Why DataRobot for Retailers?
Exceptional Customer Experiences with Hyper-Personalization
DataRobot gives retailers a scalable way to hyper-personalize every touch. Build hyper-accurate and actively monitored customer propensity models that allows you better understand CLTV, cross-sell, upsell, and churn for each of your customers. With prediction explanations, retailers can get individual customer insights and proactively adjust touch points or advertisements to influence their behavior.
Improve Operations Across Every Point Of Your Value Chain
Optimize efficiency across your entire operations. With DataRobot you can break down prediction silos and ensure everyone is using the same forecasts and predictions from logistics and supply chain, to merchandising, marketing, financial planning, and elsewhere. DataRobot gives you the flexibility to easily deploy any model – even those built outside of DataRobot to the business applications your business stakeholders use everyday.
Sense Changing Market and Customer Dynamics
In today’s environment it’s no longer effective to put a model into production and ignore the changing retail landscape. Now, retailers can get real-time insights into changing customer behaviors and supply chain risks through active model monitoring. This allows for fast changes to product and inventory mix, pricing, and promotions across channels. Now you can easily stay ahead of changing consumer buying behaviors and optimize pricing based on current conditions.
Precise and Fine-Grained Forecasts
Building forecasts at the individual item-store level has never been easier nor more precise. DataRobot makes it easy to not just build hyper-granular forecasts, but maintain them in production. With DataRobot’s time series, dynamic time warping helps you handle irregular series or seasonal forecasts with ease, while dynamic time warping helps you discover patterns you wouldn’t intuitively predict. Effortlessly handle all types of SKU-level demand patterns from seasonal, intermittent and irregular series to cold start/net new SKU forecasting. Point solutions can’t do this, and reality is neither can many data science teams.