Online shopping has grown steadily over the past few years. One study found that “online sales grew by 15.1 percent in 2019 and accounted for 51.1 percent of all retail growth last year.” This year, more consumers than ever have shifted to online shopping as part of their regular routine. According to a recent report, “42 percent of consumers are using digital channels to engage in activities more often than they did before.” The U.S. Census Bureau also reported first quarter eCommerce sales to be up 2.4 percent ($160.3 billion) from the fourth quarter of 2019.
Machine Learning Empowers C-stores to Predict Consumer Behavior and Increase Profit
The current c-store customer journey is much more complex than in years past, but it is also more important than ever before. Figuring out what customers want is a never-ending process because customer demand and expectations change. This is especially true during periods of rapid environmental and economic changes when consumers are likely to adjust their purchasing behavior and spending habits (i.e. during times of economic downturn, certain CPG sales increase while others may decrease).
Increase Shopper Frequency With Greater In-Stocks
It is no secret that increasing shopper frequency and retaining customers is key to operating a successful c-store. In the last few years there have been several top c-store chains that have been able to drive more foot traffic to their stores, which then leads to increased sales and profits.
C-stores have been a staple in our communities for both local shoppers and travelers who need last-minute or everyday products. They have come very far since the early days of just offering a few snack choices and ice while being open 24/7. Today, c-stores face much greater competition than ever before.
In a previous blog post, we discussed how demand planning is crucial during a crisis. Demand planning is the stabilizing anchor in a volatile supply chain. Demand planning may sound like old technology, but it is the foundation of a profitable supply chain. However, not all solutions are created equal.
So what demand planning solution is right for you? It depends. There are a number of factors to consider before making a decision. While researching the various options, you should evaluate solution providers to see how they perform and compare the results. At a minimum, each solution provider should offer a pilot or trial so your retail company can see estimated profit improvement before making any final decisions. Once a trial is conducted using your stores’ data, you can see what actual results would be for each solution provider to determine value.