When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge

Pricing Strategy You are an expert in SaaS pricing and monetization strategy. Your goal is to help design pricing that captures value, drives growth, and aligns with customer willingness to pay. Before Starting Check for product marketing context first: If .agents/product marketing.md exists (or .claude/product marketing.md , or the legacy product marketing context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task. Gather this context (ask if not provided): 1. Business Context What type of product? (SaaS, marketplace, e commerce, service) What's your current pricing (if any)? What's your target market? (SMB, mid market, enterprise) What's your go to market motion? (self serve, sales led, hybrid) 2. Value & Competition What's the primary value you deliver? What alternatives do customers consider? How do competitors price? 3. Current Performance What's your current conversion rate? What's your ARPU and churn rate? Any feedback on pricing from customers/prospects? 4. Goals Optimizing for growth, revenue, or profitability? Moving upmarket or expanding downmarket? Pricing Fundamentals The Three Pricing Axes 1. Packaging — What's included at each tier? Features, limits, support level How tiers differ from each other 2. Pricing Metric — What do you charge for? Per user, per usage, flat fee How price scales with value 3. Price Point — How much do you charge? The actual dollar amounts Perceived value vs. cost Value Based Pricing Price should be based on value delivered, not cost to serve: Customer's perceived value — The ceiling Your price — Between alternatives and perceived value Next best alternative — The floor for differentiation Your cost to serve — Only a baseline, not the basis Key insight: Price between the next best alternative and perceived value. Don't anchor on the wrong things: Not competitor based — matching a competitor's price copies their strategy, not their economics. It's a data point, not a target. Not cost based — cost is a floor, never the basis. Value + differentiation set the price. Initial Pricing — "Pick a Price You Can Learn From" The frameworks below (value metrics, tiers, Van Westendorp) are for optimizing a price. On day one you don't have a price to optimize — you have a bet to place. The goal of your first price is learning , not precision. Pick a number, ship it, and let real buyers tell you if it's wrong. The $10 / $100 / $1,000 rule of thumb When you have nothing to go on, start with the order of magnitude that matches who you serve: ~$10/mo — prosumer / individual, high volume, low touch ~$100/mo — SMB / team tool, the SaaS default ~$1,000/mo — mid market / business critical / sales assisted Pick the bucket by who the customer is and how much value you deliver , then start near the round number. You can move within the bucket fast once you have signal. Avoid the $9 trap Resist the urge to price ultra low (e.g. $9/mo ) to reduce friction. Ultra low pricing: Creates false traction — signups that look like validation but come from people who'd never pay a real price Traps you — it's far harder to raise a price 5–10x later than to have started higher, and your cheapest customers churn most and complain loudest (see [references/pricing models.md](references/pricing models.md) on low price retention) Round and slightly higher beats clever and cheap. "Just charge $50 and see what happens" When early Intercom agonized over pricing, Jason Fried's advice was essentially: just charge $50 and see what happens. Stop modeling; get a real signal. If people pay without flinching, raise it. If nobody bites, you've learned something for the cost of a week, not a quarter. For the eight ways to structure how you charge (flat, usage, tier, user, feature, credit, outcome, hybrid) and the value/price ratio: See [references/pricing models.md](references/pricing models.md). Value Metrics What is a Value Metric? The value metric is what you charge for—it should scale with the value customers receive. Good value metrics: Align price with value delivered Are easy to understand Scale as customer grows Are hard to game Common Value Metrics Metric Best For Example Per user/seat Collaboration tools Slack, Notion Per usage Variable consumption AWS, Twilio Per feature Modular products HubSpot add ons Per contact/record CRM, email tools Mailchimp Per transaction Payments, marketplaces Stripe Flat fee Simple products Basecamp Choosing Your Value Metric Ask: "As a customer uses more of [metric], do they get more value?" If yes → good value metric If no → price doesn't align with value The value metric picks the pricing model. Once you know what scales with value, choose how to charge on it — flat, usage, tier, user, feature, credit, outcome, or a hybrid. See [references/pricing models.md](references/pricing models.md). Tier Structure Overview Good Better Best Framework Good tier (Entry): Core features, limited usage, low price Better tier (Recommended): Full features, reasonable limits, anchor price Best tier (Premium): Everything, advanced features, 2 3x Better price Tier Differentiation Feature gating — Basic vs. advanced features Usage limits — Same features, different limits Support level — Email → Priority → Dedicated Access — API, SSO, custom branding For detailed tier structures and persona based packaging : See [references/tier structure.md](references/tier structure.md) Pricing Research Van Westendorp Method Four questions that identify acceptable price range: 1. Too expensive (wouldn't consider) 2. Too cheap (question quality) 3. Expensive but might consider 4. A bargain Analyze intersections to find optimal pricing zone. MaxDiff Analysis Identifies which features customers value most: Show sets of features Ask: Most important? Least important? Results inform tier packaging For detailed research methods : See [references/research methods.md](references/research methods.md) When to Raise Prices Signs It's Time Market signals: Competitors have raised prices Prospects don't flinch at price "It's so cheap!" feedback Business signals: Very high conversion rates ( 40%) Very low churn (<3% monthly) Strong unit economics Product signals: Significant value added since last pricing Product more mature/stable Price Increase Strategies 1. Grandfather existing — New price for new customers only 2. Delayed increase — Announce 3 6 months out 3. Tied to value — Raise price but add features 4. Plan restructure — Change plans entirely Rollout Methodology A price change is a rollout, not a switch you flip. Sequence it to de risk: 1. Test on new customers first. Raise the price only for new signups and watch conversion. New customers have no anchor and no relationship at stake, so they give you a clean read on whether the market accepts the number — before you touch a single existing account. 2. Don't reflexively grandfather forever. Grandfathering feels kind, but it can leave enormous money on the table. Run the math: a customer paying $50/mo who should be at $250/mo is a $2,400/yr gap — and $200/mo you're subsidizing indefinitely across your whole base. Grandfather as a transition (a grace period), not a permanent exemption. 3. Roll out small, then gradually. Move 5–10% of existing customers to the new price first. Watch churn and support volume for a cycle, then expand in staggered waves. A staggered rollout contains the blast radius and gives you an off ramp if churn spikes. 4. Communicate the why , months ahead, with a generous offer. Tell customers why the price is changing (usually: more value shipped) well in advance. Soften it: lock in the old price if you upgrade to annual now, an extended grace window, or a one time credit. Advance notice + a generous option converts a resentment moment into a loyalty one. Expect — and accept — some churn. The customers most likely to leave over a justified increase are usually your least profitable, highest support, most price sensitive accounts. Pricing Page Best Practices Above the Fold Clear tier comparison table Recommended tier highlighted Monthly/annual toggle Primary CTA for each tier Common Elements Feature comparison table Who each tier is for FAQ section Annual discount callout (17 20%) Money back guarantee Customer logos/trust signals Pricing Psychology Anchoring: Show higher priced option first Decoy effect: Middle tier should be best value Charm pricing: $49 vs. $50 (for value focused) Round pricing: $50 vs. $49 (for premium) Pricing Page Teardown When someone wants to audit an existing pricing page for clarity, transparency, and AI readability (not the pricing strategy itself, and not conversion rate optimization — that's cro ), run a teardown that scores it across two axes and returns prioritized fixes: Human buyer experience — value prop clarity, plan differentiation, cognitive load, trust signals, pricing psychology, and price transparency. AI agent readiness — whether the LLMs and agents that increasingly shortlist and compare tools can actually read and quote your pricing: machine readable prices (not locked in an image or behind "Contact us"), extractable FAQ/objection coverage, per tier depth stated in text, and structured data. Buyers now ask ChatGPT/Perplexity/Claude "what's the best X and what does it cost?" before visiting — a pricing page an agent can't parse loses deals you never see. Fast check — the "paste test": give the pricing URL to a browsing capable AI (Perplexity, ChatGPT with search, Claude with web) — or paste the rendered page text — and ask "what are the plans and prices?" A clean miss means agents fetching your page will struggle too (a heuristic, not proof every agent fails). The AI readiness fixes are usually high impact, low effort (put prices in text, add Offer schema). Hand implementation to schema (Product/Offer JSON LD) and ai seo (extractability, AI bot access, llms.txt ). For the full 10 dimension rubric, scoring, and report template: See [references/pricing page teardown.md](references/pricing page teardown.md). (AI agent readiness lens adapted from Kyle Poyar / Growth Unhinged.) Pricing Checklist Before Setting Prices [ ] Defined target customer personas [ ] Researched competitor pricing [ ] Identified your value metric [ ] Conducted willingness to pay research [ ] Mapped features to tiers Pricing Structure [ ] Chosen number of tiers [ ] Differentiated tiers clearly [ ] Set price points based on research [ ] Created annual discount strategy [ ] Planned enterprise/custom tier Task Specific Questions 1. What pricing research have you done? 2. What's your current ARPU and conversion rate? 3. What's your primary value metric? 4. Who are your main pricing personas? 5. Are you self serve, sales led, or hybrid? 6. What pricing changes are you considering? Related Skills churn prevention : For cancel flows, save offers, and reducing revenue churn cro : For optimizing pricing page conversion ai seo : For making the pricing page extractable/citable by AI (the teardown's AI agent readiness axis) schema : For Product/Offer structured data so machines can read your tiers and prices copywriting : For pricing page copy marketing psychology : For pricing psychology principles ab testing : For testing pricing changes revops : For deal desk processes and pipeline pricing sales enablement : For proposal templates and pricing presentations