Walmart has built an AI (Artificial Intelligence) lab in a bid to improve the customer experience.
The supermarket giant - who has over 3,500 supercentre stores in the United States alone - already has robots to identify when they need to restock their shelves.
And now they've revealed they have launched the Intelligent Retail Lab at their store in Levittown, New York, to learn how to improve the standards of the restocking robots and find out better ways to monitor spillages and when certain items are incorrectly placed.
It was previously revealed Walmart deployed shelf-scanning robots at over 50 of their stores in the US to ensure their stock is always replenished on the shelves.
The robot - which is around two foot in height - has cameras built into it that looks at the shelves to see where there are gaps. From there, they can inform their human colleagues, who are then able to check the robot's identification of a gap and then restock their shelves.
Jeremy King, chief technology officer for Walmart U.S. and e-commerce, said: "If you are running up and down the aisle and you want to decide if we are out of Cheerios or not, a human doesn't do that job very well, and they don't like it."
Walmart previously filed a patent to create a camera that can tell if a customer had a bad experience at their store so it can be rectified before the customer leaves.
They wrote in their patent application: "It is much easier for a merchant to retain an existing customer than to acquire a new customer through advertising. However, it can also be very expensive to maintain sufficient staff to provide great customer service. It can also be difficult to establish an appropriate staffing level that will provide proper customer service without excess staffing.
"Often, if customer service is inadequate, this fact will not appear in data available to management until many customers have been lost. With so much competition, a customer will often simply go elsewhere rather than take the time to make a complaint. The systems and methods disclosed herein provide an improved approach for characterising customer dissatisfaction and adjusting staffing levels appropriately."