dotData Transforms Retail With Omnichannel AI

Develop highly accurate demand forecasting models by utilizing weather data, regional characteristics, sales promotion information, etc., in addition to actual sales and order/delivery records. Automate product ordering operations, optimize inventory level, and reduce out-of-stock risk by integrating accurate forecasting with ordering systems.

Develop accurate demand forecasting at various levels (e.g. SKU, product category, daily, weekly, etc.) and maintain model accuracy with automated model retraining. With highly accurate and granular demand forecasting, retailers can reinforce and optimize their supply chains.

Automate product ordering operations, optimize inventory level, and reduce out-of-stock risk.

Predict the degree to which each customer is likely to visit a store and recurrent purchases through sales promotions. Automatically analyze common characteristics of customers by promotion response type to enable a data-driven promotion strategy.

Analyze all customer information, such as behavior logs, attributes, preferences in conjunction with other data sources such as geographical characteristics and build deeper hypotheses of store visits and recurrent purchases.

Increase customer loyalty, store visits, and recurrent purchases – eventually increasing the store sales.

Relying purely on focus groups to understand customer sentiment is no longer sufficient, but mining consumer sentiments on social media and web portals can be costly and time-consuming. Leverage the power of AI to automate the process.

Leverage your historical data and combine it with data from focus groups as well as website data to build more accurate models of customer sentiment and to forecast special campaigns and offers.

Identify customer loyalty trends, model predicted outcomes to new product introductions, and to price adjustments by mining your in-house and external data to create accurate forecast models of consumer behavior.

Take price planning beyond simple cost and revenue calculation to identify key factors that influence price sensitivity to create the best possible experience for consumers while maximizing your opportunity for revenue.

Take advantage of both in-house data like transaction histories as well as readily available market data to build more accurate pricing models. Integrate pricing predictors into your inventory systems to modify pricing in response to market conditions quickly.

Strike the perfect balance between maximizing revenue and providing customers with a high degree of satisfaction by analyzing past sales data to create ideal pricing scenarios.