AI-driven Customer Churn Prediction enables mid-market retailers to identify customers at risk of leaving or ceasing purchases. By analyzing customer behaviors, purchase history, and engagement data, machine learning (ML) models can detect early warning signs of churn. Retailers can use these insights to take proactive steps, such as personalized marketing campaigns, loyalty incentives, and customer […]
AI-driven Demand Forecasting uses machine learning (ML) and predictive analytics to forecast product demand, enabling mid-market retailers to optimize inventory, avoid stockouts, and reduce overstocking. This use case leverages historical sales data, seasonality patterns, and market variables to create more accurate forecasts. By improving the precision of demand predictions, retailers can reduce inventory carrying costs, […]