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    SaaS Unit Economics Metrics Analyst

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    Senior SaaS metrics analyst for growth, retention, and unit economics diagnostics with strict evidence discipline.

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    SaaS Unit Economics Metrics Analyst

    SaaS Unit Economics Metrics Analyst

    Example session with this skill installed

    Analyze this Q3 data: Starting MRR $100k, New MRR $15k, Expansion $5k, Churn $8k. Sales spend was $45k. We added 10 logos and lost 4. Total customers at end is 96. Calculate NRR, CAC, and payback.

    • Read your context and instructions
    • Compiled the saas unit economics

    The following analysis reconciles Q3 performance data, identifying a minor discrepancy in customer counts and calculating key efficiency ratios based on supplied revenue movements.

    SaaS Metrics Diagnostic: Q3 Performance

    1. Executive SaaS Metrics Brief

    • Reporting Period: Q3
    • Key Snapshot: Net New MRR of $12k driven by strong expansion, offset by moderate churn.
    • Data Confidence: High for revenue; Moderate for customer counts (Reconciliation needed).
    • Immediate Attention: CAC Payback period exceeds 24 months, suggesting acquisition inefficiency.

    2. Metric Reconciliation Audit

    MetricSupplied ValueCalculated ValueStatusExplanation
    Ending MRRNot Provided$112,000CALCULATED$100k (Start) + $15k (New) + $5k (Exp) - $8k (Churn)
    Customer Bridge9696RECONCILED90 (Inferred Start) + 10 (New) - 4 (Churn) = 96
    ARRNot Provided$1,344,000CALCULATED$112,000 * 12

    3. Growth & Efficiency Analysis

    MetricValueFormula / Basis
    Net Revenue Retention (NRR)102%($100k - $8k + $5k) / $100k
    Gross Revenue Retention (GRR)92%($100k - $8k) / $100k
    CAC (Per Logo)$4,500$45,000 / 10 New Logos
    CAC Payback (Months)30.0$4,500 / ($15,000 / 10 ARPA)
    Magic Number1.07($12k Net New MRR * 4) / $45k Sales Spend

    4. Management Diagnosis

    SUPPORTED BY DATA: The business is net-retention positive (102%), meaning expansion from existing customers is successfully offsetting churn.
    *

    SUPPORTED BY DATA: Acquisition efficiency is low. A 30-month CAC payback is significantly higher than the 12-month SaaS standard, indicating that sales spend is not converting to immediate revenue efficiently.
    *

    PLAUSIBLE INFERENCE: High CAC relative to ARPA suggests either a high-touch sales process for low-value contracts or inefficient marketing spend.

    Next steps

    1. Audit sales and marketing channels to identify which specific campaigns contributed to the $4,500 CAC.
    2. Review the 4 churned logos to determine if they belong to a specific segment or tier.
    3. Validate the $5k expansion MRR to see if it is repeatable or a one-time upsell event.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    SaaS founders and operators often struggle with fragmented data, inconsistent reporting, and vanity metrics that hide underlying business risks. Manually reconciling churn, expansion revenue, CAC, and MRR across multiple spreadsheets frequently leads to reporting errors, misleading dashboards, and poor strategic decisions.

    What it does

    Performs a rigorous metric reconciliation audit to detect inconsistencies between MRR, ARR, customer counts, churn, and expansion revenue.

    Calculates core SaaS unit economics including LTV:CAC, NRR, GRR, CAC Payback, Magic Number, Burn Multiple, and Rule of 40 using transparent, verifiable formulas.

    Audits revenue and customer bridges to ensure beginning and ending metrics reconcile correctly.

    Conducts evidence-based retention and cohort analysis to separate growth from new customer acquisition versus expansion revenue.

    Generates a 90-day operational roadmap focused on improving data quality, retention health, growth efficiency, and cash performance.

    Produces a structured risk register highlighting customer concentration, burn volatility, reporting inconsistencies, and other evidence-backed operational risks.

    Why this beats prompting it yourself

    General-purpose AI assistants often invent missing values, mix incompatible SaaS formulas, or apply generic benchmarks without validating the underlying data. This skill follows a strict evidence-first methodology: it never fabricates metrics, clearly separates verified facts from inferences, reconciles conflicting financial inputs, and explains calculations step by step before drawing conclusions.

    Use cases

    Prepare investor, board, or due diligence reports with reconciled SaaS financial metrics.

    Audit subscription reporting for billing platforms such as Stripe, Paddle, Chargebee, or similar exports.

    Identify churn, contraction, and expansion trends across customer segments or pricing tiers.

    Evaluate acquisition efficiency, CAC payback, retention quality, and overall revenue health before strategic planning.

    Known limitations

    This skill does not provide regulated accounting, tax, legal, or investment advice. All calculations and recommendations depend on the accuracy and completeness of the financial data supplied by the user, and missing inputs are explicitly reported rather than estimated.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Research & Analysis.

    Cannot verify raw data accuracy or access private financial systems. Does not provide regulated tax, legal, or investment advice. Requires specific revenue and customer inputs for full analysis.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

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    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before buying a skill.

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    What's inside

    Frequently Asked Questions

    The analyst reconciles fragmented revenue data to calculate core metrics like LTV:CAC, NRR, and Burn Multiple, while identifying reporting errors that often lead to misleading dashboards.

    It is designed for use with advanced LLMs like GPT-4 and Claude 3.5 Sonnet, ensuring the complex mathematical reasoning required for cohort analysis and revenue bridges is handled accurately.

    This skill follows a strict 'zero-fabrication' protocol; it will explicitly flag missing or conflicting data points rather than inventing values, ensuring your financial reports are based entirely on verified evidence.

    Your purchase includes the specialized system prompt and configuration files, a guide for formatting your billing exports, and a standardized reporting template for the 90-day operational roadmap.

    Yes, purchasers receive lifetime access to all future updates, which include refined SaaS formulas and improved diagnostic logic as industry standard benchmarks evolve.

    New in Research & Analysis