Companies lack the ability to measure promotion ROI and performances due to a lack of transparency. But by leveraging AI, Neal Analytic’s Promo Max solution enables businesses to validate every expenditure by identifying the value behind every investment. Track the monetary impact of every change to your promotional campaigns and use predictive analytics to forecast your ROI.
Advanced Demand Forecasting
The sooner you can accurately identify future demand for your product, the more effectively you can adapt to changes in the market. This Forecasting Solution leverages state of the art modeling techniques to give your business a clear picture of where demand is heading at the individual plant or product level. While an accurate number for local operations is useful, this solution also leverages HR & Operations data to describe the staffing needs associated with fluctuating demand.
SKU Assortment Optimization
Inventory Optimization offers CPG and Retail companies an innovative way to manage product assortments across their business – ensuring each outlet gets the best product assortment based on local customer needs and preferences. Neal Analytics offers an open, integrated solution that provides machine learning insights through a scalable platform for advanced analytics.
Customer Lifetime Value
In the expanding Retail & Packaged Goods industry, understanding your customers and creating the best possible customer experience is more essential than ever. Neal Analytics’ Loyalty Max solution helps businesses gain an in-depth, 360-degree view of their customer base with a focus on cultivating customer loyalty. By guiding successful interactions with customers at key lifecycle moments, individual lifetime value can be increased and marketing ROI can be improved. Understanding the contributing factors of customer lifetime and churn will also help leadership teams better invest in the their customers’ futures.
Neal Analytics provides CPG and Retail companies a multifaceted product recommendation engine that takes into account consumer preferences and historical purchases. The result is a recommendation engine that enables businesses to engage in personalized marketing campaigns, provide tailored customer recommendations, and identify popular consumer baskets.