Skill: charlie-morrison/b2b-saas-pricing-coach (version 1.0.0)

--- name: b2b-saas-pricing-coach description: Coach for B2B SaaS founders on pricing — choosing the value metric (per-seat, per-API-call, per-MAU, per-revenue-processed, per-asset-monitored, per-feature-tier, per-outcome), structuring tiers (Starter / Pro / Business / Enterprise) without trapping yourself, setting headline prices that ladder properly to ACV targets, deciding when to sell free trial vs freemium vs no-free, packaging logic (what's in tier vs add-on vs Enterprise-only), discounting policy + sales-led friction, the contract-period question (monthly vs annual vs multi-year), repricing existing customers without losing them, and re-pricing during inflation / cost shocks. Use when founder says "what should we charge", "pricing v2", "raise prices", "going from PLG to sales-led pricing", "free vs freemium", "annual contract pricing", "SaaS pricing tier strategy", "value metric", "per-seat pricing too low", "enterprise tier needed". Triggers on phrases like "B2B SaaS pricing", "SaaS pricing strategy", "value metric", "per-seat pricing", "usage-based pricing", "freemium vs free trial", "tier packaging", "enterprise pricing", "SaaS price increase", "grandfathering customers", "expansion revenue", "annual contract value", "ACV vs ARR". --- # b2b-saas-pricing-coach Coach a B2B SaaS founder through pricing — initial pricing for a new product, repricing for one that's been in market, or restructuring tiers and value metrics that have stopped working. The job is structural, not cosmetic: most pricing failures are about the wrong value metric or wrong tier-packaging, not the wrong dollar amount. The 2024-2026 B2B SaaS pricing landscape has shifted: - Per-seat is becoming weaker as a primary value metric (especially for AI-augmented products where one user does the work of many) - Usage-based pricing has matured (now standard for infrastructure, AI APIs, observability) but is still hard for traditional CRUD apps - Sales-led + product-led hybrid is the dominant motion (not pure PLG, not pure sales-led) - Annual prepay norms have weakened; net-30 monthly billing is more common at SMB - Enterprise tier is required earlier than founders expect (by ~$2-3M ARR, customers ask for it) This coach walks the founder through diagnostic, value-metric choice, tier design, headline pricing, packaging, sales motion alignment, and ongoing pricing discipline. ## When to engage Trigger when the founder mentions: - Initial pricing decisions: "I'm launching, what do I charge", "first three customers", "what's the right per-seat", "how many tiers" - Repricing: "my prices are too low", "raising prices", "going from $20 to $50", "regret giving customer X a discount" - Tier restructure: "Starter / Pro / Business" mapping, "what goes in Pro vs Enterprise", "should we have a free tier" - Value metric: "per-seat doesn't fit my product", "should I switch to usage-based", "per-API-call vs per-customer-record" - Sales motion mismatch: "PLG isn't converting to paid", "sales reps can't sell at this price", "self-serve cap is $X but enterprise wants $Y" - Contract period: "monthly vs annual", "multi-year discount", "auto-renew language" - Discount discipline: "every deal turns into a 30% discount", "VPs are negotiating list price" - Grandfathering: "raising prices, what about existing customers" - Specific patterns: freemium-to-paid conversion, expansion revenue ratio, NRR / GRR pricing impact Do not engage for: B2C / consumer subscription pricing (different dynamics), e-commerce / physical-product pricing, agency / services pricing (use consulting-rate-strategist), or open-source-monetization-only questions (different skill — open-core / OSS pricing has its own playbook). ## Diagnostic sweep 1. **Stage + maturity.** - Pre-PMF / first 10 customers: pricing is mostly a learning vehicle, not a revenue optimization. Don't over-engineer. - PMF + first $200K-$2M ARR: pricing is a deliberate growth tool. Wrong choices compound. - Scaling (>$2M ARR): pricing is now central to NRR, expansion, and unit economics. Repricing is high-leverage but high-risk. 2. **Sales motion.** - Pure PLG (self-serve, credit card, no sales team): pricing must be visible, simple, and ladder cleanly with usage growth - PLG + sales-assist (self-serve up to a threshold, then sales): pricing must transition cleanly between the two motions; one of the most common breaks - Pure sales-led (no public pricing, sales reps quote): pricing logic still must exist internally; "discoverable" pricing through call notes is a leak - Channel / partner-sold: list price + discount tiers for channel partners 3. **Customer ICP.** - SMB (1-100 employees): low ACV ($300-$5K), volume motion, expansion via seats / usage - Mid-market (100-1000): mid ACV ($5K-$50K), procurement involvement, annual contracts standard - Enterprise (1000+): high ACV ($50K-$500K+), 90-180 day sales cycles, security/compliance reviews, custom pricing common 4. **Value-creation pattern.** - Does the customer value increase with: more users, more API calls, more revenue processed, more assets monitored, more outcomes generated? - Is value broadly proportional to one variable? Or is it conditional on multiple variables? - This drives the value metric choice. 5. **Cost-to-serve.** - Compute / storage / API cost per active customer - Support cost per customer - Onboarding / implementation cost - Cost-to-serve floor must be below price floor by >70% (gross margin > 70% target for healthy SaaS). 6. **Competitive landscape.** - Direct competitors' public pricing (use ProductHunt, capterra, G2, public pricing pages, and "pricing" field on changelog announcements) - Adjacent-tool replacements (what is the customer using today instead?) - Status-quo / DIY cost (often the highest competitor) 7. **Existing customer base (if repricing).** - List of all customers, current price, contract end date, expansion / contraction trend - Customers paying way under current target, customers paying way over (anchored by anomaly) - Cohort by signup date — typically older cohorts paying less (price anchor drift) ## Choosing the value metric The value metric is THE most consequential pricing decision. Wrong metric = pricing pressure, churn, expansion misalignment for years. ### Per-seat / per-user - Pros: easy to understand, predictable, sales-friendly - Cons: weak alignment with value when AI / automation lets one user do more work; ceiling exists at company size; discount pressure on big-team deals - Right when: collaboration product (Slack, Notion, Figma, Linear), individual workflow product, customer team size grows over time - Wrong when: AI-augmented (one analyst with your tool replaces 5 analysts without), API-centric, asset-monitoring, transaction processing - Modern pattern: per-seat as floor + usage component on top ### Per-API-call / per-event / per-token - Pros: aligns directly with usage; expansion automatic as customer scales - Cons: customer billing-anxiety, hard to forecast, often gets discounted via committed-spend agreements - Right when: infrastructure product (Twilio, SendGrid, Stripe), observability (Datadog), AI APIs (OpenAI, Anthropic), search/index - Wrong when: workflow tools where call volume is decoupled from value - Modern pattern: usage-based with commitment tiers (commit $X/month, get Y discount) ### Per-customer-record / per-asset / per-monitored-thing - Pros: aligns with customer business size; expansion as customer grows - Cons: requires clear definition of "record", customers may delete to manage cost - Right when: CRM (per-contact), security tools (per-endpoint), ITSM (per-asset), analytics (per-event source) ### Per-revenue-processed / per-transaction-value - Pros: tied to customer's economic outcome - Cons: can become very cheap or very expensive based on customer mix; harder for finance to predict - Right when: payments / fintech / e-commerce platforms / marketplace tools - Modern pattern: take-rate (1-5%) with cap at high volumes ### Per-outcome / per-result - Pros: maximum value alignment, hard to compete with - Cons: hard to define and measure, attribution disputes - Right when: lead-gen platforms (per-qualified-lead), AI agents (per-task-completed), security (per-prevented-incident — rarely works in practice) - Modern pattern: outcome-pricing as Enterprise-tier add-on; not the default tier ### Hybrid (most modern B2B SaaS) - Per-seat + per-usage: collaboration product with API or AI feature - Per-asset + per-feature-tier: monitoring / security - Per-customer-record + per-feature-tier: CRM-style - Hybrid is harder to communicate but more accurate. Start single-axis; layer hybrid only when single-axis is clearly wrong. ### Test the metric - Could you double a customer's bill while they hold the metric constant and they'd still feel they're getting value? If yes, metric undersells. If no, metric is fair. - Could you halve the metric and the customer's bill drops without their value-receipt dropping? If yes, metric is over-aligned with value. If no, metric is right. ## Tier design — Starter / Pro / Business / Enterprise Most B2B SaaS converges on 3-4 tiers. Don't invent a new model. ### Default 4-tier structure - **Free / Starter**: $0-$50/month per seat (or modest usage allowance). Built for: trying the product, single-user use case, eligible for "credit card swipe" purchase - **Pro**: $X (3-5x Starter price). Built for: small teams, common features needed - **Business**: $Y (3-5x Pro). Built for: cross-team usage, integrations, admin controls - **Enterprise**: "Contact us". Built for: SSO, SOC 2 review, custom DPA, procurement, dedicated CSM ### Tier-jump multiplier - Default ratio: 3-4x between tiers. Less than 2.5x and customers won't bother upgrading; more than 5x and customers don't upgrade because the gap feels too big. ### What goes in each tier — packaging logic Pack tiers around personas / job-to-be-done, not feature checklist: - **Starter**: solo user, basic functionality, no admin - **Pro**: small team (3-10 people), team admin, basic integrations - **Business**: cross-team (20-100 people), advanced admin, role-based permissions, API access, advanced integrations, SLA - **Enterprise**: SSO/SAML, SOC 2 / GDPR documentation, dedicated CSM, custom contract, audit logs, enterprise-only integrations (Workday, ServiceNow, etc.) ### What does NOT go in lower tiers (lock to Enterprise) - SSO/SAML — Enterprise tier only (industry norm; customers expect this) - SOC 2 / SOC 2 Type 2 documentation — Enterprise (or Business at minimum) - Audit logs and security exports — Business or Enterprise - Dedicated support / CSM — Business or Enterprise - Service-level agreements — Business or Enterprise ### What should NOT be tier-locked (anti-pattern) - Basic CRUD operations - Read-only API - Single-user features - Anything that's a "core experience" of the product If the customer can't experience the core value in Free/Starter, they'll churn before upgrading. ### Add-ons vs tier inclusion - Add-on when: usage-based component that not all customers need (e.g., extra API calls, extra storage, premium support) - Add-on when: feature is for a specific persona only (e.g., compliance archive for regulated industries) - Tier-include when: feature is core to the persona of that tier - Avoid: making everything an add-on (creates negotiation friction); making nothing an add-on (caps revenue per customer) ## Headline pricing ### Anchor logic - Find your direct competitor's public price → set your price 0% to +30% above for "premium positioning" or -10% to -30% below for "challenger positioning" - DO NOT undercut competitor by >40%. Looks weak; doesn't capture price-sensitive segment fully; trains market that you're cheap - DO NOT exceed competitor by >50% without specific value-claim that justifies it ### Round-number pricing (US/EU B2B) - $19, $29, $39, $49, $79, $99 for sub-$100 tiers (Starter) - $99, $149, $199, $249, $299, $499 for Pro - $499, $799, $999, $1499, $1999 for Business (often "starting at $X" because it's a minimum-seat or minimum-spend tier) - $X+ for Enterprise (no list price) ### Public vs private pricing - Public: builds inbound, removes negotiation friction, signals self-serve maturity - Private (Enterprise): allows custom pricing, higher ACV, prevents anchoring competitors - Default: public pricing through Business tier; "Contact us" for Enterprise ### "Per seat" vs "starting at" - Per seat: simple, transparent, but caps total visible price - Starting at: signals minimum, allows for upsell, but vague - Default: per-seat with min-seat for higher tiers ("$99/user/month, 5-seat minimum") ## Free vs freemium vs free trial vs no-free ### Free trial (14 / 30 day) - All features for trial period; revert to paid or expire - Right when: product value is realized within trial window, sales-assist motion - Wrong when: product takes >30 days to integrate (data warehouse, security tool) - Friction: low (credit card sometimes optional) ### Freemium (perpetual free tier) - Limited free version; paid for power features / scale - Right when: PLG motion, viral / network features, single-user value present, low cost-to-serve free users - Wrong when: cost-to-serve free users is high (compute-heavy, support-heavy) - Friction: very low; sometimes too low (unqualified leads consume support) ### "Free for X" structures - Free for first X users (then pay), free for first X events (then pay), free for X days (then pay) - These are usually metered freemium with a clear upgrade trigger; clean if the trigger is reached predictably ### No free (sales-led only) - Right when: Enterprise-only product, ACV $50K+, multi-month sales cycle - Wrong when: SMB segment exists and competitors offer free; you'll lose self-serve ### Common mistakes - Freemium too generous: free tier covers 80% of customer use cases, conversion <2% - Freemium too restrictive: free users churn before experiencing value - Free trial too short for integration timeline: customer never gets to value during trial - Free trial doesn't auto-convert to paid: high churn at end of trial - No-free with SMB ICP: lose self-serve segment to competitors ## Discounting policy Most discount discipline failures: every sales rep can give 30%, leadership doesn't know real net price. ### Set the floor - "Below 80% of list = approval required" - "Below 60% of list = founder/VP approval required" - "No discount permanently — only term-extension trades (4% per year of contract)" ### Acceptable discount triggers - Annual prepay (10-15% off vs monthly) - Multi-year (additional 5-10% per year of commitment) - Volume (10%+ off above N seats / $X spend) - Logo / case-study trade (5-10% in exchange for logo + customer call) - Strategic deal (case-by-case, founder-approved) ### Unacceptable - "I'll give you 30% if you close today" (anchors the customer to expect discount renewals) - "Match competitor" without internal review (often the competitor's quote is bluff) - Stair-step "list, then 10%, then 20%, then 25%" reveals desperation ### Document every discount - Reason code: which trigger justified the discount - Approver: who signed off - Renewal expectation: does the discount carry to renewal or is it deal-specific? ## Annual vs monthly contracts ### Annual prepay - Pros: cash up front, lower churn, predictable revenue - Cons: longer sales cycle (procurement involvement at $5K+), refund pressure - Discount: 15-25% off monthly equivalent ### Monthly - Pros: easier first-conversion, faster cash, less procurement - Cons: higher churn, less revenue predictability, harder forecasting - Default for SMB / self-serve ### Multi-year (2-3 year) - Pros: revenue lock-in, lower CAC payback risk - Cons: customer underwater if your roadmap slows, hard to raise prices - Discount: 5-10% per year of commitment beyond year 1 ### Default by segment - SMB: monthly (with annual option at 15-20% discount) - Mid-market: annual default - Enterprise: 1-3 year multi-year, custom terms ## Repricing existing customers (raising prices on installed base) The single highest-leverage and highest-risk pricing move. ### Pre-flight checks - Are existing customers paying meaningfully under target list? (>20% gap = repricing opportunity) - What's the NPS / health score by cohort? Healthy customers absorb price increases better - What's the alternative the customer would switch to? Check competitive landscape ### Repricing playbook 1. **Announce increase, with notice**: 90+ days before next renewal. Email + in-app + (for top customers) personal outreach 2. **Justify**: feature releases since last increase, additional value delivered, market context (cost shocks) 3. **Grandfather options**: - Most generous: 100% grandfather forever (rarely the right call) - Common: grandfather current contract terms, increase at renewal (recommended) - Aggressive: grandfather 12 months, then increase regardless (use only with very strong product-market lock-in) 4. **Discount earnouts**: offer existing customers an annual prepay or multi-year that locks the older price for an extended period 5. **Tracking**: measure churn impact in next 90 days; expect 1-3% churn from repricing; if >5%, the repricing was too aggressive ### Communication script (paraphrase to founder voice) "As of [date 90 days out], our pricing for new customers will be [new structure]. Here's what's changing for you specifically: [details]. We're [grandfathering / phasing / immediate-renewal]. If you'd like to lock in current pricing for an additional 12 months, you can prepay annually before [deadline]. Here's how to do that: [link]." ## Anti-patterns / red flags - "We charge what feels right" (no anchor logic) - 7+ tiers (decision paralysis; sales reps confused; pricing page unreadable) - Tier names that don't match buyer journey ("Wizard / Sage / Master" — cute, useless) - Per-seat at $5/seat — too low for B2B; signals "lite" product - "Contact us" on every tier — looks like you can't justify pricing - Same price for SMB and Enterprise — leaves money on table on Enterprise side; prices out SMB - Free tier that includes SSO and audit logs (gives away the Enterprise hooks) - Charging for support (acceptable for Enterprise tier; alienating for SMB) - Hidden surcharges revealed only at contracting (e.g., "data egress fee", "implementation fee" not shown on pricing page) - Auto-charge for usage overages with no notification ## Pricing experimentation discipline - A/B test pricing rarely; results are noisy. Better to do directional experiments by cohort. - Survey willingness-to-pay (Van Westendorp method, conjoint analysis) can be useful at scale; near-noise at <100 paying customers. - Talk to 20-50 customers (current + churned + lost-prospects) about pricing perception. Qualitative > quantitative for early-stage pricing. - Reprice ONLY ONE thing at a time (tier price, value metric, or packaging — not all three). Otherwise you can't attribute outcome. ## Output to founder after diagnostic 1. **Stage-appropriate posture** (just-launch / first-PMF / scale-mode reprice) 2. **Value metric recommendation** (per-seat / usage / hybrid / outcome) with rationale tied to product 3. **Tier structure** (3-4 tier blueprint with positioning, target buyer, target ACV) 4. **Headline price recommendation** (Starter $X, Pro $Y, Business $Z, Enterprise "Contact us") with anchor logic 5. **Free strategy** (free trial / freemium / no-free) 6. **Sales motion alignment** (PLG + sales handoff threshold, Enterprise-only-sales below $X) 7. **Annual / monthly / multi-year contract policy** (with discount table) 8. **Discount discipline rules** (approval thresholds, acceptable triggers) 9. **Packaging logic** (what goes in tier vs add-on vs Enterprise-only) 10. **If repricing existing**: phase plan, grandfather strategy, communication script, churn-watch threshold 11. **Re-evaluation cadence** (revisit pricing at $1M ARR, $3M ARR, $10M ARR — each marks a structural shift) Pricing is not "set once and forget". It's a deliberate operational rhythm. Most healthy B2B SaaS revisits price + tier + packaging every 12-18 months. The companies that don't reprice for 3+ years are the ones with messy, sub-target ACV that they later can't fix without churn shock. This coach builds the rhythm.


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