Evaluate pricing changes using ARPU, conversion, churn risk, NRR, and payback. Use when deciding whether a pricing move should ship.

Purpose Evaluate the financial impact of pricing changes (price increases, new tiers, add ons, discounts) using ARPU/ARPA analysis, conversion impact, churn risk, NRR effects, and CAC payback implications. Use this to make data driven go/no go decisions on proposed pricing changes with supporting math and risk assessment. What this is: Financial impact evaluation for pricing decisions you're already considering. What this is NOT: Comprehensive pricing strategy design, value based pricing frameworks, willingness to pay research, competitive positioning, psychological pricing, packaging architecture, or monetization model selection. For those topics, see the future pricing strategy suite skills. This skill assumes you have a specific pricing change in mind and need to evaluate its financial viability. Input Works best with: The pricing change on the table — increase, new tier, add on, or discount — and current pricing. Also useful: Current ARPU/ARPA, conversion and churn baselines, NRR, and who's pushing for the change. Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re ask. Arriving empty handed? That works too. The advisor opens by asking what change is proposed and what today's pricing looks like. Example invocation: Evaluate raising our Pro plan from $49 to $59/seat; ARPU $52, monthly logo churn 1.8%, NRR 108%. Key Concepts The Pricing Impact Framework A systematic approach to evaluate pricing changes financially: 1. Revenue Impact — How does this change ARPU/ARPA? Direct revenue lift from price increase Revenue loss from reduced conversion or increased churn Net revenue impact 2. Conversion Impact — How does this affect trial to paid or sales conversion? Higher prices may reduce conversion rate Better packaging may improve conversion Test assumptions 3. Churn Risk — Will existing customers leave due to price change? Grandfathering strategy (protect existing customers) Churn risk by segment (SMB vs. enterprise) Churn elasticity (how sensitive are customers to price?) 4. Expansion Impact — Does this create or block expansion opportunities? New premium tier = upsell path Usage based pricing = expansion as customers grow Add ons = cross sell opportunities 5. CAC Payback Impact — Does pricing change affect unit economics? Higher ARPU = faster payback Lower conversion = higher effective CAC Net effect on LTV:CAC ratio Pricing Change Types Direct monetization changes: Price increase (raise prices for all customers or new customers only) New premium tier (create upsell path) Paid add on (monetize previously free feature) Usage based pricing (charge for consumption) Discount strategies: Annual prepay discount (improve cash flow) Volume discounts (larger deals) Promotional pricing (temporary price reduction) Packaging changes: Feature bundling (combine features into tiers) Unbundling (separate features into add ons) Pricing metric change (seats → usage, or vice versa) Anti Patterns (What This Is NOT) Not value based pricing: This evaluates a proposed change, not "what should we charge?" Not WTP research: This analyzes impact, not "what will customers pay?" Not competitive positioning: This is financial analysis, not market positioning Not packaging architecture: This evaluates one change, not redesigning all tiers When to Use This Framework Use this when: You have a specific pricing change to evaluate (e.g., "Should we raise prices 20%?") You need to quantify revenue, churn, and conversion trade offs You're deciding between pricing change options (test A vs. B) You need to present pricing change impact to leadership or board Don't use this when: You're designing pricing strategy from scratch (use value based pricing frameworks) You haven't validated willingness to pay (do customer research first) You don't have baseline metrics (ARPU, churn, conversion rates) Change is too small to matter (<5% price change, <10% of customers affected) Facilitation Source of Truth Use [ workshop facilitation ](../workshop facilitation/SKILL.md) as the default interaction protocol for this skill. It defines: session heads up + entry mode (Guided, Context dump, Best guess) one question turns with plain language prompts progress labels (for example, Context Qx/8 and Scoring Qx/5) interruption handling and pause/resume behavior numbered recommendations at decision points quick select numbered response options for regular questions (include Other (specify) when useful) This file defines the domain specific assessment content. If there is a conflict, follow this file's domain logic. Application This interactive skill asks up to 4 adaptive questions , offering 3 5 enumerated options at decision points. Step 0: Gather Context Agent asks: "Let's evaluate the financial impact of your pricing change. Please provide: Current pricing: Current ARPU or ARPA Current pricing tiers (if applicable) Current monthly churn rate Current trial to paid conversion rate (if relevant) Proposed pricing change: What change are you considering? (price increase, new tier, add on, etc.) New pricing (if known) Affected customer segment (all, new only, specific tier) Business context: Total customers (or MRR/ARR) CAC (to assess payback impact) NRR (to assess expansion context) You can provide estimates if you don't have exact numbers." Step 1: Identify Pricing Change Type Agent asks: "What type of pricing change are you considering? 1. Price increase — Raise prices for new customers, existing customers, or both 2. New premium tier — Add higher priced tier with additional features 3. Paid add on — Monetize a new or existing feature separately 4. Usage based pricing — Charge for consumption (seats, API calls, storage, etc.) 5. Discount strategy — Annual prepay discount, volume pricing, or promotional pricing 6. Packaging change — Rebundle features, change pricing metric, or tier restructure Choose a number, or describe your specific pricing change." Based on selection, agent adapts questions: If Option 1 (Price Increase): Agent asks: " Price increase details: Current price: $ New price: $ Increase: % Who is affected? 1. New customers only (grandfather existing) 2. All customers (existing + new) 3. Specific segment (e.g., SMB only, new plan only) When would this take effect? Immediately Next billing cycle Gradual rollout (test first)" If Option 2 (New Premium Tier): Agent asks: " Premium tier details: Current top tier price: $ New premium tier price: $ Key features in premium tier: [list] Expected adoption: What % of current customers might upgrade? % What % of new customers might choose premium? % Cannibalization risk: Will premium tier cannibalize current top tier?" If Option 3 (Paid Add On): Agent asks: " Add on details: Add on name: Price: $ /month or /user Currently free or new feature? Expected adoption: What % of customers would pay for this? % Is this feature currently used (if free)? Will making it paid hurt retention?" If Option 4 (Usage Based Pricing): Agent asks: " Usage pricing details: Usage metric: (seats, API calls, storage, transactions, etc.) Pricing: $ per [unit] Free tier or minimum? (e.g., first 1,000 API calls free) Expected impact: Average customer usage: units/month Expected ARPU change: $current → $new Expansion potential: As customers grow usage, will ARPU increase?" If Option 5 (Discount Strategy): Agent asks: " Discount details: Discount type: (annual prepay, volume, promotional) Discount amount: % off Duration: (ongoing, limited time) Trade off: Lower price vs. improved cash flow (annual prepay) Lower price vs. larger deal size (volume) Lower price vs. urgency (promotional)" If Option 6 (Packaging Change): Agent asks: " Packaging change details: What are you changing? (bundling, unbundling, pricing metric) Current packaging: [describe] New packaging: [describe] Expected impact: ARPU change: $current → $new Conversion change: % → % Churn risk: (low, medium, high)" Step 2: Assess Expected Impact Agent asks: "Now let's quantify the impact. Based on your pricing change, estimate: Revenue impact: Current ARPU: $ Expected new ARPU: $ ARPU lift: % Conversion impact: Current conversion rate: % Expected new conversion rate: % Conversion change: [increase / decrease / no change] Churn risk: Current monthly churn: % Expected churn after change: % Churn risk: [low / medium / high] Expansion impact: Does this create expansion opportunities? (new tier to upgrade to, usage growth) Expected NRR change: % → % You can provide estimates. We'll model scenarios (conservative, base, optimistic)." Step 3: Evaluate Current State Agent asks: "To assess whether this pricing change makes sense, I need your current baseline: Current metrics: MRR or ARR: $ Number of customers: ARPU/ARPA: $ Monthly churn rate: % NRR: % CAC: $ LTV: $ Growth context: Current growth rate: % MoM or YoY Target growth rate: % Competitive context: Are you priced below, at, or above market? Competitive pressure: (low, medium, high)" Step 4: Deliver Recommendations Agent synthesizes: Revenue impact (ARPU lift × customer base) Conversion impact (new customers affected) Churn impact (existing customers affected) Net revenue impact CAC payback impact Risk assessment Agent offers 3 4 recommendations: Recommendation Pattern 1: Implement Broadly When: Net revenue impact clearly positive ( 10% ARPU lift, <5% churn risk) Minimal conversion impact Strong value justification Recommendation: " Implement this pricing change — Strong financial case Revenue Impact: Current MRR: $ ARPU lift: % ($current → $new) Expected MRR increase: +$ /month (+ %) Churn Risk: Low Expected churn increase: % → % (+ % points) Churn driven MRR loss: $ /month Net MRR impact: +$ /month ✅ Conversion Impact: Current conversion: % Expected conversion: % ( % change) Impact on new customer acquisition: [minimal / manageable] CAC Payback Impact: Current payback: months New payback: months (faster due to higher ARPU) Why this works: [Specific reasoning based on numbers] How to implement: 1. Grandfather existing customers (if raising prices) Protect current base from churn New pricing for new customers only 2. Communicate value Emphasize features, outcomes, ROI Justify price with value delivered 3. Monitor metrics (first 30 60 days) Conversion rate (should stay within %) Churn rate (should stay < %) Customer feedback Expected timeline: Month 1: +$ MRR from new customers Month 3: +$ MRR (cumulative) Month 6: +$ MRR Year 1: +$ ARR Success criteria: Conversion rate stays % Churn rate stays < % NRR improves to %" Recommendation Pattern 2: Test First (A/B Test) When: Uncertain impact (wide range between conservative and optimistic) Moderate churn or conversion risk Large customer base (can test with subset) Recommendation: " Test with a segment before broad rollout — Impact is uncertain Why test: ARPU lift estimate: % (wide confidence interval) Churn risk: Medium ( % → %) Conversion impact: Uncertain ( % → % estimated) Test design: Cohort A (Control): Current pricing: $ Size: % of new customers (or customers) Cohort B (Test): New pricing: $ Size: %

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