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Beyond the search bar

Jake Holmquist
Field CTO Google Cloud

september 10, 2025

Why retailers are turning to conversational commerce to create truly personalized and interactive shopping experiences

Retailers are losing revenue and customer loyalty because traditional keyword search fails to deliver the personalization shoppers now expect. Google’s Conversational Commerce agent in Vertex AI Search for Commerce addresses this gap by replacing the static search bar with an interactive, AI-powered dialogue. From understanding customer intent and surfacing relevant products and recommendations, this enables retailers to boost conversion rates, reduce cart abandonment and keep up with the expectations of their most demanding customers. 

An animated gif showing a conversational commerce experience. A user ask what gift to buy their niece. The conversational agent responds with some gift ideas, 3 products, and some other searches for the user to try. The interaction ends with the user selecting a product and adding to cart.

The conversation begins

The interaction above is more than just a chatbot. It’s a glimpse into the future of retail. A customer arrives not with a specific product in mind, but with a need: a birthday gift for their niece. 

From monologue to dialogue

For years, the primary challenge in e-commerce was moving beyond simple keyword matching. Vertex AI Search for Commerce transformed how customers find products by introducing deep Natural Language Understanding (NLU), allowing retailers to finally comprehend the intent behind long-tail, complex queries. The search bar got smart. 

This is the leap forward offered by Conversational Commerce. It builds upon a strong foundation of NLU to create a true dialogue. It's the next iteration of this transformation, designed not only to understand a customer's initial request but to engage them in an interactive conversation of refinement and suggestion. 

The high cost of a silent storefront

The gap between customer expectations and the reality of most online experiences is widening. A 2021 McKinsey study found that 75% of consumers want brands to make it easy for them to navigate their online experience, and 67% expect relevant product recommendations. 

The cost of failing to meet these expectations is staggering. According to Google research, only 1 in 10 consumers report finding exactly what they're looking for with legacy keyword search. This friction has severe consequences: 94% of U.S. consumers have abandoned a shopping session due to irrelevant results, and 85% of consumers view a brand differently after just one unsuccessful search. 

From theory to tactical: Real-world use cases

Conversational Commerce isn't a futuristic concept. It's a practical tool that drives tangible business outcomes today. Consider these use cases: 

  • AI concierge: For high-consideration purchases like furniture or fashion, an agent can guide a customer through a query like, "Help me update my wardrobe for my new job," asking about dress codes and style preferences to find the perfect look. 
  • The expert product advisor: For complex domains like electronics or auto parts, an agent can answer, "What's a good jacket for hiking in a rainy climate?" and recommend products based on technical attributes like waterproofing and breathability. 
  • The "recipe-to-cart" assistant: For grocery and consumer packaged goods (CPG), a customer can simply say, "I need the ingredients for lasagna," and the AI can populate their cart with the necessary items, perhaps even asking if they prefer a certain brand of sauce. 

Deconstructing the conversation: The agent in action

Screenshot showing a typical conversational commerce interaction. The 4 main components are explained in the paragraph below

The Google Cloud advantage: An AI-first architecture

  • Built on a decade of search DNA: Vertex AI Search for Commerce is built from the ground up, leveraging Google's largest shopping datasets, knowledge graphs and over a decade's worth of user query and click-through data. Valtech’s customers seamlessly inherit Google's deep understanding of how users search, interact with and purchase products. 
  • A fully-managed, revenue-optimized engine: This is not a single model but an AI system powered by an ensemble of over 14 AI models (including four vector models). It is highly tuned for commerce with specific adaptations for catalog augmentation using Vision AI and AI-driven relevance and ranking designed to maximize revenue, not just match keywords. 
  • A new philosophy: "Trust the AI": We encourage enterprises to move away from the old model of endless manual rules. Start with the AI, which learns from real-time performance data and then add business rules and optimization controls as needed, not as a first resort. This reduces manual effort and allows the system to scale. 
  • Constant innovation: The platform benefits from continuous innovation in Google Search and AI, including foundational upgrades to our large language models (LLMs) for relevance and revenue grading. 

Want to learn more?

The evolution of e-commerce is moving from a product-finding utility to a customer-centric service. The most impactful AI goes beyond just thinking to act and interact. The technology to build a truly interactive, intelligent storefront is here. The future of commerce isn't just personalized. It's conversational. 

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