How will AI impact convenience stores? This was the topic SparkCognition Chief Technology Officer Sridhar Sudarsan recently explored with National Advisory Group for Convenience Stores (NAG) Executive Director John Lofstock on the CStore Decisions YouTube channel.
You’ll definitely want to watch the whole video here, packed with illuminating information for convenience store operators who want to learn how AI can solve common retail challenges that enhance customer experience, employee experience, and profitability. Right now, we want to spotlight a few of our favorite takeaways.
Augmented intelligence: “Now you know.”
After a brief background on artificial intelligence, Sudarsan noted that he often thinks about AI as augmented intelligence. He explained it as human knowledge, skills, and limitations augmented by computers’ ability to process a vast amount of data at scale. It’s computers helping people think through and perform tasks. Technology using AI is empowering surgeons, engineers, safety officers, retail store employees, etc., to “consume, process, infer, reason, and make a decision in that instance in time. That’s what augmented intelligence can do for you because machines can scale a lot faster and better than humans can.”
To illustrate his point, Sudarsan pointed to a common convenience store challenge that is highly important to customer experience, keeping the bathroom clean. AI is adept at making predictions (when will the bathroom require cleaning?). Pairing with a convenience store’s existing cameras, SparkCognition Visual AI Advisor can be leveraged to predict when the bathroom needs cleaning based on how many customers are observed coming and going through the bathroom area of the store. It can then alert employees to take action—check the bathroom. It’s that simple: not a glamorous AI example by any stretch of the imagination. But these are the types of solutions that are extremely valuable in aggregate because we are now automating a process that had depended entirely on busy employees’ already divided attention.
From in-store to forecourt: Speeding up time to value
Giving another example, Sudarsan talked about customer queuing. “One of our applications allows you to determine that there are [for instance] five people in line and the predicted wait time for the last person in that queue is going to be more than 8 minutes or more than 5 minutes, etc. People are getting impatient, right? People are trying to move in and out. Can I send an alert to somebody who isn’t working right now and open up another register?” Using the cameras convenience stores already have, Visual AI Advisor can recognize what’s happening and provide an immediate alert to an employee to take an action: open up a new register before people have to wait too long; or worse, leave and not come back.
Sudarsan continued, “You can set up a new product campaign. You can set up a new placement campaign. And you can get immediate responses and results to see whether or not they were effective.” He explained that these iterative approaches, using augmented intelligence, speed up time to value “where you don’t have to wait for weeks before you get all your sales data and you look at everything. Now you know. It’s all out there. And you can see it.”
Lofstock agreed, adding: “And not just knowing that ‘you sell a lot of pizza at 4 pm.’ You can actually get a whole profile of each consumer that’s purchasing pizza. It’s not just a notch on a report. It’s an actual picture of the consumer, maybe tied to their loyalty program, really understanding who that customer is, and specifically, the path that customer took in that store. You can really get a digital footprint of your consumers by customer. That’s fascinating. That’s like a goldmine for C-stores.”
Talking about opportunities to leverage visual AI in the forecourt, beginning with security, safety, and compliance use cases, Lofstock brought up the challenge of converting fuel customers into convenience store customers. CStore Decisions and SparkCognition are currently partnering on a study to understand EV consumer behavior and trends, adding to the industry’s understanding of this subject. Whether EV or gas fuel customer, though, Lofstock said the goal has always been to convert that customer 100% of the time, ideally, but Lofstock noted the actual percentages are frustratingly low. Can AI help incentivize customers to enter the store?
Sudarsan unpacks this challenge around the 17:30 mark (spoiler alert—it can).
Key Takeaways: Proven technology to solve retail labor challenges
Asked what takeaways he hoped retailers would get from their conversation, Sudarsan offered three. “Number one: this is not a cool technology that you should wait for five years [to try], because it will be five years too late. This is here now.” He continued: “It is a hardened technology that has been deployed at scale, and you can get the value for that now. The way we have built it, you can start deploying this within days.”
“Number two: The biggest value here is on managing labor. If I look at one of the biggest challenges in retail—especially in the convenience store, but it’s true for all retail right now—it is labor management. It’s the availability of labor, retention of labor, turnover, and costs. It’s the experience for your employees that you want to provide. It’s all of that. It’s being able to use labor that you already have in the most efficient way. And to me, that’s where the partnership for the use of AI technology (especially computer vision) with your employees becomes a very powerful combination. So can you manage 100% of the store operations with 70% of labor that you have? And how do you do that most effectively? It’s through the use of AI.”
“And the third thing I’ll say is: Yes, there are many, many applications that you’re probably using. Very likely, they’re all giving you a lot of data. And you’re getting inundated with it . . . you’re just looking at so much data that you’re looking at no data.”
“And so what we have chosen to focus on is actions. Can any of these applications give you immediate actions that you can take or that your store managers, area managers, cashiers, forecourt operators, food service managers, and corporate offices can take across the different stores? That’s what I think you want to focus on. Because that will give you the best time to value.”
Closing with a final thought, Sudarsan predicted: “I think the convenience store industry is primed to be transformed, and it starts with every single store.”
Watch the full conversation on visual AI’s impact on c-stores in the video podcast.
Join us at the NAG Conference, March 26-29
We thank John Lofstock and CStore Decisions for the thoughtful conversation, and we encourage you to join us at the NAG Conference, March 26-29, 2023, in Austin, TX, where we look forward to revealing the results of our joint study about what electronic vehicle customers are doing at convenience stores while their car is charging. See you there!
