At a time of realignment for the pure-play e-commerce sector, British fashion retailer Asos is putting its turnaround phase behind it. The company is implementing a ‘new commercial logic’ designed to decouple growth from deep discounting. At the World Retail Congress in Berlin, José Antonio Ramos Calamonte, Chief Executive Officer (CEO) of Asos, explained the new strategy. He explained how the British fashion giant is using AI-powered personalization and a redesigned loyalty program to ensure long-term profitability.
Away from the discount trap
Since taking over in 2022, Ramos Calamonte has led a rigorous transformation. This aims to manage the ‘rollercoaster effects’ of the post-pandemic period. The key challenge is to move away from a business model that relied heavily on excess inventory and performance marketing to increase volume.
“We are coming from a period of a lot of growth, but not necessarily sustainable, profitable growth,” noted Ramos Calamonte. The new strategy focuses on ‘product sovereignty’. It’s about putting the right inventory on the market at the right time to encourage sales at full price. He cited a recent collaboration with Adidas as a model for future expansion. This sold out within days without any discounts. “It’s not about finding silver bullets or magical solutions. It’s about continuing our journey in that direction.”
Redefine loyalty through experience
A cornerstone of this transition is ‘Asos World’. The loyalty program deliberately avoids the industry-standard points-for-discounts model. Despite initial internal skepticism, the program has seen high participation. It has 3.5 million members in the UK and 20% adoption in recently launched markets such as Germany and the US.
The program focuses on early access to exclusive collections and real-world experiences. According to Ramos Calamonte, top members increased their consumption by nine to 20 percent.
“If our story to consumers is about the best products and experiences, but then we give a 20 percent discount, that’s not built into that experience. We didn’t choose traditional discount mechanisms because that’s not what they want.”
AI and ultra-personalization
For a primarily digital retailer, the integration of artificial intelligence (AI) is no longer optional, but fundamental. Asos reported that 15 percent of code is now written by AI. 20 percent of purchasing decisions and 50 percent of customer service interactions are managed by automated systems.
However, the strategic focus for 2026 and beyond is on ‘ultra-personalization’. The goal is to create a unique storefront for all consumers. AI is supposed to suggest outfits based on previous purchases, for example combining a newly purchased dress with the right accessories for a specific occasion. This level of relevance is seen as a key driver to unlock the remaining 70 percent of the retail market that is still offline in major European territories.
Managing returns through consumer responsibility
Returns remain a constant source of friction for the European fashion trade. This is particularly true given the EU’s changing sustainability expectations. Instead of relying solely on logistical optimizations, Asos has adopted a policy of ‘radical transparency’ when it comes to consumer behavior.
The retailer now informs customers about their individual return rates. “One of the best things we’ve done is give power back to consumers,” Ramos said. “We say, ‘Dear consumer, this is your actual return rate. Now you see it.’ This transparency has been the most effective tool because they now feel responsible for their actions.”
Key takeaways for leaders:
Operational realignment:
Asos is making the transition from a high inventory and promotional model to a disciplined commercial strategy. The focus is on full-price sales and product sovereignty.
Non-transactional loyalty:
The ‘Asos World’ program prioritizes exclusive access and experiences over traditional discount mechanisms. This leads to increased consumption among top members without loss of margin.
Radical transparency:
Sharing individual returns data with customers has proven to be more effective in reducing return rates than punitive measures. It gives consumers responsibility for their shopping behavior.
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