Autonomous Robot Usage Extends To Daytime As Retailers Adjust To New Cleaning Demands
Robotic floor scrubbers are increasingly being used during daytime hours to help retailers keep up with heightened cleaning demands in wake of the COVID-19 pandemic.
During the first four months of 2020, the use of BrainOS-powered robotic floor scrubbers in US retail locations rose 18% compared to the same period last year, including a whopping 24% y-o-y increase in April, the latest data from Brain Corp has revealed.
More than two-thirds (68%) of this 18% year-to-date increase occurred during the daytime, between 6:00 and 17:59.
Alan Butcher, vice-president of client services at Brain Corp, said, “Expanding robotic usage into daytime hours generates more cleaning coverage and also provides a strong visual reminder of a grocer’s commitment and investment in clean.”
In a recent survey by C+R Research, 60% of American shoppers said they are 'now fearful' of shopping at grocery stores, with 73% saying they are shopping less at physical stores.
During normal times, shoppers visited food retailers twice per week on average. That figure is now only once per week, with 45% disinfecting their groceries when they get home, according to the survey.
Robotics help in unlocking cleaning efficiency and regain consumer trust because the autonomous floor scrubbers don’t require additional resources.
According to Brain Corp network data, BrainOS-enabled cleaning robots are providing more than 8,000 hours of daily work, on average.
BrainOS-powered robots have already logged more than 1.5 million autonomous hours, proving that the technology is highly scalable.
Phil Duffy, vice-president of product at Brain Corp, said, "Together with our OEM partners, we combine proven AI software with industry-best cleaning equipment that businesses already know and trust.
"We believe the market is validating this approach compared to vendors who try to build robotic cleaning solutions from soup to nuts - hardware, software, navigation, etc. That’s a lot to get right, and hard to reliably scale.”