“AI-Driven Automation and Predictive Analytics in Retail Planning”
- A significant and accelerating trend in the global category management software market is the adoption of artificial intelligence (AI) and predictive analytics to optimize assortment planning, shelf space allocation, and pricing strategies. These technologies enable retailers to make real-time, data-backed decisions, resulting in improved efficiency and increased profitability
- For instance, Oracle Retail and SAP SE have integrated machine learning into their category management platforms to analyze purchasing behavior and forecast demand more accurately, allowing retailers to align product offerings with shopper preferences across channels
- AI-enabled software can automate traditionally manual processes such as clustering, planogramming, and markdown planning, significantly reducing operational time while improving accuracy. Predictive models also help retailers respond to seasonal demand, competitive pricing changes, and regional preferences in near real-time
- Integration with POS systems, inventory management tools, and e-commerce platforms further enhances decision-making by creating a 360-degree view of product performance across the supply chain. This holistic insight allows businesses to enhance personalization and responsiveness to market trends
- Companies such as JAGGAER and GEP are also embedding advanced analytics into their platforms, helping businesses streamline supplier collaboration and sourcing strategies within their category planning workflows
- The demand for intelligent, automated, and highly adaptive retail planning tools is rapidly growing, especially as retailers seek to enhance omnichannel strategies, improve inventory turnover, and maximize space efficiency in competitive environments
