Users arriving from AI platforms have already been filtered and nurtured through the consideration phase. They land on your site with high intent, leading to conversion rate increases of 2-5x for B2C and as high as 20x for B2B, far surpassing the performance of typical paid or organic search traffic.
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Anticipating a shift to "agentic commerce," SharkNinja is actively re-optimizing its e-commerce site for Large Language Models. The company believes what drives human conversion today may not rank highest in AI-driven search and expects commerce via AI platforms to be meaningful by Christmas 2025.
Following SEO, App Store Optimization, and social virality, the next major distribution channel is AI answer engines. Product teams must now strategize how to get their brand, features, and knowledge base indexed and surfaced in AI responses, making AEO a critical growth lever for the modern era.
AI search is the new overpowered marketing channel, with traffic converting up to 17x higher than Google. To get featured, invest heavily in comprehensive "alternatives to [competitor]" and "[your product] vs [competitor]" pages, as these are the bottom-funnel queries AI models cite most often.
Traditional SEO often involves technical debates (e.g., subdomains vs. folders) and link building. In contrast, optimizing for AI search (AIO) is about teaching the LLM about your product's value, features, and benefits, much like training a salesperson. It requires strong product marketing skills over technical SEO expertise.
The speaker's firm saw a 50% traffic drop after Google's AI Overview launch, yet leads from tools like ChatGPT grew 500%. This suggests that while AI-driven search reduces overall traffic volume, the visitors it does send have higher purchase intent and are better qualified.
As AI devalues simple clicks, marketing focus must shift to building a strong brand that algorithms recognize as authoritative. High-quality, well-structured owned content (like blogs and reports) becomes more critical for discoverability than traditional performance marketing tactics.
Unlike Google, which primarily handles discovery, AI models engage users in a Q&A process that guides them through consideration. This means when a user clicks through from an AI search, they are highly qualified and ready to convert, explaining the significantly higher conversion rates seen from this traffic source.
Traffic driven by answer engines is significantly more qualified. Webflow observed a 600% higher conversion rate from LLM referrals compared to traditional search. This is likely because users have higher intent after a detailed conversational query process, making AEO a highly valuable channel.
With 80-90% of AI-powered searches resulting in no clicks, traditional SEO is dying. The new key metric is "share of voice"—how often your brand is cited in AI-generated answers. This requires a fundamental strategy shift to Answer Engine Optimization (AEO), focusing on becoming an authoritative source for LLMs rather than just driving website traffic.
The rise of AI agents means website traffic will increasingly be non-human. B2B marketers must rethink their playbooks to optimize for how AI models interpret and surface their content, a practice emerging as "AI Engine Optimization" (AEO), as agents become the primary researchers.
