Artificial Intelligence for Retail Applications

The retail industry has been facing major headwinds spawned by disruptors like Amazon, Alibaba, and Walmart, as well as hundreds of hungry startups, that have built lean, analytics-driven organizations based on scale and efficiency. The goal of these organizations is to drive top-line revenue and reduce operating costs. Overall, revenue and margins are under pressure as these more efficient and scalable disruptors draw more buyers and sales with sharper pricing, personalized customer journeys, and finely tuned assortments. Meanwhile, they are driving down costs through efficiencies in supply chain & inventory management. The stakes are high. It is estimated that hundreds of billions of dollars are lost every year through missed opportunities and excess costs due to issues. Increasingly, a broad range of solutions providers and pioneering retailers are launching AI-driven solutions that are taking the following steps: leveraging contextual personal data and predictive analytics; improving search functionality through sharper meta-tagging and visual search; creating digital maps of in-store inventory; and applying predictive analytics and data science. This Omdia | Tractica Focus Report examines the market issues surrounding AI use cases in the retail industry and presents profiles for key industry players throughout the ecosystem. It analyzes 11 major use cases: supply chain & inventory management; e-commerce VDAs; video surveillance; image recognition (visual search, content management, & advertising); stockout management & promotion compliance; personalized customer journeys; autonomous stores; merchandising; shopper behavior analytics; customer service & marketing VDAs; and returns management. Global market forecasts for retail AI software spending, segmented by region and use case, extend through 2025.