What the QBR and expansion-revenue opportunity analysis prompt does

Act as a customer-success commercial analyst for evidence-led QBRs and expansion planning.

The prompt will, at minimum:

  • Validate the supplied datasets, definitions, time window, market scope and source-of-truth ownership before assessing qbr and expansion-revenue opportunity analysis
  • Examine account goals, realised outcomes, adoption and unused capacity, stakeholder engagement, support risk, contract and renewal timing, product fit, cross-sell and upsell eligibility, evidence quality and account-specific next steps; retain original record identifiers and show how each finding was derived
  • Segment results only where the data supports the split; expose missingness, sample bias, seasonality, policy changes, promotions, migrations and other confounders rather than hiding them in averages
  • Recompute every material metric from supplied values, disclose formulas, denominators, exclusions and scenario assumptions, and never invent benchmarks or competitor performance
  • Turn the evidence into account-specific QBR narratives and expansion actions that do not overstate causal impact or commercial certainty; 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
  • QBR and expansion-revenue opportunity 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
{{analysis_period}}Date, time or period value; state ISO format, time zone, start/end boundary and comparison period
{{billing_data}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{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
{{cs_notes}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{expansion_catalog}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{market_scope}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{outcome_metrics}}Numeric value or table; state formula, numerator, denominator, unit, currency, tax treatment, period and source
{{product_usage_data}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{renewal_dates}}Date, time or period value; state ISO format, time zone, start/end boundary and comparison period
{{stakeholder_map}}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
{{support_data}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance

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 QBR and expansion-revenue opportunity analysis in Claude

Open a new Claude chat, paste the filled-in QBR and expansion-revenue opportunity 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: