suede-pricing · v2.1.0 · 2026-10-23 · sha256 a140b900a65ff70a
suede-pricing v2.1.0A
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--- name: suede-pricing description: "Suede AI pricing and packaging: chooses the value metric (seats, usage, credits, outcomes), structures tiers, compares free trial, freemium, and reverse trial, plans willingness to pay research and price increases with grandfathering, and tears down a pricing page for buyer clarity and for search and AI-assistant readability (text prices, matching schema, quotable FAQ). Returns a Pricing Decision Brief or a scored teardown. Use when deciding what to charge, restructuring tiers, pricing AI features with variable compute cost, raising prices, or fixing a pricing page that buyers or AI answers misread. NOT FOR: in-product upgrade screens (use suede-paywalls), offer bonuses and guarantees (use suede-offers), or executing billing changes." metadata: version: 2.1.0 --- # Suede Pricing & Packaging Suede AI Pricing turns verified product economics, buyer evidence, and commercial constraints into testable prices, value metrics, tiers, and migration plans. It produces a decision brief and measurement plan while keeping billing changes behind explicit approval. ## 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 Three axes, decided in this order: **packaging** (what's included per tier), **pricing metric** (what you charge for), **price point** (how much). Price sits between the next best alternative (the floor) and the customer's perceived value (the ceiling). Cost to serve is a baseline, never the basis. --- ## 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 ### Pricing AI features When a feature's cost to serve scales with model usage, flat per-seat pricing can turn heavy users unprofitable. Common structures: - **Hybrid:** a seat or platform fee with included usage, plus credits or overage beyond it. - **Credits:** one currency across AI actions, priced so the most expensive action still clears margin. Publish what a credit buys in plain words. - **Outcome-based:** charge per resolved ticket, qualified lead, or completed task, when the outcome is countable and attributable. For each, model margin at the 90th-percentile user, state included limits on the pricing page, and give buyers a usage view before the bill surprises them. ### Defaults to Beat These are the answers a model reaches for unprompted. Each is allowed, but only once you state why it beats the alternative for this product: never by default: **$9/$29/$99** (or any flat 3x ladder); **Starter/Pro/Enterprise** names that carry no product meaning; **exactly three tiers** when the buyer set is two or four; **20% off annual** as the reflex discount; **"Contact us"** on the top tier, which hides price from buyers and from the agents that now shortlist tools (see Pricing Page Teardown); **per-seat** when usage, records, or transactions track value better. --- ## 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:** - Conversion well above your own trailing baseline with no price objections in sales notes - Churn low and stable, with price rarely named as a cancel reason - Strong unit economics (payback and gross margin, from your own data) **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 **Legal notice floor for existing subscribers:** an increase on an auto-renewing plan needs clear advance notice with cancellation instructions. California's amended Automatic Renewal Law (in force July 1, 2025) requires that notice 7 to 30 days before the new price applies; contracts and other jurisdictions may require more. Current rules live in `suede-paywalls`. --- ## Pricing Page Best Practices ### Above the Fold - Clear tier comparison table - Recommended tier highlighted - Monthly/annual toggle - Primary CTA for each tier ### Common Elements - An on-page FAQ that answers cost, limits, trials, and cancellation in plain text (buyers and AI assistants both read it) - The annual saving stated in dollars and percent, whatever discount you chose - A guarantee or trial terms near the CTA - Renewal terms beside any auto-renewing plan: price, billing interval, and how to cancel ### Price transparency rules - Show the total mandatory price. In the UK, the DMCC Act has banned drip pricing of mandatory fees since April 6, 2025 ([CMA207 guidance](https://www.gov.uk/government/publications/unfair-commercial-practices-cma207)). - Auto-renewing plans need clear disclosure and consent before billing under US ROSCA and state auto-renewal laws; `suede-paywalls` holds the current US, UK, and EU subscription rules. ### Pricing Psychology Treat each as a test, using the evidence tiers in the `suede-offers` behavioral-models catalog: - **Anchoring (Robust):** show the higher-priced option or the cost of the alternative first, honestly. - **Good-better-best relativity (Context-dependent):** design the middle tier as the target and check real tier-selection data. - **Decoy tier (Contested):** a third tier can clarify the comparison; do not count on it to move choice. - **Charm vs. round endings (Context-dependent):** weak for B2B subscriptions; test rather than assume. --- ## 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 `suede-site-alchemy`), 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 JSON-LD that matches them). Hand implementation to **suede-seo-audit** (structured data and supported-schema checks), **suede-ai-seo** (extractability and AI-bot access), and **suede-competitors** for "vs" and alternatives pages that cite the same prices. **For the full 10-dimension rubric, scoring, structured-data facts, and report template:** See [references/pricing-page-teardown.md](references/pricing-page-teardown.md). --- ## Output: Pricing Decision Brief Every pricing or packaging engagement that is not a teardown returns this exact structure. Use these headings verbatim; leave a heading in with "not decided, [what's missing]" rather than dropping it. ```markdown # Pricing Decision Brief: [product] ## Value metric [What you charge for, and the one sentence proving usage of it tracks value.] ## Tier map | Tier | Who it's for | Included | Limits | Price | |------|--------------|----------|--------|-------| ## Price points + rationale [Each number, and what it is anchored to: alternative, perceived value, or research.] ## Assumptions [Every number taken on faith, flagged as assumption not measurement.] ## Validation plan [What test or research confirms each assumption, and the metric that reads out.] ## Migration + grandfathering [Existing customers: who moves, when, on what notice, and who is held.] ## What I did NOT decide [Anything left to the user: committed price, published copy, billing changes.] ``` --- ## Boundaries - Do not create or change billing products, prices, subscriptions, or customer migrations without verified live state, a maximum-cost check, and explicit approval. - Do not present willingness-to-pay, conversion, churn, or revenue impact as measured unless current research or product data supports it. - Do not publish pricing copy, choose grandfathering policy, or commit the business to a price; return a recommendation, assumptions, and validation plan for the user to decide. ## Routing - Use `suede-paywalls` for in-product upgrade and paywall experiences. - Use `suede-offers` for bonuses, guarantees, and offer framing. - Use `suede-ab-testing` to validate pricing-page or packaging hypotheses. - Use `suede-revops` for approved deal-desk and pipeline implementation.