Retail Transaction Data Suggests Frequent Shoppers Aren’t Necessarily Loyal Ones

March 21, 2014

This article is included in these additional categories:

Brand Loyalty & Purchase Habits | Brand-Related | CPG & FMCG | Food & Restaurants | Retail & E-Commerce

Cardlytics-Loyalty-to-Single-Retailer-by-Category-Mar2014A frequent customer is not always a loyal one, says Cardlytics in a new study [pdf] based on a “whole-wallet” analysis of transaction records held by consumers’ banks for nearly 70% of US households. The research indicates that customers who frequently visit specific retailers tend to be heavy category spenders, meaning that they also frequently visit other retailers in the same category. Instead, true loyalty is often the domain of “light customers,” who make fewer trips to stores but typically shop at the same ones.

The analysis looked at 5 retailer categories: restaurants; apparel; gas and convenience; grocery; and general retail. Rather than simply analyze how often customers of these categories visit specific stores (which might be how the stores themselves determine loyalty), the whole-wallet approach based on transaction records looks at how often customers visit stores as a percentage of their total category visits.

Customer loyalty differs among the various categories:

  • For restaurants, 44% of customers dine at the same one for more than half of their dining trips out;
  • For apparel, 53% shop at the same store the majority of the time;
  • For gas and convenience, 57% are loyal to the same store most of the time;
  • For general retail, 80% are loyal a majority of the time; and
  • For grocery, 81% visit the same store most of the time.

On the surface, that shows a significant degree of loyalty to favorite stores. But a deeper analysis indicates that loyalty (defined here as at least 50% of category trips made to the same store) is much more prevalent among infrequent than frequent customers of each category.

For the purposes of the analysis, customers of each category were broken down into 3 segments by frequency of category trips:

  • Light: Customers making fewer than 52 trips a year; less than once a week;
  • Medium: Customers making between 52-129 trips a year; 1-2.5 times every week; and
  • Heavy: Customers who made 130 or more trips in a year; at least 2.5 times a week.

In each case, “light” customers were more loyal than “heavy” customers. Here’s how those comparisons broke out at the extremes by category:

  • Only 23% of “heavy” customers in the restaurant category visited their favorite store more than half of the time, compared to 57% of “light” customers in the category;
  • The gap was even more severe in the apparel category, where just 15% of “heavy” customers made more than half of their trips to their favorite store, compared to 75% of “light” customers;
  • In the gas and convenience category, 69% of “light” customers frequented the same store at least half of the time, compared to 39% of “heavy” customers;
  • The gap was much narrower in the grocery category, where 86% of “light” customers visited their favorite store at least half of the time versus 72% of “heavy” customers; and
  • A similar pattern was apparent for the general retail category, where 89% of “light” customers visited the same store the majority of the time versus 65% of “heavy” customers.

Obviously, heavy visitors to a category are going to account for more dollar sales than light visitors – even to particular stores. And in general, the top 20% of customers accounted for a greater share of spending in each category (63-69%) than share of trips (56-60%).

But the data still shows that those top customers (by absolute visits) aren’t all that loyal (by percentage of visits). That means that marketers should craft their messaging for different types of customers, not just those that appear to frequent their stores the most.

About the Data: Cardlytics partners with nearly 400 financial institutions including Bank of America, PNC, Regions and Lloyds Banking Group, providing insight into consumer purchase behavior for ~70% of U.S. and ~30% of U.K. households, across all stores and categories.

The data used in the article is for the first 6 months of 2013, and is drawn from the Cardlytics Automated Transaction System (CATS), a proprietary technology. Cardlytics notes that “the increase in card use is what enables Whole-Wallet analytics now ”“ there are transaction records for the majority of consumer debit, credit and prepaid card spending, held securely by the consumer’s bank.”

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