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πŸ’° Financepublic

Sales vs Cost & Scale Readiness Dashboard

Generates an AARRRC-based executive dashboard and a CEO scaling questionnaire from financial data.

Aman Bhogalby Aman Bhogal
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Why You'll Love This
Drive strategic growth: Sales, Costs, & Scaling insights in one.
  • Gain AARRRC-based insights for holistic business performance.
  • Visualize Sales vs. Cost instantly for strategic clarity.
  • Assess scaling readiness with a tailored CEO questionnaire.

Transform your financial data into actionable insights. This recipe delivers an AARRRC-based executive dashboard and a CEO scaling questionnaire to guide your strategic growth decisions.

Workflow Visualization

Prompt Template

You are a strategic finance analyst and executive dashboard architect. Create a "Sales vs Cost" dashboard recipe for company_name using the AARRRC framework. This recipe bundles a visual dashboard component with a CEO readiness-check questionnaire for scaling decisions. --- **PART 1 β€” AARRRC DASHBOARD** Build a structured dashboard displaying the following six metrics alongside the core "Sales vs Cost" KPI: | Metric | Definition | Key Data Points to Show | |---|---|---| | Acquisition | New customer inflow | CAC, lead volume, conversion rate | | Activation | First-value moment | Onboarding rate, time-to-first-action | | Retention | Repeat engagement | Retention rate, cohort data | | Referral | Word-of-mouth growth | NPS, referral rate, viral coefficient | | Revenue | Income generated | MRR/ARR, ARPU, revenue growth % | | Churn | Customer/revenue loss | Churn rate, lost revenue value | **Core KPI Panel β€” Sales vs Cost:** - Analyze uploaded_data_file to extract Total Sales Revenue, Total Operating Cost, and all relevant AARRRC metrics - Scope all trend analysis and calculations to the period: analysis_period (e.g., Last 12 Months, Last Quarter) - Express all financial figures in target_currency (e.g., INR β‚Ή, USD $, EUR €) - Calculate and display: Gross Margin %, Revenue-to-Cost Ratio, and Month-over-Month trend - Visual format: Render charts using Mermaid.js syntax so they display natively in supported interfaces β€” produce a side-by-side bar chart for Sales vs Cost and a trend line overlay for MoM growth **Status Indicators β€” use only the benchmarks below. Do not infer or hallucinate thresholds:** | Metric | 🟒 Green (Healthy) | 🟑 Amber (Watch) | πŸ”΄ Red (At Risk) | |---|---|---|---| | Gross Margin % | β‰₯ 60% | 40–59% | < 40% | | Revenue-to-Cost Ratio | β‰₯ 1.5x | 1.0–1.49x | < 1.0x | | CAC Payback Period | ≀ 12 months | 13–18 months | > 18 months | | Monthly Churn Rate | ≀ 2% | 2.1–5% | > 5% | | Net Revenue Retention | β‰₯ 100% | 85–99% | < 85% | | NPS Score | β‰₯ 50 | 20–49 | < 20 | | Lead-to-Customer Conversion | β‰₯ 15% | 8–14% | < 8% | Flag each metric with the appropriate 🟒 / 🟑 / πŸ”΄ indicator based solely on these thresholds. Present all metrics in a clean, scannable layout suitable for executive review. --- **PART 2 β€” CEO SCALE-READINESS QUESTIONNAIRE** The company is evaluating a 3x revenue scale. Generate a 5-question readiness-check the CEO can use with their team. Each question must: - Be answerable in under 2 minutes - Reveal a specific operational or financial risk - Include a follow-up probe if the answer is unclear Format each question as: **Q[N]: [Question]** *Why it matters:* [1-sentence rationale tied to AARRRC or Sales vs Cost] *Follow-up probe:* [Clarifying question if team hesitates] *Green signal:* [What a confident, scale-ready answer looks like] --- **RECIPE METADATA** - Category: finance - Use case: Executive dashboard + scaling decision support - Analysis period: analysis_period - Currency: target_currency - Data source: uploaded_data_file - Company: company_name

Variables (4)

Company Name{{company_name}}Required

e.g., Acme Corp

Financial Data File{{uploaded_data_file}}Required

Upload your sales and cost report (CSV or Excel)

Analysis Period{{analysis_period}}Required

e.g., Last 12 Months, Q3 2023

Target Currency{{target_currency}}Required

e.g., USD $, INR β‚Ή, EUR €

AI Configuration

Extended Thinking
Model
Custom Model

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