What Supermarkets Can Learn from C-Stores

Several of our posts have focused on the importance of innovation and the customer experience, and how retailers must make continuous improvement in these areas a priority. Along those lines, a recent SupermarketNews article shared some interesting insights on the significant success the country’s 153,000+ convenience stores (c-stores) have experienced due to making ongoing improvements via “digital transformation.”

The piece quoted Scott Langdoc, a strategist specializing in the grocery chain, drug, and convenience/fuel retailing segments at Amazon Web Services, who said, “By focusing digital transformation efforts on supporting emerging customer journeys, optimizing product and service offerings, and prioritizing efficiency of retail operations, c-store retailers are working with Amazon Web Services (AWS) to double down on innovation while recovering revenue and attracting new customers.”

The article went on to explain the different product fulfillment expectations at c-stores, which include fuel fill-up, basic snack and beverage purchases, buying prepared foods like pizza or sandwiches, a quick errand for a household necessity or a combination of those scenarios.

Langdoc also noted that, more frequently, customers expect a personalized experience regardless of how or where they engage in the c-store.

Examples given included:

  • While a customer pumps fuel, they order a slice of pizza at the dispenser via a voice-activated order system and use their mobile phone to pay for both the pizza and their fuel.
  • A shopper buys a fountain drink in a store and gets a personalized discount to buy fuel as an incentive because the customer hasn’t purchased fuel at that station in the last month.
  • A customer grabs the items they want to buy at an Amazon Go store and walks out without having to stand in line to pay at a traditional cash register.

The Bottom Line
While recognizing that fuel remains the top selling c-store product category, the article concluded by suggesting, “in-store product sales and an extensive prepared food menu represent the largest overall sales growth categories, and on average, they are the biggest contributor to overall gross profit.”

Therefore, retailers should focus on capturing the broadest spectrum of transaction details possible and applying the analytics and machine learning to generate hyper-accurate predictions of future demand.

“This transaction detail can help optimize category plans, profitable private label assortments, high-selling menu offerings, and better in-store stock availability,” the article said.

Read the full article…