Could artificial intelligence (AI) optimize predictive fuel pricing and dynamic in-store pricing for convenience retailing? Some retailers believe that it may help them better understand data. Others are more hesitant and wonder if it would homogenize the market.
The Convenience Leaders Vision Group (CLVG) hosted a presentation on how AI can assist retailers in optimizing pricing strategies without jeopardizing customer loyalty. It was facilitated by Frodi Hammer, founder and CEO of A2i Systems, and was followed by a discussion held by Vision Group Network Co-Founder Myra Kressner.
Hammer emphasized the importance of factors beyond price, such as location, cleanliness, staff and overall customer experience. The meeting also addressed transparency in retail pricing, the ability of AI to account for missing information and the potential impact of AI on the competitive landscape. Hammer proposed creating a "digital twin" with AI for concurrent pricing simulation.
The ensuing discussion also explored the nuanced nature of pricing strategies, addressing optimism and skepticism from CLVG members.
Pros of AI Fuel Optimization
Many participants recognized the potential of AI to facilitate fuel pricing given the plethora of data it can analyze.
“The idea of pattern recognition is really exciting when you consider all the data that we've got,” said Roy Strasburger, co-founder of the Vision Group Network. “For decades we, as an industry, and other retail industries, have been collecting all this data and what do you do with it? I mean, you drown in the data. If we can rethink this in regard to using the pattern recognition side of AI to help us better understand all that data, it will enhance, shall we say, the human component of the marketing and the retailing side of the business.”
Hammer emphasized the adaptability of AI models to changing market dynamics and their extension into areas like car washes.
The adaptability of AI models to changing market dynamics and their potential extension into areas like car washes were also explored. Joe Sheetz, board of directors chairman for Sheetz Inc., commented, “I think what's important for our industry …we're not just about fuel anymore. It used to be that's what drove all the trips and things have changed. And so any modeling we get into has to model what's happening to the total facility, not just what's happening to your gas gallons or your gas margin. What are you doing to your beverage sales or your food sales based on what you're doing with your gas pricing? It's all one big puzzle at the end of the day.”
Skepticism
Challenges include standardization and what it would mean for all c-store retailers to use the same technology.
Scott Hartman, CEO of Rutter’s, and Donna Sanker, president of Parkland USA, expressed caution, citing the complexity of data and the need for human insight in pricing decisions. Can AI bring a qualitative component to the data?
“My mind goes to where is the system getting all of the missing pieces of information that it might not have, and how do you account for all the qualitative pieces of information that are happening all the time?” said Mark Samuels, executive vice president of convenience retailing at Dash In/The Wills Group. “The station down the street running out of gas, you mentioned construction earlier. This store's down for a remodel. Pricing is going to be obvious, but you don't know all of the competitors' volumes at their price compared to yours. You know yours, but where do you fill in all the gaps and how does that system work to adapt for that?”
CLVG members also discussed the role of external data, the challenges in standardizing it for integration, and the potential business model of selling external information to retailers.
Natalie Morhous, president of RaceTrac, raised concerns about the potential homogenization of the market if all businesses adopt similar AI models.
Scott Hartman, CEO of Rutter’s, said, “I think currently AI or what's closer to a well-designed intelligent software is out there in our phones and our cars today. So I think the near term AI we should all be aware of is the customer asking the device to find them fuel, asking them where's the nearest place with beer or placing a mobile order for food, talking to it, it's listening, it's placing the order, it's sending it to a place.”
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