Big Data Decisions

Retailers are discovering the power of data to bolster their capacity to personalize the customer experience, increase sales and drive brand loyalty.


No longer is each convenience store transaction a simple exchange of goods for cash. Technology empowers businesses to turn each purchase into an opportunity to mine information about customers’ shopping habits that then can become the basis to design highly-personalized marketing strategies.


“As an industry, we have seen a considerable change recently in our business. Highly-informed customers, [product] selection and pricing are challenging us to be more sophisticated in how we analyze data, answer difficult questions and execute efficiently. The margin for error has gotten much smaller,” said Joe Hamza, chief operating officer for Nouria Energy Corp. Headquartered in Worcester, Mass., the company owns and operates 116 convenience stores, including the brand Lil’ Mart, and 49 carwashes in Massachusetts, Connecticut, Maine, New Hampshire and Rhode Island.


Since the introduction of scan data collection in c-stores, the primary function has centered on inventory control. Tracking sales enables category and store managers to more accurately calculate stock availability, and therefore more precisely gauge reordering so stores aren’t left short-changed on products or overstocked.


“Sales analyses help improve a stable supply of products on shelves. Store operators can use historical sales data to forecast demand for the coming weeks based on seasonal trends. That application is very instrumental, and stores have been moving in this direction for quite some time,” said David Bishop, managing partner at Balvor LLC, a sales and marketing practice based in Barrington, Ill.


“We run sales reports on cooler and foodservice items to make sure we have supplies. For cigarettes, we do weekly reports,” said Lisa Dell’Alba, president and CEO of Square One Markets Inc., located in Bethlehem, Pa. “We’re a heavily cigarette-based chain, so we make sure we always have the brands our customers want us to have.”


Like many smaller c-store businesses, Dell’Alba doesn’t see the return-on-investment value of running frequent reports across all product categories. With nine Square One Market sites, she isn’t convinced analytics provide her anymore insight into her customer base or the marketability of products than she’s already deriving from basic inventory assessments and managers’ observations.


“Data can be cumbersome for a small company to sort out what is important and what’s not,” she said. “You have to sort out the noise and figure out what to focus on. There are opportunities to collect data with technology, but for us, that would mean less customer interaction.”


That said, Dell’Alba does use data analyses as an internal incentive.


“We run reports to create competitions between stores based on the number of items sold. We have competitive managers and they are very enthusiastic to beat each other,” she commented.




For larger regional, multistate and national c-store chains, the empirical evaluations scan data analyses provide have become a necessary business tool.


According to the Retail Vision Study by Zebra Technologies, and reported by, nearly three-fourths of retailers agree that managing big data is a business-critical function. What’s more, approximately two-thirds of respondents stated they are prepared to invest in automated technology for better inventory management over the next few years. In fact, 70% of retail decision-makers said they’re ready to add Internet of Things (IoT) features to scan data programs, such as installing shelf sensors that detect when products are removed and automatically adjust inventory numbers.


“As you grow the store base, you as an operator become disconnected from the physical shopper. There are more points of distribution and more outlets. You can’t just rely on intuition and personal experience,” said Bishop.


Depending on the area of the business, Nouria can run reports daily, weekly, monthly, quarterly or annually.


“We use a multidimensional approach when analyzing the performance of a particular metric, category, product or overall sales,” said Hamza. “For example, when analyzing a particular category, we conduct the following process: review current six-week trends and current period performance versus the same period the prior year; measure its impact on other complimentary categories and overall sales; conduct internal benchmarking using average chain performance versus each individual division; and review its relative performance versus the market using market data. The insights from the analysis are then used to guide our decisions and actions.”


Even though Dell’Alba’s use of data is limited, she does conduct comparisons when introducing new products or when vendors switch promotional strategies so she can measure performance reactions.


“For example, Pepsi recently changed its sales format. It used to be buy two 20-ounce drinks for $3, and now it’s buy one, get one free. I wasn’t sure it would do as well as the $3 program so I created reports to evaluate both programs,” she said. “We also do that when we bring in new products. We did it when VUSE and VUSE Vibe came out.”




Of course, line-item analysis remains the predominant purpose behind scan data programs in c-stores, but there’s a growing curiosity about what other value can be mined from the input, especially if it can be used to identify new marketing channels. The current push is toward providing individuals with more personalized attention by highlighting preferences. Perhaps one of the more apparent examples of this application is online advertising.


Websites and internet service providers watch where you click and how long you linger on a page. This observation then serves to target future ads featuring products you’ve expressed interest in, or items similar to products you’ve expressed interest in. These aren’t random ad placements. They’re based on your click history. Now, brick-and-mortar retailers want scan data to help them to attract more customers based on personalized messages created from purchase histories.


“Capturing more robust data allows stores to do transactional analysis that helps identify customers’ affinities, said Bishop. “Having that insight allows retailers to make adjustments to merchandising, and evaluate if it makes sense to relocate a product so it’s adjacent to a complimentary product. For example, if the analysis shows correlations with gum purchases and hot coffee, a retailer may want to merchandise some gum near the hot coffee to entice those coffee customers by offering a special deal. That could increase the likelihood of cross-sales possibilities.”


The analysis doesn’t end there. Retailers can use the details to further target promotional efforts. Data obtained through loyalty programs not only indicate shopper preferences, but also how often they frequent a store and visit patterns, such as which days of the week as well as what time of day they shop. This knowledge can enable businesses to send specific promotional messages to entice loyalty members to visit during a different time of day or increase their number of visits.


“Loyalty customers can be divided into frequent, infrequent or lapsed shoppers. You can try to reengage the lapsed customer by sending communications with offers to try to increase their frequency of visiting,” said Bishop. “That’s a much more precision or objective approach. There’s a saying that 20% of customers drive 80% of sales. The mission critical is to serve that 20% and grow them in various ways such as increasing visit frequency or amount of spending per trip.”

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05 Mar 2018

By Anne Baye Ericksen