Build a measurement model around the way your marketplace actually works. Rudrriv helps platform teams connect buyer demand, seller or provider supply, listings, matching, transactions, retention and monetization into decision-ready analytics rather than disconnected reports.
Global delivery. Scope, data access, timing and final pricing are confirmed after the marketplace model and data environment are reviewed.
Marketplace analytics is priced as a Custom Quote because meaningful scope depends on the marketplace model, number of participant sides, available history, source systems, metric definitions, data quality, integration needs and reporting cadence. No teaser price is shown for work that may require materially different levels of analysis.
Best for founders, product, growth or operations teams that have data but lack a shared view of marketplace health.
Best for teams that need recurring operational visibility across buyers, sellers, matching, transactions and monetization.
Best for marketplace teams that need recurring health reviews, cohort analysis, reporting maintenance and decision support.
A marketplace with a clean event model and one transaction flow is materially different from a multi-region platform with separate buyer, seller, listings, payments, refunds and support datasets. The quote is built around the minimum work needed to produce analytics you can actually use.
Describe the marketplace model, the decisions you are trying to make and what data or reporting you already have. We can use that context to identify the most appropriate scope before pricing is confirmed.
Standard ecommerce reporting can focus primarily on a shopper-to-purchase path. A marketplace or platform must also understand whether supply is available and active, whether the two sides can successfully find or match with each other, whether transactions create sustainable platform revenue, and whether both sides return.
Top-line growth can hide marketplace weakness. More buyers do not help if relevant supply is missing; more sellers do not help if they receive no qualified demand; higher GMV does not automatically mean stronger net revenue or better unit economics. The measurement model needs to show how these parts interact.
The final scope is selected around your operating model. A service marketplace, product marketplace, booking platform, B2B exchange or on-demand platform will not use identical funnels or definitions.
Separate demand-side and supply-side acquisition so growth cost and activation are not blended into one user metric.
Understand whether enough relevant, active and usable supply exists for the demand you are generating.
Measure the steps between intent and a successful match, cart, booking, request, response or other marketplace outcome.
Analyze conversion, failed or cancelled outcomes, average transaction value and other transaction-stage friction.
Bridge marketplace activity to platform economics using agreed definitions for GMV, net revenue, fees and take rate.
Compare whether buyers and sellers continue to participate, transact or remain active across time and segments.
Break performance by category, geography, participant type, acquisition source, tenure or other useful dimensions.
Translate agreed KPIs into views that answer recurring product, growth, operations, finance or leadership questions.
Metric names are only useful when everyone agrees on the business definition, source fields, exclusions, time window and owner. Rudrriv can document that logic so reporting does not change meaning from one dashboard or stakeholder to another.
| Measurement area | Example questions | Possible metrics | Important definition checks |
|---|---|---|---|
| Marketplace scale | Is transaction activity growing, and where? | GMV, transaction count, average transaction value, active buyers/sellers | Completed vs booked value, cancellations, refunds, currency, reporting period |
| Liquidity / matching | Can qualified demand find suitable supply? | Match/fill rate, time to match, search success, response or acceptance rate | What counts as qualified demand, available supply and a successful match |
| Demand funnel | Where do buyers lose intent? | Activation, search-to-view, view-to-intent, intent-to-transaction, repeat rate | User identity, sessions, duplicate events, cross-device behavior |
| Supply funnel | Are sellers/providers becoming productive? | Onboarding completion, activation, active supply, time to first transaction, retention | Definition of active supply, availability windows, listing/provider status |
| Monetization | How does platform revenue relate to marketplace volume? | Net revenue, take rate, fees, incentives, refund impact | GMV vs revenue, gross vs net treatment, fee timing, pass-through amounts |
| Retention & quality | Are both sides returning and receiving useful outcomes? | Repeat purchase/use, buyer/seller retention, churn, cancellations, service quality proxies | Cohort start date, activity threshold, seasonality and reactivation rules |
These analyses are especially useful because the same GMV or active-user trend can mean very different things depending on supply-demand balance, matching efficiency, participant cohorts and monetization.
Liquidity should be defined around how your marketplace creates a successful connection. A product marketplace, job platform, services marketplace and on-demand network can require different numerator, denominator and time-window logic.
GMV measures transaction value flowing through a marketplace; it is not the same as the platform's revenue. Analytics should show how transaction volume becomes revenue and whether that economics improves or weakens by cohort, category, region or participant segment.
Included work describes what Rudrriv performs. Deliverables describe what your team receives. The exact combination depends on the selected engagement and data environment.
Activities are selected against the agreed business questions rather than running every analysis by default.
Formats are confirmed before delivery so your team knows what is editable, where the reporting will live and who owns ongoing updates.
You do not need every system connected on day one, but the analysis needs enough structure to connect participants, marketplace objects, events and commercial outcomes without double counting or losing important context.
Buyer, seller, provider, host, merchant or other participant records and lifecycle status.
Listings, products, services, jobs, properties, inventory, availability or other supply objects.
Search, browse, view, inquiry, request, response, cart, booking, match or other journey events.
Orders, bookings, fees, payouts, refunds, cancellations or other monetization records.
Marketing attribution, product analytics, CRM/support or other systems that explain how activity started or failed.
Current dashboards, spreadsheets, SQL extracts or management reports that expose known definitions and pain points.
The sequence adapts to the engagement, but each stage is designed to keep business definitions, data logic and outputs aligned before the next layer is built.
Confirm marketplace model, stakeholders, business questions and success criteria.
Decision briefInventory sources, identifiers, events, metric rules and known reporting conflicts.
Data mapCheck completeness, joins, duplicates, statuses, time logic and calculation assumptions.
QA notesRun the agreed funnel, cohort, liquidity, monetization or segment analysis.
AnalysisTranslate validated metrics into the agreed dashboard, scorecard or reporting format.
ReportingResolve review comments, document limitations and hand off metric and reporting guidance.
Final handoffThe review model focuses on data and calculation correctness, interpretation boundaries and agreed business logic. It does not promise that incomplete source data can support every requested metric.
Confirm the meaning of GMV, revenue, active supply, transaction, repeat activity and other core terms.
Check identifiers, joins, time fields, status logic, duplicates and completeness against the agreed use.
Compare important totals and calculation paths so dashboard outputs do not silently drift from source reporting.
Document gaps, assumptions and metrics that should not be interpreted beyond what the underlying data supports.
These are realistic situations rather than fabricated case studies. The right scope depends on the decision, the marketplace mechanics and the data currently available.
Analyze whether the issue is buyer intent, supply availability, search relevance, response, acceptance, pricing or transaction-stage friction.
Scope focus: liquidity + funnel diagnosticsSeparate onboarding completion from meaningful activation, time to first transaction and ongoing supply participation.
Scope focus: supply-side cohortsBuild a shared definition and bridge for transaction value, fees, refunds, commissions and other amounts so stakeholders interpret the same numbers.
Scope focus: commercial metric reconciliationSegment acquisition, liquidity, retention and monetization to identify whether local network density or category mix is driving the difference.
Scope focus: cohort + segment analyticsReplace disconnected team reports with a documented KPI model that links marketplace health, operations and commercial outcomes.
Scope focus: KPI model + dashboardEstablish recurring reviews for retention, supply-demand balance, anomalies, cohort performance and other operating questions.
Scope focus: managed analytics supportThese answers clarify suitability, data requirements, deliverables, pricing, review and boundaries before you submit an enquiry.
You do not need to diagnose the analytics problem before contacting us. Describe the marketplace model, the question you are trying to answer, the reporting you have today and any important deadline.
Email ID, Phone and Requirement Details are required. Name is optional.
