Why discovery is moving from keywords to conversations

For two decades, winning the first page of Google was the primary strategy for product discovery. Brands invested millions in keyword research, backlink campaigns, and content optimization to earn clicks from the search results page. Now, that playbook is being rewritten.

The rise of AI-driven answer optimization represents a fundamental shift in how consumers find and evaluate products. When shoppers ask ChatGPT for the best running shoes for flat feet or query Perplexity about sustainable skincare brands, they're bypassing traditional search entirely. They're getting direct answers, curated recommendations, and increasingly the ability to buy without ever seeing a search results page.

For commerce brands, this shift carries profound implications. The customer journey no longer begins with a Google search. It begins with a conversation.

The data behind the discovery shift

The numbers reveal how quickly consumer behavior is changing. ChatGPT's weekly active users surged from 300 million in December 2024 to 800 million by October 2025. That represents a 2.6x increase in less than a year. According to McKinsey research, 44% of AI-powered search users now consider AI their primary source of insight, compared to 31% who still rely most on traditional search.

The impact on traditional SEO metrics has been stark. Google AI Overviews now appear in approximately 30% of all searches. For sites that previously ranked first for their target keywords, the average click-through rate dropped from 0.73 to 0.26 after AI Overviews rolled out. That's a 64% reduction in clicks.

Nearly 60% of Google searches now end without a single click. Users get their answers directly and move on. Gartner predicts that by 2026, traditional search engine volume will drop 25% due to AI chatbots and virtual agents.

What does this mean for commerce? Adobe Analytics observed a 693% surge in AI-driven ecommerce traffic for the 2025 holiday season compared to 2024. Though still a fraction of total traffic, AI-driven discovery is growing rapidly as more consumers embrace conversational shopping.

What Answer Engine Optimization actually means

Answer Engine Optimization is the practice of structuring content so AI platforms can discover, understand, and cite it when generating responses. Unlike traditional SEO, which focused on ranking in lists of blue links, AAO prioritizes being the source that AI systems reference when delivering direct answers.

This creates both challenge and opportunity for commerce brands. Companies that optimized solely for link-based rankings risk becoming invisible in AI-generated answers, even if their traditional search visibility remains strong. But brands that invest in structured, authoritative, answer-ready content can capture attention at the precise moment when purchase intent is highest.

The shift also changes how success gets measured. Traditional traffic metrics no longer tell the full story. You can have declining organic traffic while simultaneously increasing brand visibility and influence in your target market.

When an AI assistant recommends your product to users researching solutions, those impressions influence future purchase decisions even if users don't click through immediately.

Conversational commerce changes everything

The transformation extends beyond discovery into the transaction itself. Shopify's announcement of Agentic Storefronts signals how quickly the infrastructure for AI-native commerce is being built.

This represents a fundamental shift in how the purchase funnel operates. The Shopify and OpenAI partnership enables in-chat checkout directly within ChatGPT, demonstrating that AI can now own the entire journey from discovery to purchase. A shopper can ask for gift recommendations, receive curated options, compare features, and complete the transaction without ever leaving the conversation.

The customer experience implications are significant. Rather than navigating search results, filtering product pages, reading reviews, and managing a checkout flow, the entire process collapses into natural dialogue. The AI remembers preferences from previous conversations, understands context, and can make personalized recommendations that feel genuinely helpful rather than algorithmically generated.

Retailers are responding. Perplexity, for example, introduced one-click buying features. Every major AI platform is racing to become a commerce destination.

Why customer experience is the new competitive moat

In a world where AI mediates discovery, the quality of your customer experience becomes the primary differentiator. Traditional SEO allowed brands to compete through technical optimization and content volume. AI answer engines care about something different. They care about authority, consistency, and the quality of information available about your brand.

This is where the connection between AI discovery and customer service becomes critical. AI systems pull from multiple sources when generating recommendations.

They reference product information, review sentiment, support documentation, and the quality of customer interactions with your brand. A company known for exceptional service creates the kind of authoritative, trustworthy content that AI systems prefer to cite.

The feedback loop works in both directions. Purpose-built support experiences that resolve issues quickly and personalize interactions generate the positive signals that improve visibility in AI discovery. Poor support experiences create negative sentiment that AI systems will surface when shoppers ask for recommendations.

Consider what happens when a potential customer asks an AI assistant about your brand. The AI doesn't just pull product specifications. It synthesizes information about return policies, customer satisfaction, support quality, and brand reputation. Every touchpoint in your customer experience feeds the intelligence that determines whether AI systems recommend your products or steer shoppers toward competitors.

The operational shift required

Adapting to this new reality requires changes across multiple functions. Content teams need to move beyond keyword optimization toward creating authoritative, answer-ready content that AI can easily parse and cite. Marketing needs to think about brand visibility across AI platforms as a primary channel, not an afterthought. Customer service becomes a strategic function that directly impacts discoverability.

The most successful brands will integrate these functions rather than treating them as separate silos. The same knowledge base that powers your customer support AI should inform the structured data that gets syndicated to AI discovery platforms. The voice and accuracy of your brand agents should match the personality customers experience in support interactions.

This integration creates compounding advantages. Consistent, high-quality information across touchpoints builds the entity authority that AI systems favor. Clear, helpful responses in support conversations generate positive sentiment that improves brand perception. Every interaction becomes both a service moment and a discovery opportunity.

The technology infrastructure matters too. Platforms that unify customer data, support interactions, and product information enable the kind of seamless experiences that AI discovery rewards. Legacy systems that fragment customer context and force repetitive interactions create friction that shows up in AI-generated brand assessments.

Practical steps for commerce leaders

Start by auditing how your brand currently appears in AI responses. Ask ChatGPT, Perplexity, and Google's AI Overviews about your products and category. Note which competitors get recommended and what information sources get cited. This baseline reveals gaps in your AI visibility strategy.

Ensure your product data is structured and accurate across all platforms. AI systems rely on clean, consistent information to make accurate recommendations. Inaccurate inventory, outdated pricing, or incomplete product descriptions can result in your products being excluded from AI-generated shopping lists entirely.

Invest in authoritative content that directly answers the questions your customers ask. Move beyond generic category pages toward comprehensive guides that address specific use cases, comparisons, and decision criteria. AI systems favor content that provides complete, helpful answers to real questions.

Connect your support operations to your discovery strategy. The information in your knowledge base, the quality of your chatbot interactions, and the satisfaction of customers who contact support all influence how AI systems perceive your brand. Treat every support interaction as an opportunity to build the kind of reputation that AI discovery rewards.

Monitor AI citation metrics alongside traditional search performance. Track whether your brand is being mentioned in AI responses, which sources are being cited, and how your visibility compares to competitors. These metrics will become as important as organic search rankings over the coming years.

The conversation has started

The shift from search to AI-powered discovery isn't coming. It's already here. Every week, hundreds of millions of potential customers are forming opinions about products through conversations with AI assistants. They're making purchase decisions based on AI recommendations. And increasingly, they're completing transactions without ever visiting a traditional website.

The old rules of optimizing for search rankings aren't irrelevant. They’re simply incomplete. The new reality requires thinking about every customer touchpoint as both a service moment and a discovery opportunity. It requires building the kind of brand authority that AI systems trust and cite.

The conversation about your products is happening whether you participate or not. The question is whether your brand will be part of that conversation.