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Retail AI

Same query, different intent: The revenue risk of irrelevant search results

By Advanced AI EditorJune 9, 2025No Comments4 Mins Read
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What happens when two different customers type the same phrase into an ecommerce search box?

One might be a first-time visitor searching broadly. Another might be a returning buyer, already familiar with your brand and products. Yet, in most ecommerce experiences, despite their different needs, experiences, and intent, they’re met with the same product grid. No nuance. No recognition of who they are or what they’re really looking for.

That’s the problem with traditional ecommerce search, based on keyword matching. It treats everyone the same with a cascade of irrelevant listings, even when their goals couldn’t be more different.

This gap between shopper expectations and outdated search experiences is costing retailers. In Coveo’s 2025 Commerce Relevance Report, 72% of shoppers said they’ll abandon a site if search results aren’t relevant. Think about that: Nearly three out of four shoppers will walk away — not just from a product, but from an entire brand, simply because search couldn’t understand what they needed.

One-Size-Fits-All Search Doesn’t Scale, But Expectations Do

Search has long been the cornerstone of ecommerce, but traditional search isn’t built to handle the nuance of today’s buyer behavior. It’s rigid, rules-based, and blind to context. Shoppers are increasingly using full, natural queries like:

“Best sofa for a small apartment with pets”
“Waterproof jackets under $100 for hiking”
“Are these boots true to size?”

They’re not just looking for products. They’re looking for guidance, clarity, and fast, relevant answers that give them confidence to make purchase decisions. Unfortunately, most search engines can’t parse context, complexity, or intent, leaving shoppers to fend for themselves.

This is where traditional search fails — and where the intent box begins.

What Is an Intent Box?

The next evolution of ecommerce discovery, the intent box is a single, intelligent interface built directly into the shopping experience. Unlike virtual assistants or chatbots, it isn’t siloed from search or content, limited by scripts, or disruptive to the journey. It interprets natural language, adapts in real time to each shopper, and responds with the most relevant next step—whether that’s a product recommendation, expert advice, or a clear answer to a pre-purchase question.

If traditional search is about matching keywords, the intent box is about understanding people.

Instead of matching keywords, the intent box interprets meaning. It understands natural language, draws on behavioral signals and history, and responds with the most relevant next step — whether that’s a product or category recommendation or expert advice. It works quietly within the flow of the shopping experience, avoiding disruptions, redirects, or repetitive dead ends.

How it Works — and Why It Drives Revenue

The intent box combines AI search, vector-based retrieval, and GenAI to guide shoppers through discovery in real time. By blending structured product data with unstructured content, it interprets natural language, adapts to behavior, and surfaces the most relevant results. It delivers:

Natural language understanding to decode complex, multi-step queries
Generative answers grounded in trusted content and catalog data
Personalized recommendations based on real-time behavioral signals
Seamless integration into the shopper shopper without silos or scripts

This makes the discovery experience not just more relevant, but more profitable. Shoppers who feel understood are more likely to convert, spend more, and return. In fact, Coveo’s Relevance Report found that 69% of shoppers expect GenAI experiences to change how they shop online and that 62% of shoppers are more likely to purchase when supported by GenAI-powered guidance. That’s a meaningful shift in behavior with clear revenue impact.

Search That Understands Intent Delivers Revenue That Lasts

Search is often the first interaction between your brand and a customer and with every click, search, and bounce, your shoppers are telling you what they want. In a world where every shopper is different, serving the same results to everyone isn’t just outdated — it’s a revenue risk.

To evolve discovery experiences, ecommerce leaders should focus on three core goals:

Decoding intent: Move beyond keyword matching to interpret real meaning and surface the right results.
Delivering guidance: Use AI to act as a trusted advisor, not just a product filter.
Streamlining the journey: Recommend the next best product, category, or answer, without forcing the shopper to start over.

If your site search isn’t working for every shopper, it’s working against your bottom line. When it succeeds, it becomes a driver of loyalty, conversion, and long-term growth.

Coveo’s intent box helps you treat every customer like they matter — delivering relevant results, richer answers, and more profitable journeys.

Explore Coveo for Commerce.



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