In the retail sector, Cloud Data & AI play a crucial role and offer numerous benefits for companies. They provide a better understanding of customers’ behavior and preferences by providing comprehensive insights into their buying habits and interactions with the company. Based on this, personalized offers and marketing strategies can be developed to attract and retain customers. Cloud Data & AI can optimize supply chains and manage inventory efficiently. By analyzing data such as inventory levels, sales figures and delivery times, better forecasts can be made and processes automated to avoid supply bottlenecks and overstocks.
In addition, AI can increase operational efficiency and reduce costs; by analyzing data on operating costs, human resources and supply chains, companies can identify potential areas for improvement and take appropriate action.
Overall, Cloud Data & AI in retail offer valuable insights and opportunities to enhance business processes, leading to an important competitive advantage over your rivals.
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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