Smart platform experiment cycle (SPEC): a process to design, analyze, and validate digital platforms

Abstract

Abstract Digital platform business models are disrupting traditional business processes and reveal a new way of creating value. Current validation processes for business models are designed to assess pipeline business models. They cannot grasp the logic of digital platforms, which increasingly integrate Artificial Intelligence (AI) to ensure success. This study developed a new validation process for early market validation of digital platform business models by following the Design Science Research methodology. The designed process, the Smart Platform Experiment Cycle (SPEC), is created by combining the Four-Step Iterative Cycle of business experiments, the Customer Development Process, and the Build-Measure-Learn feedback loop of the Lean Startup approach and enriching it with the knowledge of digital platforms. It consists of five iterative steps showing the startup how to design their platform business model and corresponding experiments and how to run, measure, analyze, and learn from the outcomes and results. To assess its efficacy, applicability, and validity, SPEC was applied in the German startup GassiAlarm, a service marketplace business model. The application of SPEC revealed shortcomings in the pricing strategy and highlighted to what extent their current business model would be successful. SPEC reduces the risk of building a product or service the market deems redundant and gives insights into its success rate. More applications of the SPEC are needed to validate its robustness further and to extend it to other types of digital platform business models for improved generalization.