To thrive, stores must build customer loyalty.
One way to accomplish this: offering frequent shopper cards.
“Frequent shopper cards provide various small incentives to consumers for buying from their affiliated stores, such as discounts,” Dr. Steven Senger, associate professor of mathematics at Missouri State University, said.
But these discounts only come in exchange for consumers’ purchasing data.
The value of purchasing data
Purchasing data carries precise insight into consumer habits.
“Stores can tell who bought which things and at what prices,” Senger said. “The cards also record which days of the week or month consumers typically shop and at what time of day.”
Why is this information valuable?
Because it can be mined for patterns of spending.
These patterns can reveal paths to greater profits, Senger explains.
“If a store slowly raises the price of their eggs over time, for example, they may notice that people stop buying them above a certain price,” he said. “Stores can then peg the price of their eggs just under the amount to maximize their profits.”
More than one variable may be at play in a single purchasing decision.
Price could combine with the influence of weather or meal association, for example.
“There are certain things people buy more of in colder or warmer weather, which spurs seasonal fluctuations in sales,” Senger said. “Consumers’ recognition of certain foods as being for breakfast or dinner may also prompt stores to sell more of items in the mornings or evenings.”
How purchases shape consumer profiles
While stores can record a lot of data without frequent shopper cards, the cards add a key component to the equation: a look at the people behind the purchases, Senger shares.
“Frequent shopper cards’ demographic data usually includes the customer’s address,” he said. “Pairing this with data on a customer’s age, stores can often make guesses about customers’ income, how many people live in their house and their habits.”
With more variables of consumers’ habits comes more complexities.
Profiling these complexities can become key to store survival.
“Each purchase by consumers can be thought of as a data point in a very large dimensional space, where each dimension is a variable or piece of product data,” Senger said. “The store with the best data analysis can make better predictions and fuel better market performance.”
Harnessing your power as a consumer
The impact of trading data for discounts makes each consumer’s purchasing habits of value.
Consumers can channel this value into market power with the purchasing decisions they make.
“I tend to support smaller companies,” Senger said, “and I prefer to shop at stores that are very transparent about how they will use my data.”
The number of companies involved in frequent shopper card programs can affect the transparency stores offer.
Programs that stem from consulting agencies, Senger notes, can fuel further data mining.
“Consulting agencies may only access consumer data to map wider market trends,” he said. “But they may also sell data to other companies, which can lead to targeted marketing or even entail massive amounts of junk mail and robocalls.”