Vision AI adoption is spreading quickly among retailers. According to Statista, 38% of retailers are using vision AI for select use cases and regions — that is on a limited basis. Another 27% are in the planning process, conducting pilots or not using AI at all.
As you pilot, deploy and/or expand usage of vision AI, let your mind entertain the possibilities. Here are four groundbreaking, mind-boggling vision AI use cases to help you envision the future of your operation.
Next-level store optimization — Beyond heat mapping and queue evaluation, vision AI has the potential to help retailers get a jump on impulse purchases and per-ticket sales. Vision AI can effectively monitor linger points and times, customer demographics, stockouts and traffic patterns. These inputs, combined with machine learning, can recommend optimized store layouts and merchandise placement to engage shoppers, increase sales and achieve greater profitability. Fueling decision-making in real time, it’s like having a continuous stream of customer feedback to guide your store design.
Proactively reduce loss due to spoilage – Perishable goods present a problem for retailers and restaurateurs alike. An estimated 30% of food in American grocery stores is thrown away. Vision AI is changing that by offering a multi-front attack on the loss of produce. By monitoring devices and triggering alerts when they fall outside acceptable temperature-controlled thresholds, vision AI helps prevent spoilage when possible. Vision AI is also capable of identifying stages of spoilage, automatically offering value pricing on items that are beginning to deteriorate. Data collected regarding shelf-time to spoilage can be used to optimize forecasting and ordering of perishable items. This results in significantly reduced loss of perishable goods.
Streamlined warehouse performance — Intelligent warehouses and fulfillment centers aim to increase throughput and maximize efficiency. Vision AI can be used to collect insights on the end-to-end process: from receiving through warehousing, picking/packing, conveying and packaging for shipment. By expediting product identification and receipt, quickly assessing packaging dimensions and slating them for storage with optimal efficiency and space-saving, vision AI streamlines processes that lacked efficiency when handled with manual processes. With eyes on picking and packing, vision AI can trigger automatic adjustments to conveyor speeds and/or flag missing items to improve accuracy. The results include reduce downtime and increased throughput by up to 20%, according to NVIDIA.
Route optimization and trailer tracking – Vision AI combines with machine learning in powerful ways to deliver on the last-mile delivery, a challenging but crucial part of the retail journey. Whether routing trucks to warehouses or stores to replenish merchandise for sparse shelves, or guiding delivery drivers to customers’ front door, vision AI collects insights about traffic and weather conditions, combining that information with data about available workforce, broken down vehicles and promised delivery times, to plan the optimal route for delivery in real time. Vision AI can also provide visibility to trailers once they leave the warehouse, remotely monitoring conditions both inside and outside the vehicle, in additional driver behaviors. Navigating the urban jungle has never been easier for drivers.
Vision AI collects in-depth insights, triggers timely action and informs better decision-making. Telaid can help you leverage AI to tackle your most daunting business challenges, whether they are related to customer service, operations, security or efficiency. Let us create a custom tour of our best-of-breed partners that will most effectively meet your needs.