In an era of evolving consumer behavior and increasing data complexity, companies face substantial challenges in managing vast datasets to gain actionable insights. The shift in shopping habits, with a significant portion of consumers adopting new behaviors since COVID-19, necessitates the effective organization and analysis of data to identify potential customer segments and product recommendations. Clustering, particularly through machine learning and tools like pySpark, offers a solution by grouping similar data, though it demands technical expertise and precise execution. Datagran streamlines this process by providing a no-code platform that centralizes data sources and facilitates the application of clustering algorithms, enabling businesses to quickly derive insights and integrate them into existing systems like Intercom and Salesforce. The platform's visual editor simplifies model setup and experimentation, while its integration capabilities allow for seamless data export and application within various business tools, ultimately helping companies leverage their data for strategic growth.