.png)
Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
In the rapidly evolving insurtech landscape, Managing General Agents (MGAs) face a critical challenge: how to monetize artificial intelligence capabilities while maintaining healthy gross margins. As AI becomes less of a differentiator and more of an expected feature, finding the right pricing strategy has never been more important.
The AI Pricing Dilemma for Insurtech MGAs
Insurtech MGAs operate in a unique position in the insurance value chain. They underwrite and price risk on behalf of carriers while leveraging technology to improve efficiency. When these MGAs add AI features to their SaaS platforms, they encounter a fundamental pricing question: should AI capabilities be bundled into existing offerings, priced as premium add-ons, or structured entirely differently?
According to recent McKinsey research, companies that effectively monetize AI features see 30-40% higher revenue growth compared to those that don't. However, without a thoughtful pricing strategy, these same AI investments can quickly erode gross margins instead of enhancing them.
Value-Based Pricing: The Foundation for AI Features
Value-based pricing stands as the most effective approach for insurtech MGAs looking to price AI features. This method focuses on the economic value delivered to customers rather than development costs.
For example, if an AI-powered claims processing feature reduces an insurer's overhead by 15%, pricing should reflect a portion of that value creation. Quantifying this value requires:
- Customer interviews to understand pain points
- Data on cost savings or revenue enhancements
- Competitive analysis to determine market positioning
"Value-based pricing allows insurtech companies to capture a fair share of the value they create while providing clear ROI justification to customers," notes Simon-Kucher & Partners in their 2023 Software Pricing Study.
Usage-Based Pricing Models for AI Features
Usage-based pricing aligns particularly well with AI features in the insurtech space. This model ties pricing directly to consumption metrics that correlate with value delivery:
- Per-prediction pricing for risk models
- Per-document pricing for AI document processing
- Per-claim pricing for automated underwriting
Stripe's 2023 SaaS Pricing Report shows that companies employing usage-based pricing for AI features achieve 38% higher net revenue retention compared to those using flat subscription models.
When implementing usage-based pricing, insurtech MGAs should:
- Ensure pricing metrics align with customer value perception
- Create predictable billing through usage tiers or caps
- Provide transparency through real-time usage dashboards
Enterprise Pricing Considerations and SOX Compliance
For insurtech MGAs targeting enterprise carriers, pricing structures must accommodate complex procurement processes while maintaining Sarbanes-Oxley (SOX) compliance. This involves:
- Clear documentation of pricing decisions
- Consistent application of discounting policies
- Transparent approval workflows for non-standard deals
SOX compliance isn't just a regulatory burden—it provides an opportunity to formalize pricing governance that protects gross margins. By implementing price fences (constraints that limit who can access specific prices), MGAs can minimize margin erosion while maintaining flexibility for strategic deals.
Tiered Feature Packaging for Different Customer Segments
Rather than offering all AI capabilities universally, successful insurtech MGAs implement tiered feature packaging that matches customer sophistication and willingness to pay:
| Tier | AI Features | Target Segment |
|------|------------|----------------|
| Basic | Automated document classification | Small insurers, new MGAs |
| Professional | Risk scoring, basic underwriting automation | Mid-market insurers |
| Enterprise | Custom AI models, advanced analytics, API access | Large carriers, sophisticated MGAs |
This approach creates natural upsell opportunities while protecting the perceived value of advanced AI features. According to OpenView's 2023 SaaS Pricing Report, companies with three or more product tiers see 44% higher average contract values than those with simpler pricing structures.
Protecting Gross Margins Through Strategic Discounting
Discounting presents one of the greatest risks to gross margin erosion when pricing AI features. To protect margins while maintaining sales flexibility:
- Create a formal discounting framework with approval thresholds
- Offer alternative concessions beyond price (implementation services, extended support)
- Implement time-bound promotional pricing rather than permanent discounts
- Bundle AI features with other services to obscure individual feature pricing
"The best discounting strategies protect perceived value while giving sales teams the tools to close deals," explains pricing expert April Dunford in her analysis of B2B SaaS discounting practices.
Practical Implementation Steps for Insurtech MGAs
To implement effective AI feature pricing without eroding gross margins:
- Baseline your metrics: Document current gross margins before AI feature introduction
- Segment your customers: Identify which segments will extract the most value from AI
- Pilot pricing approaches: Test different models with a subset of customers
- Gather feedback: Collect both quantitative and qualitative responses
- Iterate quickly: Be prepared to adjust based on market response
- Track margin impact: Monitor gross margin effects across customer segments
Conclusion: Finding the Pricing Sweet Spot
The most successful insurtech MGAs approach AI feature pricing as an ongoing experiment rather than a one-time decision. By combining value-based principles with thoughtful packaging, usage metrics, and disciplined discounting, these companies can monetize AI investments without sacrificing gross margins.
The key lies in aligning pricing with genuine customer value creation while maintaining the flexibility to adapt as the market evolves. For insurtech MGAs willing to invest in sophisticated pricing strategies, AI features represent not just a competitive necessity but a significant opportunity for margin enhancement.