Grocery retailers have a common phrase – “If it isn’t on the shelf, customers can’t buy it.” Their business is driven by creating trust that when the customer wants an item, they will be able to find it.
Whether the retailers are investigating a new trend or ensuring staples are always on the shelves, they spend a lot of time thinking about the products they stock. And it got us wondering – how do grocery stores leverage data to make this important decision?
Traditionally, retailers have many factors to consider when determining which items to stock, including:
- In-person traffic: As shoppers return to their pre-pandemic habits, stores are getting busier. Assessing and understanding foot traffic is essential to keeping shelves full. Retailers use various tools to understand what’s happening in their stores, from foot tracking counting systems and consumer predictive analytics to forecasting services. They then use this data to determine what needs to be ordered and when.
- Seasonal items: Knowing which items aren’t selling is just as important. Grocery retailers operate on slim margins and the business relies on keeping the right items in stock at the right time. For example, yeast is an important part of many winter holiday baking traditions and will sell quickly in November and December. Stores can stock less yeast during the warm summer months when people do not bake as often.
- Shelf-life expectancy: Fresh products are a must for any grocer. And they are laser focused on ensuring available items are sold well before a printed expiration date or any visible signs the product is going bad. Proper shelf life expectancy management also ensures the stores place effective orders to keep shelves full of the freshest items.
- Customer behavior: With hundreds of people walking through a grocery store every day, it can be difficult to identify each individual’s needs and preferences. Are they cooking for one or four? Are they cooking at all? How many have families? Do they prefer healthy foods or comfort foods? Every piece of information helps create a clearer picture of the customer, which grocery retailers can use to anticipate buying behaviors and stock the items their customers expect.
Rethinking the traditional grocery shopping experience
Kroger is a national chain of grocery stores, with about 2,800 stores nationwide. In this footprint, the company engages with millions of customers every day. And each of those customers is a great individual data point.
As more customers gravitate to using self-checkout (SCO) machines, Kroger looked for new ways to gather metrics that will help them improve the customer experience. The grocer turned to IBM Technology Support Services to uncover insights from the more than 25,000 SCO machines.
The solution IBM created was custom-built to Kroger’s needs and meticulously collected and organized maintenance, repair, and restore time data from all the vendors who service Kroger’s SCO stations. The resulting report gives the Kroger team a clear a view of all stores nationwide, with the ability to generate insights by division, geography and even by store.
“We can tell Kroger what the better performing stores are versus the lower performing stores,” said Joy Donaldson, Retail Delivery Executive with IBM Technology Support Services, “and if there’s anything in the data that can help them improve the performance.”
And even seemingly small insights can result in big changes to the customer experience.
“Share as much information with your provider as you can,” said Donaldson. “No matter how minute that information is, it benefits everyone. The more data we have, the more we can do data analysis, determine trends and make predictions.”
Next, Kroger plans to work with IBM to expand the current report with data insights from its help desk.
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