In e-commerce, the customer journey often begins with a simple action: the search. However, behind this apparent simplicity lies a technological complexity that can define the success or failure of a sale. Traditional search, based solely on keywords, often fails to understand the consumer's true intent. This is where AI in search and recommendation emerges as a true revolution , transforming a functional tool into an intelligent shopping assistant.
VTEX , as one of the leading platforms in the market, is at the forefront of this transformation. Based on insights presented at VTEX Day , we will explore how the application of semantic search and personalized recommendations with AI not only improves the user experience but also generates massive gains in conversion and revenue for merchants.
THE PROBLEM WITH TRADITIONAL SEARCH: THE KEYWORD BARRIER
Think of traditional search as an extremely literal librarian. If you ask for a book about " fast automobiles ," it will only show you works that contain exactly those words in the title. Consequently, books about " sports cars " or " high-performance automobiles ," which are what you're really looking for, would be ignored. This is the main limitation of keyword search.
This model depends on a manual and exhaustive registration of synonyms and faces difficulties in interpreting natural language or contextual searches.
For example, a customer searching for " winter clothing " isn't typing keywords, but rather describing a need. A traditional search would have difficulty connecting that need to products like " coat ," " hat, " or " scarf " if those terms aren't perfectly matched.
VTEX'S SOLUTION: SEMANTIC SEARCH AND THE MAGIC OF EMBEDDINGS
To overcome this barrier, VTEX is implementing semantic search, a technology that uses large language models (LLMs) and embeddings to understand the meaning behind words, not just the words themselves.
It works like this: the AI pre-processes your entire product catalog and creates a " map of meanings ".
Therefore, when a customer searches for " running shoes ," the system understands the semantic relationship with " sports sneakers " and can display both results, even if the words are not identical.
The practical results of this technology are impressive. In a real-world case study, Fast Shop , by adopting semantic search, saw its conversion rate triple and its click-through rate (CTR) double. This demonstrates the direct impact of a search that truly understands what the customer wants.
GOING BEYOND SEARCH: RECOMMENDATIONS THAT SELL
Personalization, however, doesn't stop at the search box. The same artificial intelligence is used to create recommendation displays that adapt in real time to each user's behavior.
In partnership with the Synerise platform , VTEX captures all events in the customer journey (product views, items added to cart, completed purchases) to feed its AI models. Based on this data, the system predicts the consumer's next step and displays personalized storefronts.
The most common strategies include:
- Similar products: If the customer is viewing a product, the display window suggests similar items, from other brands or with other characteristics.
- Cross-sell: recommends complementary products. In the case of I Love Beauty, when viewing a hair oil, the system suggests shampoo and repair mask, encouraging the purchase of more items.
- Up-sell: offers a superior or more complete version of the product the customer is interested in.
The results of this approach are equally impressive, with customers impacted by the recommendations becoming twice as frequent and the average order value increasing by up to 20%.
CONCLUSION: A MEANINGFUL BUYING JOURNEY
The application of AI in search and recommendation by VTEX represents a qualitative leap in how online stores interact with their customers. After all, we've moved from a reactive, keyword-dependent model to a proactive and intelligent system that understands intent and anticipates needs. By delivering more relevant results and personalized recommendations, the technology not only optimizes metrics such as conversion and average order value, but, above all, creates smoother, more intuitive, and truly meaningful shopping journeys for the consumer.
Want to learn more about how Artificial Intelligence can revolutionize your e-commerce performance? Keep exploring the content on the e-Plus blog and discover the trends shaping the future of retail.
