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finance-based-pricing-advisor

Evaluate pricing changes using ARPU, conversion, churn, NRR, and CAC payback analysis.

Updated Aug 18, 2024
Search Tags:#churn#revenue-modeling#nrr#arpu#cac-payback#pricing-change
One-click install
npx skills add https://github.com/ch-m-n/dotfile --skill finance-based-pricing-advisor-ch-m-n
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: finance-based-pricing-advisor
Source: https://github.com/ch-m-n/dotfile/tree/main/opencode/skills/finance-based-pricing-advisor
Command: npx skills add https://github.com/ch-m-n/dotfile --skill finance-based-pricing-advisor-ch-m-n

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps product and finance leaders quantify the net business impact of proposed pricing changes so price increases, new tiers, add-ons, and discount strategies are evaluated before they harm churn, conversion, or unit economics.

Core Features & Use Cases

  • Revenue Impact Modeling: Measures ARPU/ARPA shifts alongside conversion and churn trade-offs to surface net MRR or ARR gains or losses.
  • Risk-aware Assessment: Compares pricing change types through conservative/base/optimistic scenarios that include expansion, NRR, and CAC payback effects.
  • Decision Support: Generates tailored recommendations to implement broadly, test, modify, or hold pricing with concrete contextual examples.
  • Use Case: Evaluate a 20% price increase for new customers, assess churn risk, conversion delta, and CAC impact, then prepare a go/no-go recommendation for leadership.

Quick Start

Ask the finance-based-pricing-advisor to model a specific pricing change with current ARPU, churn, conversion, CAC, and NRR to assess revenue impact and risk.

Frequently Asked Questions about finance-based-pricing-advisor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate the revenue impact of a pricing change on ARPU and churn?▼

Revenue impact modeling measures ARPU shifts alongside conversion and churn trade-offs to surface net MRR or ARR gains or losses. It applies conservative, base, and optimistic scenarios to quantify whether a pricing change is financially viable.

What metrics do I need to assess CAC payback before implementing a price increase?▼

Assessing CAC payback requires current ARPU, churn, conversion, CAC, and NRR metrics. Inputting these figures allows the model to project unit economics and determine if the payback period improves or degrades after the pricing change.

Can I model usage-based pricing and add-on packaging changes with this approach?▼

Yes, you can model usage-based schemes, add-ons, new tiers, and packaging changes. The evaluation applies the same ARPU, conversion, and churn math to generate a go/no-go recommendation for these specific monetization structures.

How do I run a sensitivity analysis for a proposed discount strategy?▼

Sensitivity analysis applies conservative, base, and optimistic scenarios to your discount strategy. By adjusting churn, conversion, and NRR variables, you can stress-test the risk-aware assessment and see how extreme outcomes affect net revenue.

When should I not use ARPU and NRR modeling to evaluate a new pricing tier?▼

ARPU and NRR modeling is less effective when you lack baseline metrics like current conversion or CAC. Without accurate current state data, the conservative, base, and optimistic scenarios cannot produce a reliable go/no-go monetization decision.

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