Use this skill when designing pricing models, packaging products into tiers, building freemium funnels, implementing usage-based billing, structuring enterprise pricing, or running price tests. Triggers on pricing pages, monetization strategy, willingness-to-pay research, price sensitivity analysis, free-to-paid conversion, seat-based vs consumption pricing, and A/B testing prices.
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Use this skill when designing pricing models, packaging products into tiers, building freemium funnels, implementing usage-based billing, structuring enterprise pricing, or running price tests. Triggers on pricing pages, monetization strategy, willingness-to-pay research, price sensitivity analysis, free-to-paid conversion, seat-based vs consumption pricing, and A/B testing prices.
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Pricing Strategy
A practical framework for designing, packaging, and testing software pricing. Pricing
is the highest-leverage growth lever most teams ignore - a 1% improvement in pricing
yields 2-4x the revenue impact of a 1% improvement in acquisition. This skill covers
the full pricing lifecycle: choosing a model (freemium, usage-based, seat-based, flat),
packaging features into tiers, building enterprise plans that close six-figure deals,
and running price tests without torching customer trust. Agents can use this to draft
pricing pages, evaluate model trade-offs, design packaging, and structure experiments.
When to use this skill
Trigger this skill when the user:
Is designing or redesigning a pricing page or pricing model
Needs to decide between freemium, free trial, usage-based, or seat-based pricing
Wants to package features into tiers (good/better/best)
Is building an enterprise tier and needs to structure negotiation levers
Wants to run a price test or willingness-to-pay survey
Needs to set or change prices for a SaaS product
Is evaluating free-to-paid conversion rates or upgrade triggers
Asks about price anchoring, decoy pricing, or price discrimination strategies
Do NOT trigger this skill for:
Billing system implementation details (use a payments or Stripe skill)
General business strategy or go-to-market planning unrelated to pricing
Key principles
Value before price - Price is a function of perceived value, not cost. Before
setting any number, articulate the measurable outcome customers get. If you cannot
name the outcome, you cannot defend the price.
Packaging is strategy, pricing is tactics - Which features go in which tier
matters more than the dollar amount on each tier. Get packaging wrong and no price
point saves you. Get packaging right and you have room to adjust prices later.
One metric to rule them all - The best pricing models charge on a single value
metric that scales with the customer's success. Seats work when every user gets
equal value. API calls work when consumption correlates with revenue. Pick the
metric where "more usage = more value for the customer."
Segment by willingness to pay, not by cost to serve - Tiers should separate
customers who get different amounts of value, not customers who cost you different
amounts. A startup and an enterprise both use the same servers, but the enterprise
extracts 100x more value - price accordingly.
Test prices, not just features - Most teams A/B test buttons and headlines but
never test prices. Price sensitivity data is the highest-signal input to pricing
decisions and can be gathered safely with the right methodology.
Core concepts
Value metric is the unit you charge on - seats, API calls, messages sent, revenue
processed, GB stored. The ideal value metric is easy to understand, scales with customer
value, and is predictable enough for customers to budget. Slack charges per seat. Twilio
charges per message. Stripe charges per transaction. Each aligns price with the value
the customer receives.
Packaging is the act of grouping features into tiers. The standard model is
good/better/best (three tiers). The middle tier should be the target - it is where
60-70% of customers should land. The top tier exists to make the middle tier look
reasonable (anchoring) and to capture high-willingness-to-pay customers.
Price fences are the criteria that separate tiers. They must be objective and hard
to game. Good fences: number of seats, API volume, data retention period, SLA level.
Bad fences: company size (self-reported), "startup" vs "enterprise" (subjective).
Willingness to pay (WTP) is the maximum price a customer segment will accept. It
varies dramatically by segment. You discover WTP through Van Westendorp surveys,
Gabor-Granger analysis, or conjoint studies - never by asking "what would you pay?"
directly.
Common tasks
Design a three-tier SaaS pricing page
Framework: Good / Better / Best
Name tiers by persona, not size - "Starter / Team / Business" beats
"Small / Medium / Large." Names signal who the tier is for.
Anchor with the top tier - Show the most expensive tier first (left or top).
It reframes the middle tier as reasonable.
Highlight the target tier - Use a "Most Popular" badge on the middle tier.
60-70% of signups should land here.
Limit to 3-4 tiers - More tiers create decision paralysis. If you need a
fourth, make it "Enterprise - Contact Sales."
Feature differentiation checklist:
Free/Starter: core value proposition, hard usage cap, no integrations
[Tier name]
[One sentence: who this is for]
[$X / mo per seat]
[3-5 feature bullets, starting with the most differentiating]
[CTA button]
Choose between freemium and free trial
Factor
Freemium
Free Trial
Best when
Product has viral/network effects, low marginal cost
Product value is obvious but needs time to discover
Conversion rate
2-5% free to paid (typical)
15-25% trial to paid (typical)
Risk
Freeloaders consume resources without converting
Short trial may not show full value
Examples
Slack, Dropbox, Figma
Salesforce, HubSpot, Netflix
Decision rule: Use freemium when free users create value for paid users (network
effects, content creation, referrals). Use free trial when the product's value requires
sustained use to appreciate but does not benefit from a large free base.
Hybrid option: Free trial of the paid tier, then downgrade to a limited free tier.
This shows users the full value, then lets them keep a foothold. Zoom does this well.
Implement usage-based pricing
When to use: The customer's value scales linearly with consumption, and usage is
measurable and predictable. Good fits: API platforms, cloud infrastructure, messaging
services, data pipelines.
Structure options:
Pure pay-as-you-go - No commitment, pay per unit. Low barrier, but revenue is
unpredictable. Best for developer tools (Twilio, AWS Lambda).
Committed use + overage - Base commitment at a discount, then per-unit overage.
Gives revenue predictability. Best for mid-market and enterprise (Snowflake).
Tiered volume - Price per unit drops as volume increases. Incentivizes growth.
Best when you want customers to consolidate spend (Stripe's volume discounts).
Implementation checklist:
Pick one value metric (not two or three)
Set a minimum monthly commitment (even $0 with a credit card on file)
Provide a usage dashboard and spend alerts
Offer committed-use discounts for annual contracts
Bill in arrears with a clear invoice breakdown
Gotcha: Usage-based pricing makes revenue forecasting harder. Pair it with annual
commitments or minimum spend agreements for enterprise customers.
Structure an enterprise tier
Enterprise pricing is not a number on a webpage - it is a negotiation framework.
Must-have enterprise features (price fences):
SSO / SAML integration
Audit logs and compliance certifications (SOC 2, HIPAA)
Dedicated support (named CSM, SLA with uptime guarantee)
Custom contracts and invoicing (NET 30/60/90)
Data residency and security controls
Admin controls, role-based access, and user provisioning (SCIM)
Pricing levers for negotiation:
Seat count - volume discount at 100+, 500+, 1000+ thresholds
Contract length - 10-20% discount for multi-year commits
Payment terms - annual upfront is default; quarterly or monthly at a premium
Usage tiers - committed volume at lower per-unit cost
Professional services - onboarding, migration, custom integrations as add-ons
Pricing floor rule: Never discount more than 30% off list price. If the customer
needs more than 30% off, restructure the deal (fewer seats, shorter term, fewer
features) rather than deepening the discount. Deep discounts set bad renewal precedents.
Run a price test
Method 1: Van Westendorp Price Sensitivity Meter
Ask four questions to a sample of target customers:
At what price would this be so cheap you would question quality? (Too Cheap)
At what price is this a bargain - a great value? (Cheap)
At what price is this getting expensive but you would still consider? (Expensive)
At what price is this too expensive - you would never buy? (Too Expensive)
Plot the cumulative distributions. The intersection of "Too Cheap" and "Expensive"
gives the optimal price point. The range between "Cheap/Too Expensive" intersection
and "Too Cheap/Expensive" intersection gives the acceptable price range.
Method 2: A/B test with geographic or cohort splits
Never show different prices to the same market simultaneously - it destroys trust if
discovered.
Safe approaches:
Test in different geographic markets (e.g., US vs UK)
Test on new signups only (grandfather existing customers)
Test different packaging (features per tier) at the same price
Use time-based splits (this month vs next month for new cohorts)
Method 3: Gabor-Granger for demand curve
Show a price and ask "would you buy at this price?" Vary the price across respondents.
Plot price vs % who would buy. Find the revenue-maximizing point (price * conversion).
Golden rule: Never test prices on existing paying customers. Only test on new
prospects or in new markets.
Set initial prices for a new product
Step 1 - Competitor anchoring: List 3-5 competitors and their pricing. You are
not matching them - you are using them to understand the market's reference frame.
Step 2 - Value quantification: Calculate the economic value your product creates.
If your tool saves 10 hours/month of a $100/hr employee's time, the value created is
$1,000/month. Price at 10-20% of value created.
Step 3 - Segment analysis: Identify 2-3 customer segments by willingness to pay.
Map features to segments. Price the top segment first, then work down.
Step 4 - Round and simplify: End prices in 9 for consumer ($49, $99, $199). Use
round numbers for enterprise ($500, $1,000). Never use decimal prices for SaaS.
Step 5 - Launch high, discount down: It is dramatically easier to lower prices
than raise them. Launch at the top of your acceptable range and adjust based on
conversion data. A product that is "too expensive" still gets feedback; a product
that is "too cheap" leaves money on the table silently.
Design upgrade triggers for freemium
Upgrade triggers are the moments when a free user hits a limit that motivates them
to pay. Design these intentionally.
Effective triggers:
Usage limits - "You have used 95% of your free storage" (Dropbox)
Feature gates - "Upgrade to unlock advanced analytics" (Mixpanel)
Collaboration gates - "Add more than 3 team members" (Notion)
Time-based - "Your premium trial ends in 3 days" (LinkedIn)
Export/integration gates - "Export to CSV requires Pro" (Airtable)
Design rules:
Let users experience the core value loop before hitting the gate
Show what they are missing (preview locked features, not just a lock icon)
Trigger upgrade prompts at moments of high engagement, not frustration
Make the upgrade path one click - pre-select the right tier based on their usage
Anti-patterns / common mistakes
Mistake
Why it's wrong
What to do instead
Pricing based on cost-plus
Your costs are irrelevant to what customers will pay; you leave massive value on the table
Price based on value delivered, use competitor pricing as reference frame
Grandfather existing customers or give 90+ days notice with clear value justification
Hiding pricing entirely
Creates friction; self-serve buyers leave; only works for true enterprise sales
Show pricing for self-serve tiers; use "Contact Sales" only for enterprise
Gotchas
Grandfathering existing customers breaks new pricing model adoption - Grandfathering legacy pricing protects current customers but creates a permanent two-tier customer base where your highest-engaged users are also your lowest-paying. Every new feature you ship subsidizes old pricing. If you need to change pricing, give existing customers a generous migration window (90-180 days) and an incentive to switch, but set a hard cutover date.
Usage-based pricing without spend alerts causes customer shock and churn - Customers who receive a bill 5x what they expected due to unanticipated usage spikes rarely renew, regardless of the value delivered. Every usage-based product must provide real-time usage dashboards and configurable spend alerts before GA. Pricing surprise is a top cause of B2B churn.
Free trial that defaults to paid after expiry without clear warning violates trust - Auto-converting a trial to a paid subscription when no credit card was required at signup, or failing to send a prominent reminder before billing begins, generates chargebacks, negative reviews, and potential regulatory exposure (ROSCA in the US). Always send email reminders at 7 days and 1 day before any trial-to-paid conversion.
Showing annual pricing as "per month" without making the billing frequency obvious is deceptive - "$49/month billed annually" shown as just "$49/mo" in a pricing table misleads customers into expecting monthly billing. Many buyers discover the $588 charge on their card and dispute it. Always show both the monthly equivalent AND the total annual amount prominently in the pricing UI.
Price testing on logged-in users who can compare notes destroys trust - Unlike geographic or cohort splits, showing different prices to users in the same market who know each other (B2B teams, developer communities) will be discovered and publicized. The reputational damage from a perceived price-fixing discovery exceeds any revenue optimization gain.
References
For detailed frameworks on specific pricing sub-domains, read the relevant file
from the references/ folder:
references/pricing-models.md - deep comparison of all pricing model types
(flat-rate, per-seat, usage-based, hybrid, reverse trial) with decision trees
and real-world examples
references/price-testing.md - detailed methodology for Van Westendorp,
Gabor-Granger, conjoint analysis, and safe A/B testing approaches with
sample survey templates
Only load a references file when the current task requires it - they are long
and will consume context.
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