What the MRR waterfall and movement-classification analysis prompt does

Act as a SaaS recurring-revenue accounting and analytics specialist.

The prompt will, at minimum:

  • Validate datasets, definitions, time windows, market scope and source-of-truth ownership before assessing mrr waterfall and movement-classification analysis
  • Examine opening and closing MRR, new business, expansion, contraction, churn, reactivation, plan changes, quantity and price changes, credits, pauses, one-time fees, currency conversion, contract amendments, effective dates, late-arriving data and reconciliation; preserve original identifiers and show the derivation of every finding
  • Segment only when evidence supports the split. Expose missingness, sample bias, seasonality, releases, campaigns, migrations and other confounders instead of hiding them in averages
  • Recompute material metrics from supplied values; disclose formulas, denominators, exclusions and scenario assumptions. Never invent benchmarks, market sizes or competitor performance
  • Turn evidence into a reconciled MRR waterfall, movement rulebook and exception queue; assign owner, priority, dependency, expected signal, verification method and human-approval point to each action

Who it is for

Gökhan Güzel's SaaS prompt for Claude users: marketers, founders, agencies and consultants who need an auditable, evidence-based deliverable instead of generic advice.

What you get

  • Executive summary and data-quality report
  • MRR waterfall and movement-classification analysis methodology and evidence ledger
  • Segmented findings, calculations and scoring
  • Prioritised action backlog with owners and validation criteria
  • Sources, limitations, confidence and QA report

Variables

PlaceholderPurpose
{{account_master}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{acquisition_events}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{analysis_period}}Date, time or period value; state ISO format, time zone, start/end boundary and comparison period
{{company_name}}Verified identifier or text value; state exact spelling, source, status and validity scope
{{contract_data}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{credit_policy}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{currency_rates}}Numeric value or table; state formula, numerator, denominator, unit, currency, tax treatment, period and source
{{data_quality_notes}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{invoice_data}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{movement_rules}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{mrr_definition}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{pause_policy}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{subscription_data}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{success_metrics}}Numeric value or table; state formula, numerator, denominator, unit, currency, tax treatment, period and source

How to use

Copy the prompt with the button above, replace every {{placeholder}} with your verified data, and paste it as the first message in a new Claude conversation. The prompt runs a short question gate first; answer it, then the deliverable is produced.

Run MRR waterfall and movement-classification analysis in Claude

Open a new Claude chat, paste the filled-in MRR waterfall and movement-classification analysis prompt and answer the short question gate. Claude then returns the executive decision, the evidence ledger and the task-specific tables in one reply.

Source

Original file in the multilingual prompt library on GitHub: