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Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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Enterprise pricing for AI products requires strategic thinking and alignment with your go-to-market strategy. Here's a comprehensive approach to effectively price your AI product:
Strategic Considerations
- Align with Your Go-to-Market Strategy
- Ensure your pricing model supports your enterprise sales motion
- Structure pricing for high Average Selling Price (ASP) solutions
- Create pricing that reduces sales friction and customer objections
- Choose the Right Pricing Metrics
- Consider combination metrics that reflect both value and usage
- For AI products, potential metrics include:
- Users/seats combined with company size/revenue
- Usage-based components (API calls, compute resources)
- Value metrics tied to business outcomes
- Package Strategically
- Rationalize your offering to clear, distinct packages
- Map features to enterprise needs and pain points
- Implement anti-commoditization packaging to maintain margins
Implementation Approach
- Pricing Model Research
- Benchmark your pricing against industry standards
- Analyze tier/package performance across metrics like average deal size
- Evaluate price bearing capability across different segments
- Specific for GenAI Products
- Consider consumption-based components for unpredictable usage patterns
- Balance predictability (subscription) with usage flexibility
- Create upsell paths as customers expand their AI implementation
- Enterprise-Ready Pricing Elements
- Design contract terms that encourage account growth
- Develop clear discounting guidelines for enterprise deals
- Create pricing that scales with customer value realization
Case Study Example
A $10M ARR SaaS company transformed their pricing by:
- Aligning pricing with their enterprise-focused GTM strategy
- Rationalizing four packages to two with strategically remapped features
- Creating a combination pricing metric based on users and company revenue
This resulted in their first consistent pricing model with improved sales effectiveness and reduced customer objections.
Remember that successful enterprise AI pricing requires cross-functional alignment, sales enablement tools, and clear implementation planning to ensure organizational adoption and customer acceptance.