, completion, and economics, but it cannot be imported from another platform without reconciling definitions.
How do leading and lagging marketplace metrics differ?
Lagging measures record an outcome that has already occurred: completed transactions, GMV, revenue, refunds, or retention. Leading measures appear earlier in the chain: supply eligibility, coverage, time to match, and response. The label is not permanent: qualified response may be an outcome for a ranking team and a leading signal for a transaction team.
How can a team detect that a metric definition changed?
Store the definition version, owner, effective date, window, population, numerator, and denominator beside the value. A change to any element requires a new version and a time-series break marker. Checking the label or SQL file alone is insufficient: meaning can change through an eligibility filter, a new event, or a different window.
Can all measures be combined into a Marketplace Health Score?
Technically yes; methodologically only after construct, weights, normalisation, sensitivity, and compensation effects have been tested. Until then, a single score hides more decisions than it explains. The site publishes a protocol for that validation but deliberately claims no universal finished index.
Strongest counterargument
Twenty-five measures create analytical bureaucracy. A team needs one north-star KPI and speed of action, not a dictionary of definitions.
Response
The objection is valid when a dictionary becomes a mandatory dashboard. This page proposes something else: select a short chain for a specific decision. A north-star records the desired outcome, one or two diagnostic measures locate the break, and a guardrail protects the side of the market the primary measure cannot see. This is usually three to five measures, not all twenty-five. The dictionary exists so the team does not substitute one quantity for another and can change the set without losing meaning.