Ebook

From Search to Intent Box:
The Future of Ecommerce Product Discovery

The search box has long been the backbone of ecommerce sites, a familiar tool where customers type keywords, hoping to find the right product. But today’s shoppers expect more.

Their behavior is changing, they are starting to search the way they talk, using natural language and asking full questions like, “What are the best shoes for marathon training?” instead of typing “running shoes men.”

Visitors may come in with a simple goal such as a list of products. But more often, they expect expert guidance that’s conversational. They want to know what’s right for them, why it fits their needs, and how it compares to other options. And they expect that clarity instantly.

Yet many search experiences remain primitive, failing to understand intent. They still rely on outdated keyword matching, returning generic results that force shoppers to scroll, refine, or abandon the journey entirely when they can’t find what they need.

This is where the evolution from a search box to an intent box changes everything. Powered by AI and GenAI, the intent box interprets user needs, understands context, and delivers precise, relevant answers and product suggestions in real time.

By combining machine learning, vector search, and generative AI, it seamlessly guides shoppers through discovery, decision-making, and
purchase.

In this ebook, we explore:

  • Why traditional ecommerce search falls short — and what today’s shoppers really expect from product discovery
  • How the evolution from search box to intent box is reshaping online buying with helpful, expert, generative guidance.
  • What makes Coveo’s intent box different: grounded in your product catalog and content, it delivers relevant answers you can trustIt’s time to think outside the search box and create an experience that makes your brand the first — and only — choice for your customers.
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Think outside the
search box

Why Traditional Search Fails Today’s Shoppers

Search is ubiquitous. It’s the default discovery tool for ecommerce sites. Whether shoppers are browsing, researching, or ready to buy, they instinctively turn to the search box. It’s always there, always accessible, and unlike passive browsing or clicking through filters, the only place where customers explicitly state what they want. 

But traditional search makes shoppers work for it, forcing them to think in rigid keywords rather than the natural way they’d ask a question to a sales associate when shopping in-store.

The problem? Shoppers don’t think in keywords, they think in needs. Increasingly, they expect to search the way they naturally speak, without having to translate their thoughts into simplified terms. A customer searching for the best laptop for graphic design under $2,000 doesn’t want a generic list of laptops; they need a tailored list of options and expert guidance on their specific use case and a clear path to the right product.

43%

of website visitors with a specific goal start by using the search bar.

72%

of shoppers abandon an ecommerce site when they can’t find what they need quickly.

Source: 2025 Commerce Relevance Report

The real revenue opportunity isn’t in generic searches but in the complex, high-intent queries that signal serious purchase intent and can best serve the customer in the moment. If search fails to interpret them, businesses lose out on ready-to-buy customers and miss the chance to build lasting relationships. Instead of guessing at keywords, the search box needs to evolve into an intent box. One that not only understands queries in natural language but the intent behind them.

That’s why the search box needs to evolve into something more intelligent, more adaptive, and more context-aware: the intent box.

Different Queries. Different Needs. One Intent Box.

Every query reveals something different: a goal, a challenge, or a desire for guidance. But most search engines still treat every query the same. The intent box doesn’t. It adapts in real time, tailoring the experience based on query type, complexity, and context.

The best response? A curated list of products basedon catalog data and semantic understanding ofhow “small,” “modern,” and “light-colored” mapto product attributes.

This calls for expert advice — articles, buyer guides,or product descriptions powered by GenAI thatsummarize the best options and even surfacerelevant categories based on the semantic intentof the answer.

This isn’t a product search — it’s a support query.The ideal response is a precise, contextual answerpulled from policy documents, powered by GenAI,with direct links to the supporting resources.

These types of queries highlight the need for a search experience that goes beyond basic keyword matching. One that adapts to intent, context, and the appropriate response, whether it’s a product list, educational content, or policy information.

Here’s how different types of queries map to growing complexity — and how the intent box enables shopper success at every level:

Complexity & ambiguity

Very Low
Very High
Query
Bosch 500 series dishwasher stainless steel
Query Type
Specific product
Challenge
User wants a specific product that fits certain pre-defined attributes; ‘stainless steel’, ‘Bosch 500 series’
How the Intent Box Responds
Returns a relevant list of products, with top-ranked results that most precisely match the query intent.
Query
Shoes
Query Type
Broad/Navigational
Challenge
User is overwhelmed with too many products.
How the Intent Box Responds
Surfaces categories and high-performing subcategories with relevant filters
Query
What is the best flooring for a basement?
Query Type
Exploratory/Educational
Challenge
User is unsure of what they want and need advice.
How the Intent Box Responds
Generates expert advice to guide shoppers on key selection criteria — alongside curated category recommendations.
Query
What is your return policy on swimwear?
Query Type
Pre-purchase Informational/Consideration
Challenge
User wants to clarify information to help with a purchase decision that may not be available on the product detail page.
How the Intent Box Responds
Generates an answer backed by supporting content (return policy, articles, guides etc.) with links to relevant sources.
Query
Earbuds won’t sync to my iPhone
Query Type
Contextual/Problem-Solving
Challenge
User has a post-purchase support question that requires some technical understanding.
How the Intent Box Responds
Generates an expert-backed answer with steps to troubleshoot and solve the issue, alongside citations, links to videos, or other relevant support materials.

Say Hello to the Intent Box

An intent box is the intelligent brain behind ecommerce discovery. It understands nuance in queries and surfaces products, comparisons, guidance, and support answers dynamically, pulling from multiple sources such as product catalogs, buying guides and expert content to deliver relevant products, guidance, advice and/or answers, ensuring shoppers find exactly what they need.


This shift powers what some might label conversational commerce or what we refer to as generative product discovery, where search doesn’t just retrieve — it guides, recommends, and refines.

Instead of forcing shoppers to adjust their queries repeatedly, the intent box interprets needs, filters results intelligently, and delivers meaningful answers. It makes search feel more intuitive, accurate, and relevant.

The Anatomy of the intent Box

This a graph explaining the anotomy of intent box

Example Spotlight: Finding the Perfect Sofa

A shopper searching for what type of sofa they should be considering for a small living space doesn’t want to see random sofa listings, be redirected to a chatbot, or have to rephrase their query multiple times to get the right results. They expect search to understand their intent and deliver relevant recommendations instantly.

An intent box should be able to dynamically surface:

  • Expert advice on key considerations, configuration, materials, and space-saving features like sleeper sectionals or storage chaise
  • Category recommendations optimized for small-space living
  • Suggested product options that match space constraints and style preferences
  • Featured products relevant to the intent of the generated answer
  • Expert-rich content such as articles, blogs or guides that can offer more in-depth guidance
  • Next best questions that help the shopper refine or expand their discovery journey

What the Intent Box Gets Right That Chatbots Don’t

62%
of shoppers are more likely to buy when supported by GenAI-driven guidance.
Source: 2025 Commerce Relevance Report

For years, brands have turned to chatbots and virtual assistants to make ecommerce feel more interactive. But generative product discovery is something else entirely.


Chatbots typically follow rigid scripts, often creating frustrating, disconnected experiences. Shoppers don’t want forced conversations — they want quick, relevant answers.

Shopping assistants usually can’t handle complex or vague queries, and they’re limited to the product catalog.

That’s the difference: chatbots interrupt, assistants have limits, but the intent box listens and responds in real-time — with full context.

Instead of frustrating shoppers, the intent box delivers seamless, relevant guidance that connects education, discovery, and support, in a single interaction point. It’s efficient, intuitive, and personalized.

And the impact is clear: 62% of shoppers are more likely to buy when supported by GenAI-powered guidance. The intent box doesn’t force interaction — it enables the right one.

Where Chatbots Fail
Where Virtual Shopping Assistants Fail
Why the Intent Box Wins
Rely on scripted, rigid dialogs, struggling with nuance, leading to dead ends or loops.
Limited scope, can’t handle complex queries or go beyond basic assistance.
Interprets shopper intent, whether they’re researching, buying, or troubleshooting and generates natural, conversational answers that match where they are in the journey.
Operate in silos, disconnected from search, product, and support content.
Lack personalization, provide generic responses and is not tailored to an individual’s behavior or real-time data
Delivers accurate, contextual responses, pulling from product catalogs, expert content, support articles, etc, ensuring answers are grounded in trusted sources.
Struggle with complex queries, often asking customers to rephrase or clarify.
Too many steps, forcing customers through unnecessary interactions to get answers.
Combines advice and product guidance, goes beyond just answering and recommends relevant categories or products
Disrupt the buying journey, forcing unnecessary back and forth.
Interrupt the flow, rather than guiding shoppers naturally within their discovery journey.
Facilitates discovery and supports the shopper, without disrupting the flow of their journey.
Lack transparency, do not explain how an answer is being generated, nor do they use data to improve over time.
Personalizes responses tailored to each journey using real-time behavioral signals
Feels intuitive,not intrusive, acts like an expert sales associate, not a robotic script.

The Power of Intent-Driven Search in Ecommerce

For ecommerce leaders, the impact is clear: An intent-driven, relevant search experience leads to higher conversions, bigger orders, and stronger customer relationships — driving real revenue growth.


An intent box elevates your site into a premium destination where shoppers can learn, explore, and buy with confidence.

By delivering intuitive, expert-level guidance at scale, it creates a seamless experience that builds brand loyalty and keeps customers coming back.

Cart Add
Higher Conversions
Dollar Bill
Increased AOV
Turning Search into Sales

Shoppers who use search already know what they want — they just need the fastest path to it. An intent box with AI search, interprets queries accurately, providing tailored and relevant results that reduce bounce rates and maximize conversions.

Relevant Recommendations, Bigger Basket

An intent box dynamically suggests contextually rich recommendations grounded in answers to queries, driving higher order values.

Full-Screen
Scalability
Target Miss
Brand Loyalty
The Virtual Sales Associate That Never Sleeps

Scaling personalized interactions is difficult — but the intent box acts as an always-on digital shopping assistant. It guides decision-making, adapts to individual needs, and provides expertise at scale without increasing customer support costs.

Become the Expert Advisor, Win Repeat Visits

An intent box delivers expert-level answers and tailored recommendations in the moment, positioning your brand as the go-to trusted source for reliable guidance — not just transactions. Customers remember when a brand makes their experience effortless — and they come back

Turning search intent
into business impact

Coveo’s Approach: Generative Product Discovery – Blending GenAI & Product Discovery

For ecommerce leaders, the impact is clear: An intent-driven, relevant search experience leads to higher conversions, bigger orders, and stronger customer relationships — driving real revenue growth.

At the heart of this transformation is a powerful GenAI solution that enhances enterprise search by providing context-aware, permission-secured answers to complex natural language queries. Using a combination of machine learning, vector search, and GenAI, Coveo can generate highly relevant, well-grounded responses — ensuring shoppers get the right product, information, or advice effortlessly.

Seamlessly integrated into Coveo-powered search interfaces, Coveo’s generative product discovery supports both simple and complex queries, delivering AI-optimized search results and generated answers from a single, unified search experience.

A Four-Stage Approach for Maximum Relevance

Coveo’s unique approach to Retrieval-Augmented Generation (RAG) retrieves only the most relevant content using a four-step process:

  1. Identifying Relevant Documents

    Coveo applies machine learning and semantic encoding to retrieve the most relevant content from an enterprise’s indexed rich content while respecting security and permissions. This ensures that only trusted, high-quality sources are used to generate answers.

  2. Extracting the Most Relevant Content
    From the selected documents, Coveo pinpoints the most contextually relevant text chunks using vector embeddings. These text segments are chosen based on their semantic similarity to the user’s query, ensuring accurate, meaningful responses.
  3. Answer Generation with AI & Controlled Content

    Coveo builds a structured prompt that includes both the user’s question and the extracted content. This is sent to a large language model (LLM), which generates an answer based only on this verified data — avoiding hallucinations. The final response appears alongside traditional search results with clear citations and filtering options.

  4. Product & Category Matching

    Coveo extends the generative experience beyond just content. The same understanding used to answer the user’s question is also used to retrieve highly relevant product listings and category suggestions. Whether a shopper is asking about features, comparisons, or best options, Coveo generative product discovery improves engagement, conversions, and customer loyalty.

From First Click to First Choice

Search is no longer just a box — it’s an intent engine and a loyalty driver. When buyers consistently find exactly what they need, they come back, again and again.


Start evolving your product discovery experiences by focusing on these three goals:

  1. Decoding shopper intent
    Move beyond keyword matching to interpret intent dynamically, surfacing the most relevant products, content, and recommendations seamlessly.

  2. Delivering credible guidance
    Create generative discovery experiences that position you as a trusted advisor, providing expert answers and personalized insights that help shoppers make confident decisions.

  3. Streamlining the path to purchase
    Intelligently suggest product categories or items that align with the generated advice — ensuring contextual awareness and seamlessly driving engagement and conversion
The future of ecommerce belongs to brands that understand and anticipate shopper needs, before they even have to ask.
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