Erik Ogren, president of loyalty solutions provider Patron Points, grew up in convenience retail.

Back then, the best way to determine if an item was selling was to check how much supply was left. “Our backroom was bigger than our retail space,” he recalled.

Even as more data started to get captured, the industry didn’t necessarily excel at using that data, Ogren said. “For years, we’ve had this information. But it was so much information that we didn’t know what to do with it. But now, our knowledge of what to do with this data has evolved.”

There’s a slow-motion evolution happening with how the industry approaches data tools, even if what exactly constitutes a data tool isn’t well defined.

The goal for this article is simple: Let people who know a lot about harnessing data share their take on where the industry is heading.

This Moment in Data Tools

Ogren suggested that there is an urgency to figuring out how to maximize in-store sales, a nod to the industry evolving from its reliance on fuel sales. “We really have to as an industry start to find who we are,” he said, adding, “We’re not just a petroleum industry anymore.”

Ogren cited data about product affinity as most valuable for many retailers. “When someone buys coffee, what are the five things that are purchased with that cup of coffee? I think that really drills down to the simplicity of what’s important. The number one purchase with coffee is an energy drink. People are purchasing it for later in the day, because at 3:00 p.m. they need a lift. So that’s where there’s a bigger chance to drill down further and say, how do we set our stores accordingly? How do we promote accordingly?”

It’s not hard to get off the ground running, but don’t do it blindly.”

Donnie Rhoads, director of business development at Vancouver, Washington-based The Convenience Group, noted that there are many vendor options available for retailers, regardless of size. “It’s not hard to get off the ground running, but don’t do it blindly.” Too many suppliers, too much software and data for the sake of data are some of the pitfalls to avoid, he said.

Jason Zelinski, vice president North American Convenience retail at NIQ, said that many retailers “have come on what’s basically a full-circle journey. The 1970s way of doing things was keeping your own books, probably on paper and then eventually with an Excel database. That was first-party POS data showing the top-selling items, which helped retailers to make basic assortment decisions. Some of our smaller retailers are probably still doing that today. The second stage of that is when they started going to second-party data, market data.” This allowed retailers to not only see what they were selling, but to see what everybody else was selling.

“Then the next stage is actually back to first-party data, analyzing basket composition, internal price elasticities, loyalty switching and supply chain position,” Zelinski said. “First-party data got richer.”

The fourth stage—the stage Zelinski said many top retailers are in now—is to “take the first-party data and enrich it with the second-party data. Bringing in market trends, enhanced product attributes, locational demographics and such.”

Tim Tang, director at Hughes Network Systems LLC, offered a different version of the evolution of data tools, with an eye towards larger retailers.

For Tang, the baseline is scan data, particularly around tobacco, and being able to monetize that POS data. “It’s shocking to me, actually, in this day and age, that so many store operators are not monetizing that,” he said. The problem, according to Tang, is that these operators are gathering data that is not properly formatted.

Next, Tang pointed to retail media networks. The biggest operators capture data about their own customers and then can work with large CPG companies. According to Tang, these operators “can go to the CPG manufacturers and tell them, ‘I have this many visitors every month, 15% of them are teenagers, 25% of them are mothers with young children and another 50% or so are young professionals coming in at these times. And what would you like to do, Mr. or Ms. CPG manufacturer, in terms of promoting your products in this space?’”

After that comes operationalizing POS data. “All these things that you could do with data, in terms of AI, anticipating customer needs, and the like, are wonderful,” Tang said. “But the big challenge is how to get started. Most specifically, I think the question is, ‘How do I take advantage of these capabilities with my existing tech stack.’”

They can’t even begin to fathom that those things can be tied together.”

AI and a New Interest in Data Tools

Bill Ivers is the CEO and co-founder of Taiga Data Inc. As the company was getting off the ground in 2019, he did a lot of the initial outreach to retailers. “Back then, the reception I would get if I used the word ‘data analytics,’ it was almost like, ‘Whoa. I’ve heard nightmarish things about that.’” Retailers were hesitant because they had heard stories about companies snarled in an expensive tangle of third-party products, integrations and dashboards.

“If you compare that reaction with where we are today, it’s unbelievable,” Ivers said. Retailers are past the point of hesitancy, he said, and are instead searching for the right tool.

Tang also noted a renewed sense of urgency. “It’s more expensive to run a store in today’s environment than it was before. And that makes your opportunity for profitability more narrow.”

Tang pointed to the emergence of AI as another factor contributing to a renewed interest in mastering data. Retailers are working towards using AI to be able to “put personalized and appropriate deals in front of the consumer.” But the major focus the past year or two has been on using AI to “control the stuff that happens inside your shop. … Cleaning up the inventory management, the back-office operations and the like, being able to understand what products should be sold and how much I should be carrying.”

We do have strong industry organizations and resources to help work through a lot of stuff together.”

Ogren also pointed to AI. “If somebody can go park in the street, put their credit card in a charger on the sidewalk, go to dinner and come back—how are we going to drive people to our stores? … We need this data. We need this AI technology to help us determine what our future is.”

“Every single company is thinking of the newest integration for whatever new tech is popular outside our industry,” said Rhoads. “But I still think our industry is behind the eight ball,” he added, pointing to the complex technical structure and abundance of legacy tech. “If you go into virtually any other retail setting, they can be set up with a tablet on day one. And they are done. Check that box, and they have so much information on the back end and plug-and-play integrations. And I think we all know that’s just not the case when you have fuel in the mix.”

Tang said that understanding the “technology debt” is going to be huge for the industry, and also pointed to the additional complexity of fuel as part of the reason. “You have an industry that is basically serving a highly combustible product through a self-service mechanism. That fundamental part of the business limits how quickly you can evolve on that side of the house.”

Implementing Data Tools

Just purchasing a tool, or many tools, doesn’t mean insights start to flow.

According to Rhoads, “You can get lost in ways to set up the different results that you want to get, just because there’s so much data that’s being collected. Build out a dashboard that captures that raw information and presents it to you in a way that’s not a foreign language. It’s really easy to get a tangle of different third-party services.”

“If you’re having to manage the data more actively, and it becomes more of a headache than a solution for you, that’s a problem, obviously,” Rhoads said. “So just making sure that it works for you in the first place is half the battle.”

Ivers of Taiga said a focus should be making sure the tools aren’t just shiny objects but instead are used as intended. “The digital transformation is about moving how you operate to be assisted by data and the technology tools that you’re using. They key there is getting staff adoption. When we think about our process for installing new software, it’s about 90% customer education and focusing on customer adoption.”

John Oakley, president and co-founder of Taiga, echoed that thought. “Most of the effort is on the change management side of the transformation. How do I utilize data to do things differently, more efficiently, to drive profit, to optimize my sets.” Each person in the organization, Oakley noted, has different needs for data.

Oakley said that for some retailers, “The mountain of data is just so cumbersome that they can’t even find the place to start, and others have the perception that there’s no way that they can be helped.”

“Maybe they’ve grown through acquisition,” Oakley said. “They might have three or four different POS systems or a couple different back-office systems and each one is managed differently. They can’t even begin to fathom that those things can be tied together,” he said. “It takes a little bit for that to become believable.”

Oakley noted that a key step is talking to other retailers that were in a similar place that have already gone through the process.

Data hygiene is key. According to Zelenski, “The best-in-class players are making sure their own house is clean. Because even if you’re going to build an analytic and insight solution in house, you need clean data, or if you’re going to work with something you’re going to buy it off the shelf, you need clean data. I’ve seen some companies struggle where they try and do both at the same time. They’re trying to clean their data and they’re trying to build internally. And they find it doesn’t work. Maybe it could have, it’s just that their data was backwards.”

Rhoads emphasized that retailers don’t have to do it alone. “We do have strong industry organizations and resources to help work through a lot of stuff together. And I think that’s really important.”