Edge computing, which involves bringing data processing closer to where it is created, offers a more efficient way of handling extensive data and reducing latency. This technology has vast potential within the retail sector to revolutionize customer experience and enhance services. Challenges faced by retailers such as scarce resources, tracking customer behavior, and slow response times can be addressed by leveraging edge computing.

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Recently, many industries have realized the importance of edge computing besides its already-recognized relevance in academic research. Edge computing encourages bringing data processing closer to where it is created, ultimately reducing latency and providing a more efficient approach to handling extensive data. Edge computing is a supporting technology to cloud computing instead of its replacement. Working together, they offer faster processing speed, increased security, and optimized network performance by reducing the number of times data is sent to the cloud.

Edge computing has been successfully used in various application domains, such as autonomous vehicles, smart homes, smart cities, and predictive maintenance. It also has immense potential within the retail sector. It can revolutionize customer experience by allowing tailored services and helps retailers adjust their operations depending on real-time edge analytics. 

While digitalization has allowed businesses to expand online sales across many industries, including retail, brick-and-mortar services are still very much needed. Whether they purchase online or in-store, customers deserve a better shopping experience that justifies the value of their money. Therefore, efficient data processing near the network edge can help retailers improve their services for enhanced customer experience.

Challenges in offering a personalized customer experience 

Despite their best efforts, retailers face several difficulties and challenges in offering seamless and personalized customer experience. The challenges include:

  • Scarce resources and in-store staff: with limited store staff and resources, the retailers may be unable to provide each customer with equal attention, leading to unsatisfactory customer service. 
  • Tracking customer behavior: without technology, it is difficult to keep tabs on how customers interact with retailers. Therefore, accurate customer preferences may be difficult to determine.
  • Retailers’ incapability of responding in real-time: often retailers may be required to respond to a customer request immediately in real-time. However, their inability to respond timely leads to a poor customer experience. 
  • Incompatible online and in-store experience: lack of integration between the online and offline mechanisms leads to inconsistent and, therefore, unsatisfactory customer experience. 
  • Increased time to locate the desired item: often the in-store experience in large shopping malls is an unsatisfying experience for the customers due to a lot of time spent in finding the items of interest. According to a consumer retail technology survey, around 61% of consumers prefer to save time during shopping.

How edge computing can redefine the retail market

The aforementioned difficulties experienced by the retailers that prevent a great customer experience can be addressed by leveraging the technology powered by the edge in the following ways:

Smart carts for personalized recommendations

Smart shopping carts equipped with edge devices such as sensor modules, Raspberry Pi computers, small but efficient processors for image processing and machine learning, cameras, a smart screen, RFID scanners, barcode scanners, charging ports, and speakers can collect and process data, model the customer’s context and offer personalized shopping recommendations. Quickly processing the collected data at the server and responding with information, such as required items, aisle and shelf information, promotions, and other items of interest based on past purchases, provides a better customer experience and greater satisfaction.

Personalized in-store navigation 

Providing customers an improved ability to navigate the stores based on data-driven offers and access to digitalized product catalogs also enhances brand loyalty among the customers, among several other benefits. To navigate inside the store to reach an item, beacons which are small Bluetooth devices, can be used on the smart carts. Instant communication among a large number of devices is made possible because of edge computing. Voice input integrated with the shopping cart through assistants, such as Amazon’s Alexa and Google Assistant, is another incredible way to enhance the shopping experience and identify the location of a desired product in the store.

Use of virtual and augmented reality

To offer customers an immersive and interactive experience, various devices, such as smart glasses, mobile phones, headsets, etc., are equipped with edge devices. As a result, the customers explore and experience the products virtually with the help of edge-based devices having low latency and high responsiveness.

Customer recognition 

Retailers can use edge computing to identify customers who enter the store with the help of cameras installed at the entrance. With this data being processed directly on edge devices, returning customers can be given tailored product information and special offers immediately. However, customer recognition through cameras can have several privacy-related challenges which must be addressed.

Social media integration

Many retailers are already using social media to communicate with customers, showcase their offerings, examine customer behavior, and strategize their business plans with the help of data collected through social media. Exploiting edge computing enhances the effectiveness of social media data processing and analysis, leading to improved customer engagement and satisfaction. 


Self-checkout kiosks equipped with edge devices make it easy and fast for customers to purchase items without waiting in long queues. Additionally, providing personalized recommendations based on items in the cart could result in some savings if the items are bought together. However, it is important that presenting the customer with excessive information could also be annoying, so a balance is needed.

Customer feedback

Edge devices can be used to collect customer feedback. In the event of any customer complaints, edge devices are able to process the data and address the issue immediately. As this data is processed locally instead of in a remote centralized location, therefore, latency is minimized. 

The case for edge computing in retail 

The following use case demonstrates the potential of edge computing in retail to enhance the customer experience. Suppose a customer visits a large grocery store. Upon entrance, the customer takes a smart shopping cart with several features. If the customer is a frequent customer, the cart prompts the customer to enter the customer loyalty code. This helps the cart retrieve the customer’s preferences based on the purchase history. With the help of the installed map, the cart guides the customer to the location of the desired item in the respective aisle and shelf. Suppose the customer wants to search for some item. In that case, the edge device immediately verifies the product’s availability in the store and responds with the location of the desired item. The customer visiting the store for the first time also can use the cart to navigate the store.  

 It is important to mention that this use case only considers a handful of scenarios, while there could be several other options for the customers to interact with the cart. For example, the customer may be prompted to input the shopping list via text or voice. Alternatively, the shopping list app on the customer’s mobile phone could be linked with the cart.

As the customer shops and places items in the cart, the cart, with the help of various devices, such as RFIDs, barcode scanners, etc., records the customer’s purchase data which is immediately processed by the edge device to offer instant recommendations about the other related items and promotions, etc.

As the customer heads to the edge-powered checkout kiosk, the kiosk recognizes the customer. It allows him to make payments immediately through his phone via Apple Pay, Google Pay, or by tapping the phone against the payment terminal to complete the transaction immediately. Similarly, when the customer completes the purchase and leaves the store, he receives a notification on his phone about the discounts on the next shopping.

The above use case demonstrates the potential of edge computing to model the customer’s context effectively, offer personalized information, and improve the overall customer experience.


Despite the numerous benefits of successfully deploying edge computing in the retail industry, certain challenges must be carefully dealt with. These include:

  • Integration of the edge technology with the existing systems
  • Data security and privacy
  • Management of a large number of heterogeneous devices
  • The cost involved in the implementation
  • Pervasive connectivity


Edge computing, due to its characteristics, such as low latency and efficient processing of reasonably larger amounts of data, has the potential to revolutionize the retail industry fully. Using technology in brick-and-mortar stores, retailers can better understand the customers’ preferences and, therefore, effectively model their context, eventually leading to an improved customer experience. 

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