In 2024, less than half of people were concerned about energy prices (45%), compared to 77% in 2022 and 65% in 2023. Similarly, only 45% were concerned about inflation, compared to 70% in 2022 and 2023. On the other hand, the portion of people who said they are concerned about sustainability and climate change, geopolitical tensions, and potential recession has risen steadily since 2022.

Danes’ feelings about how well off they are personally are closer to the average for the five countries we surveyed, with more than half saying that their physical and mental health and personal financial stability are “good” or “very good.”

Danish consumers are less concerned about other aspects of their personal situation than in 2022 and 2023. Unlike those years, a smaller portion are concerned about the need to draw on savings to get by or worried about rising mortgage rates.

People spent more on basics and cut back on non-essentials. Three-quarters of people reported higher prices for products and services in the first half of 2024. During the same six months, people also reported that income and savings stagnated or declined.

The difference resulted in people reporting higher basic and discretionary spending. Over-the-counter medications—a necessity people can rarely forgo—was the only product category surveyed with a net spending increase, of 9% for the first half of 2024. Net spending on groceries was unchanged. (See Exhibit 2.)

People’s preferences for online- or physical-only stores are closely tied to what they’re buying. They have a strong preference for shopping at a physical store for frequent purchases such as alcohol, home care products, groceries, and snacks because of the convenience or price, or because they may prefer getting help from a flesh-and-blood salesperson.

The equation changes for price-sensitive products that people buy less frequently or on an impulse, or when they want more options to choose from. Categories for which Danish consumers are most likely to make a purchase online are: apparel (41%), luxury fashion (38%), toys and games (36%), over-the-counter medications (30%), home appliances (28%), and personal care items (27%).

How Companies Can Woo Danish Consumers

To strengthen ties with Danish consumers and stay competitive, companies should consider acting in three areas: product assortment, pricing, and promotions. We've found that the impact is greater when companies launch changes in all three areas simultaneously. However, because of the time and resources needed, most companies choose to address one area at a time. In addition, for changes to be successful, companies need a strong data analytics foundation.

Localize product assortment. Danish consumers are spending less, especially on non-essentials. They have different preferences for where they like to shop, and many still like buying in a physical store. To adapt, companies could customize what they offer in their physical locations to meet local demand and offer a more broad, global range of products on their e-commerce platform, which could appeal to shoppers who go online to browse or be inspired. In addition to increasing customer satisfaction, such changes minimize excess inventory. Supermarkets in rural areas of Denmark, for example, often stock local specialties and products from nearby farms, catering to the preferences of customers in those regions. But the same farm products are in less demand among city shoppers, so urban supermarkets typically don't carry them.

Adopt dynamic pricing. Danes are becoming more price sensitive. Companies could use data-based dynamic pricing strategies to counter shifting consumer preferences while improving their ability to respond to fluctuating volumes, local market conditions, commodity prices, and competition.

A leading European furniture retailer adopted dynamic pricing as part of a strategy to sell lower-cost items in order to respond to inflation and consumers’ desire for more affordable home furnishings. To manufacture lower-priced products, the company intensified its cost focus across the board, including for design, material development, production, and marketing. The company used an advanced pricing engine to adjust prices dynamically to account for price sensitivities in the different regions it served. The changes enabled the company to increase sales despite continued challenges in the furniture industry.

Make promotions hyper-personalized. In addition to being more price sensitive and reluctant to buy non-essentials, consumers show less interest in loyalty programs relative to other shopping factors. Companies can counter such sentiments by individualizing loyalty programs and promotions.

Companies with successful programs use advanced analytics—including AI—to offer a level of personalization to loyalty members that other personalized promotions cannot match. The exclusivity that analytics-based promotions offer keeps consumers engaged and meets their need for good value and quality, making it more likely that they will keep shopping.

Nike’s membership program is a prime example of an AI-powered, hyper-personalized loyalty experience. People who download the free Nike membership app receive special access to exclusive products and experiences personalized to each shopper, free shipping, and more lenient return policies. In exchange, Nike collects consumer data from both the app and offline channels, which the company uses to improve its highly targeted, relevant promotions. For example, a Nike member who typically buys outerwear during the winter may get related promotions before the season starts.

Enhance data collection. To successfully launch initiatives in product assortment, pricing, and promotions, companies must improve their ability to collect rich data on consumer behaviors and preferences across sales channels. Rich data includes consumer demographics, interests, and motivational drivers; what people buy, when, how, where, and why; and how they engage with sales channels, including through promotions or loyalty programs. If they revamp their digital presence and loyalty programs, companies can use the access they have to first-party consumer data to capitalize on customer relationships in ways that in the past were not possible.

Acknowledgements
The authors would like to thank Mary Patrikiou and Martina Scrocco for their helpful comments and suggestions. The authors would also like to thank Megan Moore for conducting the research upon which this report is based.