AI Use Cases
synvert Accelerators
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Cloud data & AI are revolutionizing retail by optimizing processes, providing customers with personalized experiences, and making supply chains more efficient. Companies benefit from data-driven decisions, accurate sales forecasts, and optimized inventory strategies.
Artificial intelligence analyzes customer data in real time to create tailored product recommendations and improve the customer journey. Automated pricing and dynamic inventory management increase efficiency and profitability. Machine learning models optimize demand planning, while AI-based fraud detection minimizes payment defaults. Process mining and intelligent automation help to streamline operations and reduce costs.
With over 30 years of experience and more than 3.000 successfully implemented projects, synvert is the ideal partner for companies that want to drive their digital transformation with cloud data & AI.
Implemented a staged forecasting model to continuously predict total demand in online commerce.
Automated predictive model for pricing optimisation over different sales periods for a multinational retailer headquartered in Europe.
Creation of a web application to provide a platform for internal organisation usage, that provides a leading European multinational clothing retailer with tools to handle their data and application governance.
Performing analysis, design, and implementation of a BI platform in Azure for an online classifieds conglomerate, including design and implementation of relevant Tableau reports with data story telling.
CRM consolidation into a single Azure data warehouse with upgraded reporting, for a major online classifieds conglomerate.
Development of a system in which promotional offers could be both personally tailored and reliably delivered to customers. The system operates on a points-based system in which customers who share more data by participating more are rewarded.
Expansion of the data warehouse, which supports the planning and optimisation of the staffing of broadcasting slots with articles from the product range
Design and implementation of a Hadoop-based system for the analysis of receipt data. The first use cases are customer segmentation and assortment analysis. Further aspects are the development of a near-real-time supply of receipt data and the analysis of user data from the app.
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