gtm-technical-product-pricing

Solid

Pricing strategy for technical products. Use when choosing usage-based vs seat-based, designing freemium thresholds, structuring enterprise pricing conversations, deciding when to raise prices, or using price as a positioning signal.

AI & Automation 34,233 stars 4188 forks Updated today MIT

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# Technical Product Pricing ## Initial Assessment Before recommending pricing, understand: 1. **Product type**: API/platform, developer tool, SaaS application, infrastructure? 2. **Current pricing**: What do you charge now? How long has it been this way? 3. **GTM motion**: Self-serve, sales-assisted, enterprise, or hybrid? 4. **Cost structure**: What's your marginal cost per customer/user/unit? 5. **Competitive landscape**: What do alternatives cost? (Including "do nothing") --- ## Core Frameworks ### 1. The Price Increase Nobody Noticed (You're Probably Underpriced) **The Pattern:** Platform company, growth stage. Pricing hadn't changed since launch. Enterprise customers paying $15K/year for a product saving them $200K+ in engineering time. Leadership debate: "If we raise prices, we'll lose customers." **What actually happened:** Raised enterprise tier from $15K to $45K/year. Added dedicated support, SSO, audit logs to justify the jump. Lost: 0 enterprise customers. Zero. Gained: 3x revenue per enterprise account. Plus the customers who stayed started taking the product more seriously — higher adoption, more internal champions, more expansion. **Why This Happens:** Technical founders anchor pricing to cost ("it costs us $X to serve them, so we charge $2X"). Enterprise buyers anchor pricing to value ("this saves us $200K, so $45K is cheap"). **The Pricing Sanity Check:** For every customer segment, calculate: ``` Value Ratio = Customer's alternative cost / ...

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Author
github
Repository
github/awesome-copilot
Created
11 months ago
Last Updated
today
Language
Python
License
MIT

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