This study examines the application of the Good-Better-Best (G-B-B) pricing model to enhance the pricing strategy of an AI-as-a-Service (AIaaS) startup. The company’s existing pricing model, tailored to a single customer segment, proved insufficient as customer usage exceeded expectations. Using an Action Design Research (ADR) framework, the research developed a dynamic, value-based pricing model informed by detailed customer usage data. By analyzing detailed usage logs, the study designed a new tiered pricing structure that more closely aligns with perceived customer value. The findings show that the G-B-B model can drive both revenue growth and customer satisfaction by accurately reflecting the software’s value across diverse user segments. Data analysis was crucial in identifying key usage patterns and feature engagement, ensuring the new pricing model addressed real customer behavior. Additionally, the study introduces an innovative virtual currency payment system, further personalizing the pricing model for users. Beyond AIaaS, the research suggests broader applications of the G-B-B approach, highlighting its adaptability to digitally enabled product-service systems (PSS). Ultimately, the study bridges theory and practice, demonstrating how data-driven insights can inform pricing models and offering a blueprint for AIaaS companies seeking to refine their pricing strategies.