NASHVILLE, Tenn. — Once driven solely by coin-operated machines and manual oversight, the laundromat industry is transforming with the rise of data-driven operations. More and more modern stores are leveraging smart technology and advanced analytics to optimize efficiency, cut costs and enhance the customer experience.
From dynamic pricing models that respond to demand to predictive maintenance that minimizes downtime, data has become a vital tool for maximizing profits. Understanding, leveraging and protecting data used in laundry operations was the focus of a presentation during the CLA’s recent 2024 WDF Workshop. Part 1 of this story focused on the search for actionable insights. Let’s continue:
OPERATIONS DATA IN USE
Gilli Cherrin is chief product officer and co-founder of Cents, a software company that provides point-of-sale, online ordering, payments hardware, marketing tools, and business management software for laundromats and other textile care businesses. He welcomed three panelists and asked how they use and view data related to their operations.
Australian Jason Worme relocated to New York City two years ago and now owns Star Laundromats in Staten Island and Brooklyn. “The way I use data is more at a tactical level, more to run, understand, operate and grow my business,” he says.
As an example, he runs three shifts in his main store, which is open 24 hours. Using a Cents data feed that goes directly into some self-built software, it gives him a view across the three shifts as to whether their wash-dry-fold service is behind or will meet the delivery timelines.
“What comes out of that is decisions,” Worme says. “If you are behind, now you’ve got options behind bringing in more labor, talking to customers about relaxing their delivery time, making the driver potentially change his route to give some more time.”
Bhavin Patel is CEO of SpinXpress Laundry, which has several locations across Texas. He says his business has used data most effectively in serving commercial customers. Shortly after beginning to accept commercial work, his staff was trying to process 1,200 to 1,400 pounds each day using just two 160-pound washers. It became clear that the facility wasn’t large enough.
“We realized we needed to build some efficiencies into how we can take the information about how many pounds we’re going to be expecting week over week, day over day, and start planning and scheduling the (rental) inventory,” he says. “We were working with Excel back then.”
Brian Riseland owns and operates Laundry Genius, a full-service laundry center in the Seattle metropolitan community of Everett, Washington. The store celebrated its third anniversary over the summer.
“You have to have the data. Over three years in business, if I track like 160 things a month, most of it, you could call it noise that I may never use,” Riseland says. “But recently, I had an expansion opportunity and I was able to call upon that to really analyze the square footage on real estate. It was really enlightening to me about my current store and kind of my overall strategy.”
“The data doesn’t do anything for you other than give you the ability to make data-driven decisions where you still have to go with your ‘gut,’” interjects Cents CEO Alex Jekowsky, moderating the presentation. “You’re still making the calls. But where you can have an informed decision vs. a best guess, that’s where it can really be the difference between a win and a loss.”
ANY CHANGES MADE BASED ON YOUR DATA?
Worme recalls, upon buying his first location in 2023, that he was trying to understand the self-service component and how he could maximize it. The store closed at midnight, with last wash at 9:30. It was a big gap that he inherited.
“I would review the data over the initial couple of months and we would see that from around 5:30, 6 o’clock, up until 8:30, we were generating our highest revenue at any point in the day,” he says. “We were sort of turbocharging these couple of hours. But at 8:30, it would basically drop off a cliff.”
Remaining open after that rush didn’t make sense so he continued to monitor things. He looked at surveillance footage from that time and it turns out that attendants—who wanted to leave immediately upon the store closing—were telling customers coming in at 8 or 8:30 that the store was about to close, thus driving business away.
“We pretty quickly decided to try being open 24 hours,” Worme says. “Almost immediately, that supercharged revenue continued. It now goes til around 11 o’clock before it starts to drop off. We still get drop-off orders at 3 a.m. that could be hundreds of dollars per drop. The data allowed us to see something that was odd, then we were able to see other pieces of information available to see what was going on and see how we could solve the problem.”
In Thursday's conclusion: Laundry owners share data points they wish they could get but can’t
Have a question or comment? E-mail our editor Bruce Beggs at [email protected].
