Retail at the edge

Retail at the edge

Edge computing combined with AI provides retailers with a variety of opportunities to streamline and improve retail operations. In the Covid-19 era, edge computing can both improve the overall customer experience and give retailers the agility and flexibility needed to accommodate social distancing, zero contact transactions and other safety guidelines.Twitter logo

Let’s examine one such edge computing powered scenario where a customer orders a product online and then drives to their local retailer to pick it up.

Stock monitoring

A couple of months ago I embarked on an epic journey of trying to find a Nintendo Switch for my niece, on two separate occasions I purchased the item online from a local retailer only to be told that it was out of stock when I arrived at the store to pick it up. I wound up finding the device at a 3rd retailer whose web site claimed the device was out of stock, but had several Switches on the shelves. I’m sure I’m not alone in this experience, as the dreaded: “one or more of the items you ordered isn’t available” message received while halfway to the store, or worse yet in the parking lot, is a common experience. How can edge computing help?

Edge-based visual AI solutions can monitor shelves in real time and ensure that the stock levels shown online are always up to date, in addition to alerting store associates to either restock the shelves or order more from suppliers. Data from the stock out alerts can also better inform purchasing decisions as well as enabling better monitoring of shrinkage.

The solution is comprised of the following components:

  • Internet enabled cameras can monitor a group of shelves/aisles, as well as supply rooms and storage areas.
  • An edge device gathers the feeds from all the cameras, in addition to controlling the cameras as far as “patrols” that govern the shelves they monitor, ideal zoom settings for an aisle, etc.
  • The edge device uses the video feeds to determine if an item is missing, low on stock, etc., depending on the technology is deployed in your retail space

The stockout data can be used in a variety of ways:

  • Online ordering systems can interface with the stockout data and validate that the item is in stock before the customer’s order is confirmed. E.g. Customer orders at 3:16, and the system can use the video feeds to validate that the item is still in stock.
  • Apps can display stockout alerts replete with a photo of the aisle/shelf in question, enabling employees to either restock the shelves or place an order for more items.
  • The stock out data can be stored and used for BI around the rate at which items stock out, restocking efficiency, shrinkage, etc.
  • Privacy issues can be managed via “throwing out” images with people in them, only using them for inferencing but not storing them, etc.

Customer arrival notifications for curbside pick-up

Another aspect of ordering for local pick-up is that picking up your items can be frustrating, sometimes the staff notices you right away, sometimes you have to get someone’s attention and let them know you’re arrived or the app doesn’t seem to be monitored.

Using a visual AI model + edge device and external cameras, an edge-based solution can not only read your license plate and notify the store that you’ve arrived, it can also tell them your exact location in the parking lot. Instead of a hit or miss experience where the store associate is trying to find you, they instead know that the blue Toyota is in space E14. In instances where the cars have to get into a line and  pull up to a pick-up zone, the system would be able to tell associates the order the cars are in, enabling them to better organize and deliver the orders to each car.

Improving the end-to-end ordering experience

Edge computing can enable better supply chain management, reduce friction for online sales with local pick-up and improve the overall customer experience Twitter logo:

  1. When the customer completes an online order, they can be sure that the item they selected is in stock and will be available when they make the drive to pick up their order.
  2. Customers picking up their orders will experience reduced wait times and an improved overall experience.
  3. Retailers will have additional information they can use to improve their supply chain management
  4. Retailers will be better able to manage internet orders and in person pick-ups.

Neal Analytics has experience in designing edge-powered AI solutions in the healthcare, manufacturing and retail spaces, a delivery playbook that ensures implementation success and long-term partnership with Microsoft that ensures that we stay at the cutting edge of edge computing, machine learning and visual AI.

Want to discuss how edge-powered AI solutions could meet your business’ needs?  Contact us to chat more with our experts. We’ll be happy to discuss how edge computing can improve your business.

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For further reading on AI, edge computing and retail, check out the following articles: