Fashion’s New Look for Stores: Bigger, Better, Fewer

LONDON—Fashion retailers have found a way to make their shops dazzle customers again: make them more like Apple stores.

Brands including H&M and Zara have closed hundreds of stores in recent years to cut costs as more shoppers turn to e-commerce. Now they are investing in those that remain to woo customers in ways they can’t online.

The new-look stores are typically larger and more spacious, offer services such as beauty salons, repair stations and coffee shops, and enable new digital features such as apps that allow shoppers to rummage virtually through the storeroom.

“Now it’s about engaging with consumers and giving them an experience,” said Henrik Nordvall, manager of H&M’s U.K. business.

At the brand’s recently redesigned store on London’s Regent Street, foot traffic matters more than sales figures, Nordvall said. While in-store sales are still strong, many customers spend time there developing an affinity with the brand and then buy clothes online later, he added.

The refurbished store is home to a floor-to-ceiling TV screen that the company says is the biggest in any store in Europe, a beauty bar for customers to book nail or eyelash treatments, and a rental section where shoppers can borrow selected items, especially relatively expensive clothes from H&M’s designer collaborations.

Since the changes, the average duration of a customer visit has increased substantially, said Nordvall, who declined to provide specific numbers.

By turning their stores into destinations that shoppers actively seek out and spend time in—a model that Apple honed with its roomy, landmark stores filled with usable gadgets—the fashion retailers are redefining the clothing store for the digital age.

Retailers once needed a large network of stores “to reach people, but now they have the internet for that,” said Patricia Cifuentes, an analyst at the asset manager Bestinver. “Now stores are about brand image. They’re like tourist destinations.”

Not every retailer is following the approach of the big global fashion brands. Macy’s, for example, is opening smaller stores as a way of bringing its brand to places where customers run their daily errands. The electronics chain Best Buy is closing larger locations and opening small stores instead.

But for global fashion’s heavy hitters the shift toward fewer but better stores is well under way. While the investment could backfire if the stores fail to draw sustained traffic, for now the strategy appears to be working.

Inditex, the parent of Zara, has eliminated a quarter of its stores since 2018 and now has 5,745 locations across its brand stable, which also includes Bershka and Massimo Dutti. Yet the Spanish group’s total revenue from stores increased 8% in 2022 compared with four years earlier, with each store selling 30% more on average, Chief Executive Officer Oscar Garcia Maceiras said on a recent earnings call.

After closing its weaker locations and upgrading the rest, “We have been left with a network of bigger, better and more beautiful stores in the best retail destinations globally,” Garcia said.

Despite operating fewer stores overall, Inditex increased its capital expenditure budget for 2023 by 14% to 1.6 billion euros, equivalent to about $1.7 billion, half of which is earmarked to make improvements to stores.

Much of that money is being spent on the rollout of a new Zara store design—including at new U.S. locations in Baton Rouge, La., and San Antonio—to make the shopping experience more enjoyable.

Essential to the new layouts is making stores feel roomier by having more open space between displays so customers don’t feel crowded. With more open space, stores will increasingly have discrete in-store boutiques to highlight individual collections.

Zara has a team of in-house architects who design its stores, and uses pilot stores at its headquarters in Spain to experiment with new layouts.

Garcia, who regularly visits Zara stores around the world, said in a recent interview that store managers routinely tell him they want to expand because only larger stores are able to accommodate most or all of Zara’s range.

The Zara store in Miami is one beneficiary of the move toward bigger and better: It is doubling in size, according to Garcia, to provide the more spacious experience the company wants to deliver.

Bigger stores are more productive, Zara has found. Though stores are getting larger, sales per square foot is now up 16% relative to 2019, Garcia said.

Zara is cramming its stores with new tech such as automatic return and collection points, as well as self-checkout areas. Customers can use the Zara app to check the contents of the storeroom to see if an item is available in their sizes, for example.

H&M has shrunk its store count 14% from its 2019 peak to 4,375 outlets today. The company doesn’t break down its revenue into physical and online, and says the two parts of the business are complementary.

Increasingly, stores “are a way for our customers to get inspiration,” CEO Helena Helmersson said in a recent interview.

H&M upped its capital spending budget 43% for 2023 to roughly $1 billion, partly to push ahead with store modernisation.

Even before the Covid-19 pandemic, H&M’s leaders recognized it was time to update the physical store to offer a more engaging experience, said Nordvall, the U.K. manager. When the pandemic led to a surge in online sales, the company accelerated its effort to redesign its stores, he said.

The revamp of the Swedish brand’s store on London’s Regent Street was aimed at encouraging customers to spend more time there. It has a secondhand area, Lego sculptures in the children’s section and fitting rooms with a built-in selfie function.

H&M also uses the store to host events for shoppers who sign up for its membership program. In November, it held a party to mark the launch of a collaboration with the fashion house Rabanne.

The Japanese brand Uniqlo is still expanding in Western markets, where its footprint is significantly smaller than H&M and Zara, but it is also opening so-called destination stores.

The chain’s recently opened store in London’s Covent Garden is located in a converted Victorian-era carriage works building, where shop floors loop around a brightly sunlit courtyard beneath a vaulted glass roof. There is a Japanese tea shop upstairs with a rooftop balcony, and a florist downstairs.

Visitors can use a machine to print their own T-shirt designs, have clothes altered or mended at the store’s repair station, and lounge in comfy chairs while browsing coffee-table books.

While online sales are growing, destination stores “have become the driver of European earnings,” as well as places where the brand communicates what it stands for, said Taku Morikawa, the CEO of Uniqlo Europe, during a recent earnings presentation.

Only a memorable in-store experience will make customers trust and admire your brand, he said.

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion