Case Studies

AI Startup Uncovers Pricing Blind Spots Through Structured Health Assessment

A growing AI company offering a conversation intelligence and coaching platform had reached an inflection point in growth. While product usage and customer feedback were positive, pricing decisions had evolved incrementally without a unifying framework. Leadership suspected that pricing maturity had not kept pace with product and go-to-market evolution but lacked a structured way to diagnose the problem. Key challenges: - No objective view of overall pricing maturity - Limited visibility into pricing blind spots across teams - Difficulty connecting pricing decisions to business outcomes - Fragmented internal opinions on what needed fixing first

AI SaaS Improves Conversion with Pricing Page Optimisation

An early-stage AI SaaS company offering an immigration and relocation intelligence platform was seeing steady traffic to their pricing page, but conversions were lagging behind expectations. While demand was strong, users were hesitating at the final step. They suspected pricing clarity issues but lacked a structured way to diagnose what was going wrong. Key challenges: - Unclear value communication across pricing tiers - Feature-heavy plans without strong differentiation - No explicit upgrade triggers from free to paid - Pricing page optimised for features, not buyer intent

ERP Company Increases ARPU by 35%

A mid-market ERP provider was struggling with commoditization pressure. Their pricing hadn't changed in 4 years, and they were losing deals to cheaper alternatives while their most valuable customers were undermonetized. Key challenges: - Single-tier pricing couldn't capture value from enterprise customers - Sales team had no guidance on discounting - Implementation costs weren't being recovered - Churn was increasing among smaller customers

Web3 Startup Launches with Optimized Monetization

A well-funded Web3 startup was preparing to launch their developer platform. They had strong technology but no pricing strategy. With crypto market volatility, they needed a model that would work regardless of token prices. Key challenges: - No precedent for their specific use case - Uncertainty about willingness to pay in Web3 - Need to balance growth with revenue - Token vs. fiat payment complexity