Innovation Roadmap: Data-Driven Decision Making
NATIONAL REPORT — With years of scan data, coupled with loyalty program data and all the other sources convenience retailers have of collecting and accessing data — including vendors and research companies — making profitable decisions is easier now than ever before. It's also more necessary than ever before in order to stay competitive in today's market.
"Today, data is king," said Ed Burcher, a partner with Business Accelerator Team, a convenience retailing consultancy based in Phoenix. "The availability and use of data is needed today at all levels of retail, including operations, promotions, category management, and support departments such as real estate and finance."
Gone are the days of making decisions based on "a gut feel and observations," he said. Those who have embraced data to improve operations continue to thrive and grow faster.
[Read more: Charting an Innovation Roadmap]
There are so many sources of data for c-store operators today, both internal and external. Point-of-sale (POS) systems, backoffice systems, loyalty programs, fuel pumps and more provide a tremendous amount of data to help retailers make decisions around sales, labor, product assortment, promotions, planogramming, etc. Most retailers combine their internal data with external sources, such as vendor data and research companies like IRI and Nielsen.
Along with gathering data, c-store operators must decide how they want to use the information and then find ways to interpret what they collect. On a basic level, most companies are using transactional data to understand sales and predict what to reorder, as well as to schedule labor depending on sales, daypart and more, according to Burcher.
"It is important to know what questions you want answered, as this drives how you will organize and use this information," he explained. "I've helped companies design and implement dashboards, scorecards, KPIs and benchmark reporting that not only helps in day-to-day operations, but can also be used at the strategic level, including new markets, new offers and businesses to enter and exit."
Gathering & Using Data
"I don't think I recall data ever not being important because it's always been the key before we make a move, but data is a lot more enhanced now than what we were used to in the past," observed Pervez Pir, president of retail at Loop Neighborhood Market, the Freemont, Calif.-based operator of 135 convenience stores.
"Our POS and pumps are collecting data, so we know every transaction and then, our loyalty program through our app is capturing data, including how long they stay on a page and what they are clicking," he explained. "The key things are retail dollars — but you are looking at units because that justifies if you are really moving the needle — as well as basket size and frequency."
Loop also prioritizes loyalty data because it "really lets you look at behavior patterns, and we look at it on a granular level such as frequency, basket size, what customers are buying, when they shop, and to understand the promotions to offer them," Pir said.
Before loyalty data, retailers were basing marketing on POS and pump data, creating generalized offers on energy drinks, soda and other popular items. Now, with the inclusion of loyalty, he said they can drill down into data to see what each person is buying and target products to them.
"We are doing that right now with a campaign where we have five offers available and when a loyalty member punches in their phone number, they get a targeted message for either an energy drink, water or one of the other options based on what they purchased," he said.
The retailer also looks at data on promotions to measure success, along with "affinity products" to see what items are purchased together, so they can make decisions on new possible promotions. "We look to see what program worked and what didn't based on units, as well as affinity and frequency," Pir explained.
Loop, like many other retailers, looks at external data as well. The chain uses IRI, Nielsen and vendor data, especially for merchandising. They look at the portfolio for vendors to see how each category is doing as a whole and how their stores are performing compared to the competition. This data is reviewed at least quarterly, if not every two months.
"This could highlight an opportunity where there are things we are not taking advantage of, [where we] should be testing things, as well as if an item is not selling with us, but is selling well with others," Pir added.
Data also can be used for labor scheduling, and in predictive ways for product launches, seasonal events and promotions, according to Burcher. "Data can help with product-test analysis to know what is working and what is not to maximize results across an organization," he said.
Taking Data to the Next Level
Technology continues to advance when it comes to analyzing the mountains of data convenience store companies are able to collect these days. Proprietary and vendor-based solutions can help to organize and collate the data so that information can be pulled out and implemented to drive profit, whether for new items, promotions, events or restocking.
Savvy c-store retailers are using data to do much more than see what is selling in their stores. They are forecasting for the future and using AI to take learning to the next level.
"There are many ways that using predictive data and analysis can help a company," said Burcher. "In a tactical way, it can help with scheduling promotions, events, seasonality and other factors. It's most valuable when the data and the insights gleaned from it can be used to anticipate behavior."
In addition, predictive data and analysis can be used strategically to understand customer behavior and enhance customer experience. For instance, Loop created a proprietary tool called Right Sense that is based on trends and patterns. The retailer uses it to predict sales at current stores, as well as to predict sales in site selection, according to Pir.
"Right now, we started with food to predict based on sales and waste to see what would happen the following week and how much to order based on trends and patterns," he explained.
When it comes to AI, the industry is just beginning to scratch the surface of what's doable.
Loop currently utilizes AI at the operational level. For foodservice, the company might look at which store had the largest waste the day before, or what is the best-performing store for chicken wings. The chain mostly uses internal, proprietary technology, but also leverages tools such as Microsoft Power BI and Tableau business intelligence software.
"How we process the data has changed completely. Before, you used to pull reports by data and parameter and now, there is more live data being streamed so we can see something within two or three minutes of it happening rather than waiting for the day to close," Pir said. "Now, we can make changes throughout the day if we are not hitting our numbers. We didn't have that level of data 15 or 20 years ago."