Grocery and cosmetics shop in Tangier, Morocco

Are you tired of walking into your favorite store and never finding what you’re looking for? A new data-based method is here to help! Researchers from Washington State University have figured out how to ensure you can always find your go-to products in the store – and boost impulse buying.

A data-based method for periodically rearranging products enables retailers to optimize new store layouts based on customer familiarity with where their favorite things used to be. This new method uses past customer transactions to give physical stores the same personalized shopping experience that online retailers like Netflix and Amazon use to get you to buy more.

Chuck Munson, a professor at WSU Carson College of Business and co-author of the study, said:

“What’s new here is that we designed our model so that customers walking down an aisle they normally peruse will notice products they will likely be interested in based off associations with what was there before,” said Chuck Munson, a professor in the WSU Carson College of Business and corresponding author of a study appearing in Expert Systems with Applications. “Our analysis shows that if you are a store that likes to rearrange periodically this would be a smart way to do it.

Supermarket shelves full of goods and an employee

Gihan Edirisinghe, lead author of the study, had the idea for this research after a trip to Walmart a few years ago. He and his wife were walking down their usual aisles but couldn’t find their usual products. This led him to wonder if the store had put a lot of thought into the rearrangement. When he got home, he discovered that there wasn’t much research on the best way to rearrange products in a store periodically.

So, Gihan and Chuck teamed up to tackle the problem. They used data mining techniques to analyze tens of thousands of real customer transactions and came up with a three-step process to determine the ideal product placement in stores that rearrange their wares periodically.

First, the process finds the store’s most profitable products and places them in highly visible locations. Next, it matches products that tend to be bought together and places them next to each other. Finally, it takes advantage of customers’ familiarity with where products used to be to determine future store layouts.

“This last step is designed so that people looking in a familiar place for, say, potato chips will notice something new that our data tells us will interest them. Every rearrangement can then be used as the basis for the next. To the best of our knowledge no previous research has considered this effect.”

The researchers compared their method to other product placement methods and found that their method outperformed them. However, the store’s target market is important – for stores with a more casual target market, like gas station stores, a one-time optimization of products might be better. But for stores with a more high-end target market, like Whole Foods, their method is the way to go.

The researchers hope that their study will attract enough interest from commercial retailers to put their method to the test.

“Our allocation method could ultimately be something that store managers could install and use with a little training. When you take into consideration the fact that 80% of shoppers don’t make a list before visiting a brick-and-mortar retailer, it is easy to see how important something like this could be to maximizing profits and helping physical stores compete with online retailers.”

Image Credits

In-Article Image Credits

Supermarket shelves full of goods and an employee via Wikimedia Commons by Lars Frantzen with usage type - Creative Commons License. May 25, 2013
Grocery and cosmetics shop in Tangier, Morocco via Wikimedia Commons by Diego Delso with usage type - Creative Commons License. December 11, 2015