Potential for economic impact
For the applications we size, we estimate that the potential economic impact of the Internet of Things in retail environments ranges from $410 billion to $1.2 trillion per year in 2025 (Exhibit 15). Of these, the largest are automated checkout, real-time advertising and promotion (delivered to customers when they are in the store), layout optimization, and reduced inventory shrinkage.
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Checkout is one of the most labor-intensive processes in retail and a frequent source of frustration for customers, who must wait in line and go through complex, multistep transactions to make payments. While self-checkout systems have been introduced in some retail environments, most offer only limited improvement over the traditional cashier system and its card- or cash-based transaction process. The Internet of Things has the potential to completely automate checkout by scanning the contents of shopping carts and automatically charging the sale to the customer’s mobile payments account, allowing a consumer to walk out of a store without pausing.
Real-time in-store promotions
With beacons that connect to mobile phones to track customers within the store, retailers can launch custom promotions in real-time. Once the customer is identified by his or her phone, algorithms can combine historical information about the customer’s preferences and lifestyle with current in-store location data to create unique offers. Over time, these systems can develop customer profiles that include not only data about what they have purchased, but also what they are willing to pay. Real-time advertisements and promotions based on this information can increase spending per customer, giving the advertiser a higher return on investment and raising productivity. In a theater or sports arena, patrons selected by particular criteria (such as frequent attendance) could be offered last-minute upgrades to unsold premium seats at discount prices.
By studying the location and movement of shoppers over time, IoT data can be used to optimize a store’s physical layout. We estimate that layout optimization can lift productivity by 5 percent, leading to a total potential value of $79 billion to $158 billion in 2025. This assumes widespread adoption, which would be likely if early adopters show that layout optimization provides a competitive advantage, forcing other stores to match this capability.
Reduced inventory shrinkage
The difference between what a retailer pays for inventory and what is available for sale in stores is known as shrinkage. Shrinkage is caused by shoplifting, employee theft, and vendor fraud. IoT technologies such as real-time video analytics on data fed from IP CCTV (Internet protocol closed-circuit television) cameras can make surveillance far more effective. Shrinkage can be further controlled by tracking individual items and batches of items. Assuming that these measures could reduce losses by the equivalent of 1 percent of the cost of goods sold (on average, shrinkage costs stores 1.3 percent of revenue or $182 billion globally), the value to the global retail industry could be $23 billion to $92 billion per year in 2025.3
Condition-based maintenance using IoT can reduce the costs associated with many physical assets in retail environments. In banks, for example, real-time, condition-based maintenance of ATMs can reduce maintenance costs by 10 to 40 percent. We estimate that condition-based maintenance in retail environments has a potential economic impact of $16 billion to $45 billion in 2025.
Consumers may wind up getting the most out of IoT implementation in stores. They will gain convenience and save time and, in many cases, may get better prices. Avid shoppers will be able to find even better deals as they are targeted for localized and personalized promotions based on a refined understanding of their willingness to pay.