Internet of Things (IoT), Cloud and Machine Learning, have changed traditional retail scenario giving rise to connected retail, that provides organizations with innovative opportunities to collect and examine data and ensure successful business. To keep prospering in a highly competitive industry, retailers need to focus on spreading their reach to customers with several stores/outlets, handling supply chains and provide exceptional end-user experience. A recent study by McKinsey estimates that the IoT in retail industry will economically impact in the range of $410 billion to $1.2 trillion per year by 2025. Integrating IoT, Machine Learning and Cloud Computing services in the retail environment not only reduces IT costs but also improves customer experience and efficiency, streamlining the workflow.
Let us see how these new technologies transform and stimulate key benefits for the retail industry.
Stock and storage monitoring
Storage containers containing raw materials or products can be tracked using IoT devices which are based on the location tracking sensors like GPS sensor. The location tracking device will have a location sensor attached to it which will have the capability to broadcast its location via GPS and remote satellites. The captured location details is sent to the cloud for processing and then pushed to any connected mobile/desktop application where users can run time, see the location and monitor it.
Also, a combination of IoT sensor devices can be used to monitor environmental storage parameters for raw materials like edible or chemical goods.
Demand forecasting using Machine Learning (ML)
Demand Sensing algorithms which are based on Machine Learning extracts data from billing systems, warehouses to understand the sales movement. These algorithms continuously and automatically analyzes factors which are influencing sales, and constantly offers new adjustments for sales expectations. Models based on predictive sales analytics can be used to clean the data that is extracted from the systems to check if the data variables are relevant to the organization and if can impact sales. Data sensing algorithms makes use of these cleansed data and help various companies and organizations to build predictive models to understand and analyze the outcome of sales in the market. Many companies reported an increase of 5 to 15 percent in forecast reliability (up to 85 and even 95 percent) by integrating machine learning to their existing systems.
Efficient inventory management with smart shelves
Smart shelves have been in the market since early 2000s, and Amazon and Microsoft are constantly improving their technologies in this area. Smart shelves help in checking the inventory – if the product stock is over on that particular shelf. Smart shelves can be developed using RFID tags, RFID readers and RFID Antennas. The RFID tag attached to a product transmits data to the RFID reader. The information which is collected from the RFID reader is sent to the IoT device and the data received is analyzed and calculated to check for any theft, inventory management, to understand customer interest, automatic ordering, etc. The stocks reported from the RFID reader are pushed to cloud databases. Cloud connected mobile applications can help the user to understand the database on the go, so that he can manage the inventory more efficiently.
Enhancing customer experience
There are multiple technologies like IoT enabled beacons, automated checkouts, in-store layout optimization, ML based data analytics, etc. used to enhance customer experience.
Beacons are very useful components for IoT. Beacons work as radio transmitters on low energy over BLE/Bluetooth connections. They are usually used to send push notifications on the store mobile applications of smartphones based on the location proximity of the user. Some of the North America’s top retailers, including Macy’s, Target, Urban Outfitters, etc. uses Beacon technology for their stores.
Also, IoT devices like smart carts or self-checkout kiosks can be installed at a particular place in the store, so that the consumer will not have to wait in long lines. Self-checkout kiosks will have barcode scanners, where users will have to login to their account/mobile payment apps, scan the codes of the products and add it in the cart to process the payment automatically.
Moreover, layout optimization also helps the retailer to understand what products are sold the least and where they can put them forward for selling. To achieve this, retailers can use Aisle Analytics software with infrared sensors to understand customer patterns. The sensors observe traffic patterns and identify where customers spend the most time to determine a spot to place the most popular and profitable items. Retailers can also add value by generating personalized product recommendations for buyers with the help of cloud computing and analytics.
To summarize, retail businesses are seeing growth from integrating and gradually switching to new-age technologies that reduces their operational and infrastructure costs, improves data security, provide real-time access to inventory, streamlines supply chain management and provides an enhanced customer experience elevating their businesses to next level.
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