# Pricing Strategy Prover MCP > Pricing Strategy Prover forces you to validate pricing models against five critical business metrics: Value Metric definition, Willingness-to-Pay (WTP) research, Segmentation, Unit Economics, and Packaging design. It stops you from setting prices based on competitor charges or gut feeling. If your pricing needs scrutiny before launch, this tool provides the structural audit. ## Overview - **Category:** productivity - **Price:** Free - **Tags:** pricing-strategy, saas-pricing, value-metric, willingness-to-pay, unit-economics, monetization, van-westendorp, packaging ## Description The `validate_pricing_strategy` tool runs an audit on your pricing data. It checks five critical areas of your business model: value metric alignment, willingness-to-pay gaps, segmentation flaws, unit economics viability, and packaging anti-patterns. This isn't just a number checker; it forces you to prove why the price works and how much cash it keeps in your pocket. Your AI client uses this tool when pricing needs structural scrutiny before launch. It stops you from making decisions based purely on competitor rates or some gut feeling. You feed it the model, and it tells you exactly where the margin leak is. When validating a price, the system first tackles **Value Metric Definition**. You've got to prove your price isn't tied to something meaningless, like 'users.' The tool checks that your pricing unit scales directly with customer value—you know, things like API calls processed or total revenue run through the platform. If the metrics don't grow together, it flags a misalignment. Next up is **Willingness-to-Pay (WTP) Research**. It demands structured research data to validate pricing. You can’t just guess; you have to provide inputs from formal methodologies like Van Westendorp or Gabor-Granger studies. The tool uses this specific, quantitative data rather than letting vague market sentiment dictate your price points. For **Segment Pricing and Fencing**, the system makes sure you're applying different prices to distinct customer groups—say, small businesses versus large enterprises. It doesn’t just set two different rates; it defines feature gates between them. This prevents a user from simply upgrading their plan and suddenly accessing features they shouldn't be paying for, keeping your revenue streams clean. **Unit Economics Auditing** is where the real money talk happens. The tool calculates core metrics like the Customer Lifetime Value to Customer Acquisition Cost (LTV/CAC) ratio, payback period, and gross margin. It ensures the entire model generates profit at scale; if your acquisition cost burns through cash faster than you can earn it back, this thing flags it immediately. Finally, it reviews **Packaging Anti-Pattern Detection**. You'll run pricing tiers through a structural flaw check. This looks for things like overly generous free plans that kill conversion rates or upgrades that don't provide an obvious, measurable value jump. The system forces natural progression in your offering, making sure every tier has clear, defensible reasons to exist. ## Tools ### validate_pricing_strategy Runs a comprehensive audit on pricing data, checking for value metric misalignment, WTP gaps, segmentation flaws, unit economics issues, and anti-patterns in packaging. ## Prompt Examples **Prompt:** ``` We should price at $29/month per seat. That is what Competitor X and Competitor Y charge. It is a reasonable price point for the market. ``` **Response:** ``` VALUE_METRIC_UNDEFINED — 'Per seat because competitors use per seat' is not a value metric. Does each additional seat generate independent value? For an analytics platform, value comes from data processed — a 5-person team generating $2M in insights should pay differently than one checking dashboards weekly. Also: WTP_UNRESEARCHED — 'what competitors charge' is copying, not research. Run Van Westendorp on 100+ prospects. ``` **Prompt:** ``` Value metric: events processed — each event represents a user action tracked, more events = more behavioral data = more value. Van Westendorp on 142 product managers: acceptable range $0.001-0.003/event, optimal $0.002. Anchored to current Segment/Mixpanel spend ($300-800/month for same volume). Segments: Segment A — growth-stage SaaS (50K-500K events/month), price sensitivity high, target $150-400/month. Segment B — enterprise (5M-50M events/month), price insensitive, value = compliance + real-time, target $2,000-8,000/month. Fencing: volume tiers + SLA + data retention. Unit economics: CAC $420 (content + PLG), LTV Seg A $4,200 (24mo × $175), LTV Seg B $72,000 (36mo × $2,000), LTV/CAC 10x/171x, payback 2.4mo/0.2mo, gross margin 82%. Packaging: Free (10K events/month, 30-day retention, community support) → Growth ($0.002/event, 1-year retention, email support, upgrade trigger: hitting 10K limit) → Enterprise (volume discount, unlimited retention, SLA, dedicated CSM, upgrade trigger: compliance/real-time requirements). ``` **Response:** ``` PRICING_PROVEN — Rigorous pricing strategy validated. Value metric: events processed, scaling with customer behavioral data value. WTP: Van Westendorp on 142 PMs with $0.002 optimal, anchored to Segment/Mixpanel spend. Segments: growth-stage ($150-400) vs. enterprise ($2,000-8,000) with volume/SLA/retention fencing. Unit economics: LTV/CAC 10x-171x, payback under 3 months, 82% margin. Packaging: free tier limited to 10K events (upgrade trigger), enterprise adds compliance/SLA. This pricing survives board scrutiny. ``` **Prompt:** ``` Value metric: active contacts stored. More contacts = more value for CRM. WTP: 85 interviews, acceptable range $0.05-0.10/contact/month. Segments: Segment A — solopreneurs (500-2K contacts, $25-50/month). Segment B — agencies (10K-50K contacts, $200-800/month). Fencing by contact limit. Unit economics: CAC $290, LTV solopreneur $600 (12mo avg retention), LTV agency $7,200 (18mo), LTV/CAC 2.1x / 24.8x, payback solopreneur 5.8mo, agency 0.7mo. Gross margin 76%. Packaging: Free (250 contacts), Growth ($0.08/contact), Agency (volume discount). ``` **Response:** ``` UNIT_ECONOMICS_BROKEN — Value metric, WTP, and segmentation pass. But unit economics fail for Segment A: LTV/CAC of 2.1x is below the 3x threshold. Solopreneur segment has 12-month retention at $50/month = $600 LTV against $290 CAC. Options: (1) reduce solopreneur CAC to under $200 via PLG/referral, (2) increase retention to 18+ months via engagement loops, (3) increase ARPU to $65+/month, or (4) deprioritize solopreneurs and focus acquisition on agencies where LTV/CAC is 24.8x. ``` ## Capabilities ### Value Metric Validation Determines if the price is tied to a unit that actually scales with customer value (e.g., API calls processed, revenue processed). ### Willingness-to-Pay (WTP) Research Validates pricing by requiring structured research data using methodologies like Van Westendorp or Gabor-Granger. ### Segment Pricing and Fencing Applies different prices to distinct customer segments (e.g., small business vs. enterprise) while defining feature gates between them. ### Unit Economics Auditing Calculates critical metrics like LTV/CAC ratio, payback period, and gross margin, ensuring the model is profitable at scale. ### Packaging Anti-Pattern Detection Reviews pricing tiers for structural flaws, such as overly generous free plans or upgrades that lack clear value triggers. ## Use Cases ### The Per-Seat Trap A team charges $29/seat for an analytics platform. The tool immediately flags this as VALUE_METRIC_UNDEFINED, showing that charging per seat doesn't reflect the value delivered by a 500-server monitoring dashboard. It forces them to switch billing to 'per server monitored.' ### The Competitor Copy Fail A founder sets their price based on a competitor’s rate, thinking it's safe. The tool rejects this as WTP_UNRESEARCHED, pointing out that simply copying the price doesn't mean your customers have the same acceptable range or willingness to pay. ### The Unprofitable Growth Spree The finance team calculates LTV/CAC and sees 5x. The tool steps in, adjusting for gross margin (40% vs 70% benchmark), revealing the true ratio is only 2.0x—a structural failure that makes growth unsustainable. ### The Bad Free Tier A product has a 'Free' tier that includes almost everything, hoping for organic upgrades. The tool flags PACKAGING_MISALIGNED, showing this anti-pattern guarantees low conversion rates because there’s no natural reason to pay. ## Benefits - Prevents Margin Collapse: It forces LTV/CAC calculations to adjust for gross margin, so you don't think your business is healthy when it's actually unprofitable at the unit level. - Finds Your True Billing Unit: Instead of charging per seat (a poor metric), the tool helps you tie pricing to a scalable value unit like 'events processed' or 'API calls.' - Defines Tiered Pricing Correctly: It validates feature fencing, ensuring Enterprise clients pay enough for features they need but don't accidentally get for free. - Saves Months of Confusion: You skip the expensive mistake of launching a product with an anti-pattern—like a 'Generous Free' tier that kills your conversion rate. - Validates WTP Data: It demands specific market research data (Van Westendorp, etc.) instead of letting you rely on vague competitor anecdotes. ## How It Works The bottom line is that it forces your pricing strategy to pass five rigorous, interconnected financial and market audits. 1. Input your current pricing model and supporting business data: identify the core value unit, provide WTP research details (including methodology), define segment boundaries, and supply CAC/LTV estimates. 2. The tool runs a multi-pivot audit. It checks for inconsistencies across all five pillars—for example, rejecting claims of high LTV if the Value Metric is per-seat count. 3. You receive a final verdict matrix (PRICING_PROVEN or various failure codes) detailing exactly which structural flaw needs fixing before launch. ## Frequently Asked Questions **How does the Pricing Strategy Prover use the validate_pricing_strategy tool?** You provide the model details and supporting data (WTP, CAC, etc.). The tool then audits all five pillars—Value Metric, WTP, Segmentation, Unit Economics, and Packaging—to give a final 'PRICING_PROVEN' verdict. **Is per-seat pricing always wrong for the validate_pricing_strategy tool?** No. The tool doesn't ban per-seat billing; it forces you to prove that the seat count *is* the value metric. If seats don't correlate with unique value delivered, it flags VALUE_METRIC_UNDEFINED. **Do I need real Van Westendorp data for validate_pricing_strategy?** Yes. The tool requires named research methodologies and specific input (like N=200) to prove your WTP assumptions are based on data, not guesswork. **Can the Pricing Strategy Prover fix my unit economics?** It can't *fix* them, but it will definitively flag UNIT_ECONOMICS_BROKEN if your LTV/CAC is too low or if you haven't adjusted for gross margin. It tells you exactly what needs changing. **When I run validate_pricing_strategy, how does it detect conflicting pricing claims or semantic traps?** The tool's internal consistency engine flags contradictions. For example, if you claim WTP was researched but base the price on competitor data, the agent rejects it immediately. It forces alignment across all five pivots. **Before I use the validate_pricing_strategy tool, what specific inputs must my data contain?** You need structured metrics for every pivot. Don't just send paragraphs of text. Provide hard numbers like CAC per channel, gross margin percentage, and clear definitions for each customer segment. **How does the Pricing Strategy Prover handle the confidential financial metrics I input into validate_pricing_strategy?** Vinkius manages all data inputs according to strict privacy standards. Your pricing models remain private and are only used for generating your specific output within your AI client session. **What should I know about running validate_pricing_strategy multiple times in quick succession?** Because the tool runs deep financial calculations, it can be resource-intensive. Always check the Vinkius Marketplace for current rate limits and usage caps before running high volumes of validation checks. **Does it calculate prices?** No. It validates that your pricing strategy is grounded in value metrics, WTP research, segmentation, unit economics, and packaging design. It does not generate prices — it forces you to prove you derived them from data, not competitor pages. **What is Van Westendorp PSM?** The Price Sensitivity Meter asks 4 questions: at what price is it too cheap (quality doubt), a bargain (great value), getting expensive (think twice), too expensive (never buy). The intersections define the acceptable price range. It requires 100-300 respondents from your target segment to produce reliable data. **Can early-stage startups use this before having revenue data?** Yes. Pre-revenue startups use proxy data: Van Westendorp on 30+ prospect interviews, competitor pricing as anchor (not source), current workaround spend as floor, and projected CAC from channel tests. Unit economics use conservative assumptions. The tool forces you to document assumptions instead of skipping the analysis.