Case Study: Podimo improves search relevance with STX Next's machine learning and semantic search

Podimo improves search relevance by 27% with STX Next

Podimo, a Danish leader in the podcast and audiobook industry, sought to revolutionize their search functionality to better serve their users. Their existing system delivered irrelevant results due to a limited understanding of queries and content semantics. They partnered with STX Next to address these challenges with advanced machine learning.

STX Next implemented a solution combining a Machine Learning model trained on user interactions, a semantic search model for understanding query context, and a conversational search assistant. This integration re-ranked results for superior accuracy and relevance. The project resulted in a 27% improvement in the average position of clicked shows, a 3.5% increase in the conversion rate for searches, and a 1.3% rise in meaningful listens exceeding five minutes, significantly enhancing the user experience for Podimo.

Podimo