The Door to New Forms of Search
Semantic search goes far beyond the text field. Once technology understands intent and context, entirely new ways of searching become possible. Chatbots and voice assistants let customers interact with a webshop as if having a conversation: “I need a gift for my mother—she loves baking. Do you have anything suitable?” Instead of a traditional results page, the customer can be guided step by step, just like a clerk in a physical store.
​
Semantic search is at the heart of Conversational Commerce, where the way we engage with AI tools like ChatGPT is shaping how we shop online. Search is evolving into dialogue, and this shift in consumer behavior is already underway.
​
Visual search is another area where semantic, AI-powered technology is making a big impact. Customers can snap a photo of a product they like, and the search engine finds similar items. Multimodal AI models, which understand both language and images, make this experience even richer. Users can now combine an image with a prompt, for example: “I want to decorate my living room in the style of this image—what products should I consider?”
​
This transforms the experience from a database lookup into one of discovery, inspiration, and guidance. Users are freed from guesswork, and being understood feels almost human. When AI also factors in preferences and context, inspiration, consideration, and purchase blend seamlessly, reshaping the user journey.
​
Amazon’s new Visual Search feature, Lens Live, shows how effective this can be. With image recognition improving rapidly in modern AI models, customers increasingly expect such functionality—either directly from large webshops or through integrated third-party platforms—so products can be discovered via visual search.
Final Thoughts: Search That Moves the Needle
When search works well, it shows in the numbers. Microsoft reports that companies switching to AI-powered search solutions have seen up to a 30% increase in conversions. Semantic search is therefore not just a UX improvement—it’s a direct investment in the KPIs that matter.
​
At the same time, semantic search helps future-proof ecommerce businesses. It prepares you for evolving consumer behaviors, AI-driven expectations, and AI agents increasingly handling parts of the customer journey. It also allows content to become intent-focused—not just describing what a product is, but what it does for the customer—aligning with the needs-based search preferred by both humans and AI. In the near future, AI-driven search may become central to discovery, while AI agents handle more practical tasks.
​
Yet the present cannot be ignored. Customers are still used to searching with keywords, categories, and filters, so a complete search solution must accommodate both traditional and semantic approaches. This requires structured, high-quality product data, enabling AI to understand context and meaning accurately. Without it, even the best AI falls short.
​
The complexity of your catalog also matters. For large, diverse assortments, semantic search delivers enormous value; for niche stores with a few dozen products, the ROI may be smaller. Strategic assessment is key.
​
At Vertica, we see no doubt: semantic search is here to stay. It allows customers to express themselves in their own words, style, and way of exploring. The search box transforms into a digital assistant that guides rather than blocks—turning curiosity into conversion, and ensuring customers choose you over the competition.
Adrian K. Larsen
UX & Business Strategy Consultant
The search bar may be small, but its impact is enormous. With 43% of customers heading straight to it, its role in driving business success is undeniable. In just a few seconds, search decides whether a customer feels understood—or walks away. And it’s often these searching customers who contribute significantly to revenue. That’s why search isn’t just about user experience—it’s about results. By leveraging semantic search and AI, it can transform from a static tool into a smart digital assistant that listens, guides, and fosters loyalty.
Imagine walking into a store on a gray Tuesday afternoon and asking the clerk, “Do you have a jacket that will keep me warm and dry in the rain?” He stares back blankly: “Sorry, we don’t have anything with the words ‘dry’ or ‘rainy.’” By the time you realize this, you’re already walking out the door.
​
Online, this frustrating experience is all too common when search doesn’t understand human intent. We search like humans, but machines often respond like literal word-matching robots.
​
And it’s costly. A full 43% of customers start their journey in the search box, and if they get empty or irrelevant results, the opportunity is lost before it even begins. Even more importantly, these searchers are among your most valuable customers—converting up to 50% better than average and contributing disproportionately to revenue.
​
That’s why search is more than just a UX feature—it’s a business-critical tool. With AI and semantic search, we can move beyond simple keyword matching. Search can start understanding context, intent, and nuance, transforming from a rigid tool into a smart assistant that truly listens, guides, and drives loyalty.
Beyond Keywords: Searching the Way We Speak
Traditional search relies on keywords: type the right word, get a result. But users rarely think in keywords—they think in needs: “shoes for winter,” “outfit for a summer wedding,” or “chair that fits a small kitchen table.” When a webshop can only match exact words in product descriptions, many users are left empty-handed.
​
Some platforms try to bridge this gap with synonym lists—“sneakers” matches “sports shoes” or “everyday shoes.” It helps, but language evolves constantly. New trends, slang, and expressions appear all the time, making it impossible to maintain a perfect list.
​
Semantic search tackles the problem differently. Powered by AI, it understands relationships, context, and the intent behind a search. It’s about grasping the meaning of words—semantics in action.
​
With semantic search, the system knows that “rain shoes” means waterproof footwear, and that “evening dress” is functionally equivalent to “party dress.” It also transforms discovery: users can search by mood or style, like “furniture that fits an old mansion” or “I love Italian food, what kitchen utensils should I have?” In short, users speak naturally, and the webshop still delivers precise, relevant results.