RFID in combination with artificial intelligence helps to avoid “lost sales chances”
From out-of-stock to save-the-sale: hidden treasures in retail stores
By Tom Vieweger
By Tom Vieweger
Product availability is key in retail stores! In a time when the balance of power is shifting towards ‘connected consumer,’ each out-of-stock situation is a missed chance to fulfil actual demand and a risk to potentially lose a customer in the long run. What makes it even more tragic is that very often the products are actually in the right store, but they simply did not make their way out to the sales floor and are thus not easily accessible for customers to buy.
This challenge of not being able to convert customer demand to revenue, because the desired items are hidden in the stock room, is widely recognized in the retail sector. However, up until today, the methods to tackle this challenge are very often still quite archaic. Traditional refill methods are typically based on (sporadic) visual checks or converting POS transactions into refill recommendations. These processes are very time-consuming and flawed. As stock accuracy in traditional ERP systems is typically poor and stock visibility is limited, there is no guarantee that the missing size is actually available in the stock room. The item might be out-of-stock, which makes the entire refill process very inefficient and also not very satisfying for the store staff.
Increasingly, retailers see RFID as a solution for guaranteeing maximum on-shelf product availability. With RFID, it is possible to have complete inventory visibility and to differentiate stock on the sales floor from stock in the stock room. Based on the RFID count per sub-location, retailers can easily and accurately start refilling.
To increase the efficiency and effectiveness of this process, however, the RFID count data needs to be tweaked to prevent endless refill lists. Here, artificial intelligence and machine learning can be used to calculate a “smart planogram”. Nedap’s instore RFID solution iD Cloud generates store-specific refill lists based on existing and historic stock levels and is able to learn what product/size combinations are the most important on the sales floor, and which ones should not be on the sales floor. The results are then presented in a prioritized ‘refill suggestions’ list.
Increasingly, retailers who utilize RFID-based refill procedures are redefining consumer engagement by leveraging “save-the-sale initiatives” that place the highest priority on getting in-demand products into the hands of consumers. This does not only result in an increase in sales but, more importantly, in happy and loyal customers.
Not converting a customer while the desired item is actually sitting in the stock room is one of the worst scenarios for any retailer. But how can retailers make sure that out-of-stocks are prevented and shelves are always perfectly stocked with the right items?
In this white paper, we will analyze different refill methods and discuss how RFID in combination with machine learning and smart algorithms can support store teams to achieve better product availability and increase sales.