The e-commerce market's "surefire formula" is changing. In the past, platforms focused on economies of scale by pushing lowest prices and volume, but now "ultra-personalized curation" that uses artificial intelligence (AI) and data to uncover customers' hidden tastes is emerging as a key competitive edge. The analysis is that only platforms that ease consumers' fatigue from too many choices in an age of product abundance can survive.
According to the industry on the 9th, major retail companies are accelerating a shift to a "shopping for discovery" model. Personalization methods are also evolving. Whereas traditional personalization relied on limited data such as age group or purchase history to recommend for similar customer segments, the recent trend is toward ultra-personalization that reflects customers' behavior, situations, and context. It goes beyond merely showing items chosen by similar consumers to proposing in real time the most suitable product for this specific customer right now.
Hyundai Department Store recently rolled out the premium e-commerce platform "The Hyundai Hi." The Hyundai Hi prioritizes lifestyle curation content on the main screen instead of discounts, special promotions, or ads. The idea is to guide customers to naturally discover their tastes through content.
What stands out is the use of both online and offline data. It integrates and analyzes purchase history from offline department store locations with online shopping data to identify preferences by customer.
For example, a customer who bought wine glasses offline might receive online recommendations for premium wines or appetizers suited to a particular occasion. It is effectively an evolution to a sophisticated curation stage that reads the consumer's "context," beyond simple product suggestions.
Hyundai Department Store said, "We plan to build a platform where customers discover and choose tastes through products and stories carefully selected by Hyundai Department Store, moving away from the existing e-commerce structure where customers must search and compare."
Lotte ON also recently revamped its app and website. It designed the first screen to be configured differently for each person by reflecting customers' shopping history and interest data.
It also introduced a conversational search service called "Fashion AI," which recognizes even detailed requests like "Recommend a wedding guest look" and "Find a flowy blouse." It is guiding users to naturally discover products by conversing with AI, moving away from rigid, keyword-centric search. It is guiding users to naturally discover products by conversing with AI, moving away from rigid, keyword-centric search.
AI is expanding beyond product recommendations into customer service (CS) and operations. Oasis Market, a powerhouse in fresh foods, recently began a transition in its operating system by introducing a customer service system based on the AI assistant "MAY."
When customers voice or type in an issue, MAY checks related products based on orders within the past three days and immediately guides them through next steps. If you call the customer center, you can be connected to the AI assistant service; you can simply speak naturally into your smartphone, saying things like "The eggs arrived broken." MAY checks in real time the items ordered within the past three days, first asks about damage or freshness issues, and processes them.
The reason the e-commerce industry is clinging to curation is that "price competition" has hit its limit. In the past, the goal was to find the desired product, but now there are so many products that making a choice itself has become difficult. An industry official said, "As cutthroat competition among platforms has pushed prices down to a similar level, a mere 10 won cheaper isn't enough to hold on to customer loyalty."
As a result, the industry sees data-driven curation capabilities as the key variable that determines success or failure. The aim is to create an emotional bond of "this platform knows my taste best" and to capture customers through the "lock-in effect."
Today's AI has evolved to process in real time complex time-series data beyond the fact that someone searched for "jeans," including weather, location, preferred brands, and cart patterns. An industry official said, "The current changes are not a mere fad but a structural transition from seller-centric efficiency to buyer-centric convenience," adding, "Going forward, how many items a platform holds will determine its survival."