Insights from our SaaS Monetization Benchmarking Survey: What Top Performers Do Differently

Based on Monevate’s SaaS benchmarking data, this session highlights the structural and strategic patterns that differentiate top-performing companies. It contrasts how faster-growing firms approach pricing decisions, packaging, and execution, giving you concrete reference points to evaluate where your own model is strong and where it may be holding growth back.

Host
James Wilton

Table of Contents

Duolingo's AI Strategy
Key Learnings from Duolingo's approach
Looking Forward - Strategic Pricing Priorities for Duolingo
Example H5

Key Takeaways

1. The SaaS pricing model is shifting - but not uniformly

Per-seat and static tiered models are being reassessed. While usage-based and hybrid pricing are gaining traction, their success depends on aligning pricing with actual value delivered. Top performers are adapting their models to reflect how their product creates and scales value, not just what’s easy to meter.

2. The biggest sources of value leakage are predictable - and avoidable

Many companies are under-monetizing AI features, avoiding price changes due to internal friction, or bundling poorly. Leading teams are more deliberate: pricing new capabilities early, reviewing renewal structures, and ensuring packaging reflects differentiated value.

3. Execution matters more than theory

Top performers have clear pricing ownership, cross-functional alignment, and better internal tooling. Pricing is treated as a strategic discipline, not a one-off exercise. The difference isn’t just in the model, but in how consistently it’s communicated, governed, and optimized.

Recording

Insights from our SaaS Monetization Benchmarking Survey: What Top Performers Do Differently

Based on Monevate’s SaaS benchmarking data, this session highlights the structural and strategic patterns that differentiate top-performing companies. It contrasts how faster-growing firms approach pricing decisions, packaging, and execution, giving you concrete reference points to evaluate where your own model is strong and where it may be holding growth back.

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