Retail supply chain management: 4 ways to keep shelves stocked
The pandemic may be over, but retailers still face a slew of problems that wreak havoc on their supply chains and bottom lines. Here's what they can do to manage the risks.
The projected growth of the global retail internet of things market to $147 billion by 2028 reflects the expanding adoption of smart devices and sensors by retailers. Businesses equip their stores, warehouses, and inventory with IoT in pursuit of better operations efficiency and increased sales, and IoT analytics is crucial for achieving these objectives.
Keep reading to learn how IoT analytics works and what its role is in driving growth for retail businesses.
IoT analytics, explained
Setting up a network of interconnected IoT devices and gathering terabytes of various data types is half the battle, as you then have to analyze all the collected information.
IoT analytics allows for storing, processing, and analyzing data gathered from RFID tags, beacons, store cameras, and smart shelves.
By using various data analysis techniques, such as data mining, regression, factor and time-series data analysis, and machine learning techniques, companies can uncover patterns and relationships within the datasets.
Afterward, these analytics insights are presented via reports and dashboards to help retailers make better decisions.
IoT analytics use cases in retail
1. Real-time inventory management
Poor inventory management can lead to overstocking, which can cause increased storage costs, capital tied up in excess inventory, and potential product expiry. Also, promotion of goods that are in excess, or vice versa, a shortage of popular products, damages customer satisfaction.
IoT data analytics can help companies improve inventory management to avoid overstocking or stockouts. IoT technology helps inventory managers to stay informed about stock levels and plan replenishment accordingly. RFID tags attached to every product piece or batch allow managers to know the exact location and quantity of the products. Similar to RFID tags, smart shelves provide real-time data on product availability on store shelves and send alerts when it’s time to replenish.
By collecting real-time inventory data from stores and warehouses and comparing it with market trends and historical sales data, retailers can forecast demand for timely restocking.
In addition, with inventory data at hand, retailers can also keep customers aware of the availability of specific products in a particular brick-and-mortar store or at the warehouse.
2. Queue management
When it comes to checkout, it can be difficult for brick-and-mortar shops to compete with online stores, where the payment process is highly streamlined. At peak hours when physical stores are overcrowded, long queues can put off potential customers and they’re likely to shop at a less crowded shop to avoid the inconvenience.
IoT-enabled in-store cameras and sensors can detect long peak-hour queues and alert managers to open more registers. Retail managers can further analyze the collected data to identify the most and least crowded times and optimize the staffing level and staff schedules. This helps reduce queues and wait time, which improves customer experience and boosts loyalty.
3. Store layout optimization
With IoT tech installed across retail stores, store managers can track customer behavior around certain product areas and identify optimal layout options for various types of products. Proper product layout can help increase the satisfaction of customers, who will no longer need to waste time wandering around the shop in search of a particular product. IoT data analytics can also help retailers find the right spot for short shelf-life products to ensure quick sales and avoid spoilage and financial losses.
4. Supply chain visibility
GPS and RFID tags on products, pallets, or containers provide real-time data on their location throughout the supply chain, helping retailers track product shipments from the manufacturer to the warehouse, store, or a customer’s house, reducing the risk of loss or delay. Analyzing data from IoT sensors, retailers can forecast and inform customers of expected delivery timelines.
Moreover, with IoT sensors, retail companies can monitor the condition of goods being delivered, including temperature and humidity, ensuring that products, especially perishable ones, are stored and transported under optimal conditions.
5. Personalization
IoT-enabled devices and sensors, like wearables and beacons, generate vast amounts of data by tracking customer behavior, locations, and product usage patterns. By analyzing this data, marketers better understand customer preferences to create personalized ads and promotions.
Deployed in retail stores, beacons can deliver personalized offers, promotions, and advertisements to customers when they enter the area within the range of a beacon’s signal. For example, a retail store might use beacons to send special discounts to shoppers as they browse specific aisles or product categories.
Improving customer experience in retail: A new dawn rises
Undeniable stats abound in this piece on how retailers must adapt to new requirements to deliver the experience customers want and demand.
The future of IoT analytics in retail
As we move forward, the gap between traditional retailers and ones integrating IoT into business becomes wider. While some still rely on outdated methods with manual inventory updates, others embrace the possibilities of IoT, AI, and machine learning to revolutionize the retail landscape.
The future of retail with IoT holds endless possibilities for driving customer satisfaction, increasing sales, and staying ahead of the competition. Keeping up with technological advancements must be the top priority.
