The Challenge

Medisafe’s legacy pricing model was too broad for the commercial reality of the business.

The same core pricing logic was being stretched across very different customer types, use cases, and deal sizes. That created friction in sales conversations, made pricing harder to defend, and reduced clarity for buyers evaluating the platform.

The deeper issue was that monetization had not evolved with the product.

As Medisafe introduced more advanced AI-driven capabilities and expanded across increasingly complex enterprise environments, the pricing structure was no longer strong enough to reflect:

• differences in buyer value across pharma, providers, and payers
• variation in deployment size and commercial scope
• the need to monetize AI capabilities as real business value, not background product language
• the importance of a consumption-based logic that could scale more naturally with usage, complexity, and account expansion
• the need to reduce manual pricing customization and move toward a more repeatable enterprise model

The result was a pricing structure that made deals harder to explain, harder to standardize, and harder to scale.

The Pricing Redesign

SaaS Pricing Consultants worked with Medisafe to redesign the pricing architecture around three core principles.

1 – Stronger buyer alignment

The new model introduced clearer segmentation across key buyer groups, including pharmaceutical companies, healthcare providers, and payers. Pricing was better aligned to customer profile, deployment context, and strategic value, creating a stronger fit between how different enterprise customers experienced value and how that value translated commercially.

2 – Clearer AI monetization

Medisafe’s platform included meaningful AI-driven capabilities, but the old pricing model was not fully translating that into commercial terms.

The redesign helped reposition AI from a vague innovation layer into a monetizable value layer. Instead of leaving advanced capabilities buried inside the offer, the new architecture made it easier to connect AI-powered functionality to differentiated value in the buyer conversation.

That mattered because enterprise buyers do not pay more just because a product uses AI.

They pay more when the offer makes it clear why the value is greater, where the impact comes from, and how that value fits their environment.

3 – A more scalable consumption-based foundation

As enterprise deployments expanded, Medisafe needed pricing that could scale more naturally with real commercial usage.

The redesigned structure introduced a stronger consumption-based logic so pricing could better reflect differences in scope, usage intensity, and value delivery across accounts. That created a more scalable commercial foundation by allowing the model to expand more cleanly with larger deployments, broader adoption, and growing customer value.

The goal was not to make pricing more complicated.

It was to build a system that was easier to sell, easier to understand, and more capable of scaling with the business.

The Work

The project included:

• pricing and packaging redesign
• analysis of customer segments, usage patterns, and deal structure
• competitive and market review
• design of a more scalable enterprise pricing model
  stronger pricing logic for AI-powered capabilities
• development of pricing tools and messaging support for the sales team

This was not just a pricing exercise.

It was a commercial redesign aimed at improving how Medisafe translated product value into price across enterprise healthcare buyers.

The Results

The new pricing architecture produced measurable commercial impact:

• 26% increase in average deal size
• 41% improvement in closing rate
• 30% reduction in sales cycle time

Beyond the headline metrics, the new structure gave Medisafe a stronger monetization foundation for enterprise growth.

It created clearer value communication, reduced pricing friction, improved consistency in sales execution, and established a more scalable pricing model for an AI-powered platform operating across complex healthcare environments.