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Advise on pricing strategy — competitive analysis, willingness-to-pay research, tier design, price increase modeling, discount frameworks, and packaging optimization for startup monetization.
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| name | pricing-strategy-advisory |
| description | Advise on pricing strategy — competitive analysis, willingness-to-pay research, tier design, price increase modeling, discount frameworks, and packaging optimization for startup monetization. |
| version | 2.0.0 |
| author | Crewm8 |
| maintainer | Gokul (github.com/gokulb20) |
| license | MIT |
| homepage | https://crewm8.ai |
| tags | ["cfo","finance","pricing","monetization","tier-design","price-optimization"] |
| related_skills | ["unit-economics-analysis","profitability-analysis","revenue-forecasting","strategic-initiative-modeling","business-case-modeling"] |
| inputs_required | ["current-pricing-structure","competitor-pricing-intelligence","customer-willingness-to-pay-data","unit-economics-by-segment"] |
| deliverables | ["competitive-pricing-landscape","recommended-pricing-model-and-tier-structure","price-increase-impact-analysis","discount-framework-and-approval-guidelines"] |
| compatible_agents | ["hermes","claude-code","droid","cursor","windsurf","openclaw","openai","generic"] |
Advise the CEO and leadership on pricing — how much to charge, how to structure tiers, when and how to raise prices, and how to package the product for maximum value capture. Goal: the company charges what it's worth, not what it's afraid to ask for.
Pricing is the single most leveraged lever in the business — a 10% price increase flows almost entirely to profit, and poor pricing leaves millions on the table. Yet most startups underprice by 30-50% because founders are afraid of losing deals. This skill provides the frameworks, analyses, and confidence to set prices that capture the value the product actually delivers, design tiers that maximize willingness-to-pay capture, and execute price increases without destroying customer relationships.
unit-economics-analysis (CAC, LTV, gross margins per segment).| Pricing Model | When to Use | Key Tradeoff |
|---|---|---|
| Flat rate | Simple product, single persona | Easy to sell, leaves money on table |
| Per-seat / per-user | Collaboration / productivity tools | Scales with adoption, penalizes adoption |
| Tiered (Good-Better-Best) | Most SaaS products | Captures different WTP, tier design is hard |
| Usage-based | API, AI, infrastructure | Aligned with value, unpredictable for customers |
| Hybrid (base + usage) | Platform products | Predictable base + value-aligned variable |
| Pricing Psychology Principle | Application |
|---|---|
| Never 2 tiers | People can't choose between 2; add a third (decoy) |
| Decoy effect | A high tier makes the middle tier feel reasonable |
| Annual discount | 15-20% off monthly anchors higher monthly price |
| .99 pricing | $99 feels meaningfully cheaper than $100 |
| Price increase timing | At renewal, grandfather existing 6-12 months |
For each competitor, map:
| Competitor | Starting Price | Mid-Tier | Enterprise | Pricing Model | Differentiator |
|---|---|---|---|---|---|
| Comp A | $29/seat/mo | $79/seat/mo | Custom | Per-seat | Has feature X |
| Comp B | $49/mo flat | $199/mo | $499/mo | Flat + add-ons | Cheaper at scale |
| Us | TBD | TBD | TBD | TBD | Better UX, faster |
Gather signals from:
For each tier:
Model the financial impact:
Current state:
Customers: 200
Avg ARPU: $500/mo
Monthly Revenue: $100,000
20% Price Increase (to $600/mo):
Assume 5% churn from price increase (10 customers)
Remaining: 190 customers × $600 = $114,000/mo
Net change: +$14,000/mo (+14% revenue, -5% customer count)
Is the revenue gain worth the customer loss? Almost always yes.
When to raise prices:
When NOT to raise prices:
| Discount Type | When to Use | Max Discount | Requirements |
|---|---|---|---|
| Annual prepay | Always offer | 15-20% | 12-month commitment |
| Multi-year | Strategic accounts | 20-30% (year 2-3) | 24-36 month term |
| Volume / seats | > 50 seats | 10-20% | Minimum seat commitment |
| Startup program | Early stage, logo value | 50%+ for year 1 | Case study, reference, logo |
| Non-profit / education | Mission-aligned | 50%+ | Verification |
| Never discount because they asked: | Unless there's a strategic reason | — | — |
Price = Value delivered to the customer × Value capture rate
Example: Your tool saves a company $100k/year in engineering time.
Value capture at 25% = $25k/year price.
Not what it costs to build. Not what competitors charge. What it's worth to the customer.
| Model | When to Use | Pros | Cons |
|---|---|---|---|
| Flat rate | Simple product, single persona | Easy to sell, predictable | Leaves money on the table |
| Per-seat / per-user | Collaboration / productivity tools | Scales with adoption | Penalizes adoption, seat-capping |
| Tiered (Good-Better-Best) | Most SaaS products | Captures different WTP, upgrade path | Tier design is hard |
| Usage-based | API, AI, infrastructure products | Aligned with value delivered | Unpredictable for customers |
| Hybrid (base + usage) | Platform products | Predictable base + value-aligned variable | Complexity |
| Tier | Target Customer | Price Point | Features | Purpose |
|---|---|---|---|---|
| Good (Starter) | Individual / small team | Low | Core features, limited usage | Acquire, prove value |
| Better (Growth) | Growing team | 3-5x Good | Core + collaboration + integrations | The anchor — most will buy this |
| Best (Enterprise) | Large teams | 2-3x Better | Everything + SSO + SLA + support | Capture high WTP |
revenue-forecasting)The skill is complete when:
Can you answer "What is our price relative to the value we deliver?" and "If we raised prices by 20%, how much revenue would we gain vs lose to churn?" and "What feature would force a customer to upgrade from Starter to Growth?" If not, the pricing analysis is incomplete.
User: "Review our pricing tiers and recommend improvements. We currently have a single flat $49/mo plan with 200 customers." Expected behavior: You analyze willingness-to-pay signals from customer conversations, run a competitive audit of 5 competitors with similar products, recommend a 3-tier Good-Better-Best structure ($49 Starter / $149 Growth / $399 Enterprise), identify the feature that forces upgrades (SSO and API access for Enterprise), model the financial impact (estimated 30% increase in blended ARPU), and propose a grandfathering plan for existing $49 customers.
User: "Should we raise prices by 25%?" Expected behavior: You check the preconditions (NPS > 40, win rate > 30%, competitors charge more, product has improved), model the financial impact with churn sensitivity (assume 5-10% churn from price increase, calculate net revenue gain), recommend the timing (at renewal, not mid-contract), and propose a grandfathering period (6 months) for customers on legacy pricing.
unit-economics-analysisprofitability-analysisrevenue-forecastingstrategic-initiative-modelingbusiness-case-modelingReconciles bank accounts and credit cards monthly — matches every transaction to the ledger, resolves exceptions, tracks uncleared items, and documents the process. Use when the user mentions bank reconciliation, transaction matching, reconciling accounts, GL cash balance not matching the bank, or asks about month-end reconciliation or corporate card reconciliation.
Manages banking relationships — account optimization, fee negotiation, credit facility oversight, treasury yield, and fraud prevention. Use when the user mentions banking setup, bank fees, credit facility, treasury yield, investing excess cash, opening new accounts, or asks about banking architecture, account optimization, or fraud prevention.
Builds and maintains a 13-week rolling cash forecast — models inflows, outflows, scenario analysis, and forecast-vs-actual accuracy tracking. Use when the user mentions cash forecast, 13-week forecast, liquidity projection, cash runway, or asks about modeling cash under different scenarios or when cash runs out.
Monitors daily cash position across all accounts, flags anomalies, tracks burn rate, and produces a daily cash snapshot. Use when the user mentions cash position, daily cash check, burn rate, bank balance, or asks about unusual transactions or cash alerts.
Optimizes working capital — improves DPO, accelerates collections, manages inventory, and negotiates payment terms to maximize cash efficiency. Use when the user mentions working capital, cash conversion cycle, DPO, DSO, or asks about improving payment terms, accelerating collections, or optimizing cash tied up in operations.
Routes CFO and financial operations requests to specialized sub-skills based on user intent matching, task classification, and multi-skill chain assembly. Use when the user mentions startup CFO tasks, financial operations, reporting, fundraising questions, cash management, financial planning, strategic advisory, or asks about running any CFO-related workflow.