pricing-strategy-advisory

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"]

Pricing Strategy Advisory

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.

Purpose

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.

When to Use

• "How should we price our product?"
• "Review our pricing tiers / packaging"
• "Should we raise prices?"
• "Competitive pricing analysis"
• "Model the impact of a price change"
• "Design our enterprise pricing"
• "Good-better-best tier strategy"

Inputs Required

1. Current pricing — tiers, features per tier, pricing model (per-seat, usage, flat), current prices.
2. Competitor pricing — public pricing pages, sales intel, customer feedback.
3. Customer data — willingness to pay signals, feature adoption by tier, churn reasons related to pricing.
4. Unit economics — from unit-economics-analysis (CAC, LTV, gross margins per segment).

Quick Reference

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

Procedure

1. Competitive Pricing Audit

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

2. Willingness-to-Pay Signal Analysis

Gather signals from:

• Sales conversations ("it's too expensive" vs "that seems reasonable")
• Win/loss analysis (did we lose on price?)
• Feature adoption (which features do people upgrade for?)
• Customer segments (do SMB and enterprise value things differently?)

3. Tier Design Recommendations

For each tier:

• Which features create the upgrade pull?
• What's the "must-have" that forces the upgrade? (SSO, reporting, API access, seats)
• Are the jumps between tiers too small (nobody upgrades) or too big (churn at renewal)?

4. Price Increase Modeling

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:

• NPS > 40 (customers are happy)
• Win rate > 30% (you're winning enough)
• Competitors charge more (you're underpriced)
• Product has materially improved since last pricing change

When NOT to raise prices:

• Churn is already high
• Major product gaps vs competitors
• Just lost a round of funding (looks desperate)
• During a competitor's launch or price war

5. Discounting Framework

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	—	—

Pricing Frameworks

Value-Based Pricing (the goal)

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.

SaaS Pricing Models

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

The Good-Better-Best Framework

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

Output Format

• Competitive pricing landscape
• Recommended pricing model and tier structure
• Price increase impact analysis (with churn sensitivity)
• Discount framework and approval guidelines
• Revenue forecast under new pricing (from revenue-forecasting)

Done Criteria

The skill is complete when:

1. Competitive pricing audit is completed for at least 3-5 competitors.
2. Willingness-to-pay signals are analyzed from sales and customer data.
3. Tier structure is recommended with clear upgrade drivers between tiers.
4. Price increase impact is modeled with churn sensitivity.
5. Discounting framework is defined with approval guidelines.
6. A clear recommendation is provided with supporting data.

Pitfalls

1. Underpricing by 30-50% — most startup founders are afraid of pricing. The data consistently shows that startups undercharge significantly. Price pushback from 10-20% of deals is a sign you're in the right range.
2. Designing pricing in a vacuum — pricing decisions made without competitor analysis, willingness-to-pay data, or unit economics inputs are guesses. All three data sources are necessary.
3. Too many tiers — more than 3-4 tiers paralyze buyers. Good-Better-Best is the proven framework for a reason.
4. Putting enterprise pricing on the website — "Contact us" for enterprise. Pricing is part of the negotiation. Putting it on the website gives away leverage.
5. Never raising prices — SaaS companies that don't raise prices annually leave 5-15% revenue on the table every year. Annual price increases are standard and expected.

Heuristics

• Most startups undercharge by 30-50%: founders are afraid of pricing. Push them.
• If you're not losing 10-20% of deals on price, you're too cheap: price pushback is a sign you're in the right range.
• Raise prices annually: 5-15% per year is standard in SaaS. Inflation + more value = justified.
• Grandfathering is a tactic, not a strategy: eventually, bring everyone to the new pricing. Sunset old plans.
• Enterprise pricing should NOT be on your website: "Contact us" for enterprise. Pricing is part of the negotiation.

Edge Cases

• Freemium to paid conversion: the free tier must be genuinely useful but limited enough to create upgrade urgency. The free-to-paid conversion rate is the critical metric.
• International pricing: PPP-adjusted pricing is complex. Typically, price at 60-80% of US for EU, 40-60% for emerging markets.
• Platform / marketplace pricing: take-rate pricing (X% of transaction). Model the take-rate sensitivity carefully.
• Bundling multiple products: bundling increases stickiness but can mask which products are actually valuable.

Verification

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.

Example

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.

Linked Skills

• Customer lifetime value & willingness to pay → unit-economics-analysis
• Profitability impact by segment → profitability-analysis
• Revenue forecast with new pricing → revenue-forecasting
• Strategic moves (new tier launch) → strategic-initiative-modeling
• Business case for pricing change → business-case-modeling