Mastering GenAI Product Pricing: Trends, Strategies, and Case Studies

This session examines how teams are pricing GenAI features in practice, with a focus on managing cost exposure, customer expectations, and adoption dynamics. Featuring Malvika Gupta, it covers trial design, tiering approaches, and model testing strategies that support predictable growth as usage scales.

Host
Malvika Gupta

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. Challenges in Usage-Based Pricing:

GenAI pricing models often struggle with high usage costs that don't always correlate with the value customers receive. Malvika emphasized that when costs are unpredictable and not tied to tangible outcomes, customers can feel frustrated, which can limit adoption. Striking the right balance in usage-based pricing, where value and cost align better, is critical for customer satisfaction.

2. Monetizing GenAI Features

When introducing new GenAI functionality, it's essential to clearly communicate the ROI and benefits to customers. Malvika stressed using free trials or tiered pricing to give customers hands-on experience with the new features. This helps potential buyers understand the value before committing to higher costs, driving adoption while ensuring fair pricing.

3. Testing and Piloting Pricing Models

Malvika advised that businesses must thoroughly test their pricing strategies before going live. This means analyzing customer personas, predicting usage patterns, and experimenting with different models like tiered or outcome-based pricing. Testing ensures that your pricing structure works, and it helps avoid the pitfalls of unanticipated outcomes, like the challenges faced by OpenAI's $200 tier due to unexpected usage.

Recording

Mastering GenAI Product Pricing: Trends, Strategies, and Case Studies

This session examines how teams are pricing GenAI features in practice, with a focus on managing cost exposure, customer expectations, and adoption dynamics. Featuring Malvika Gupta, it covers trial design, tiering approaches, and model testing strategies that support predictable growth as usage scales.

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