Hawaii Digital Agency Plate Lunch Collective reports users now input detailed queries to AI platforms, and businesses must optimize for “super intent.”
HONOLULU, HI, UNITED STATES, January 6, 2026 /EINPresswire.com/ — In 2025, the data showed a fundamental shift in how people seek information online. According to Similarweb’s 2025 analysis of user search behavior, informational query length on AI platforms averaged 31.2 words, a 900% increase compared to the 3.4-word average on traditional search engines. Plate Lunch Collective, an AI-native digital marketing agency in Hawaii, reports this pattern defines 2026 as the year businesses must restructure content: not for keyword matching, but for how AI systems across all platforms actually retrieve and synthesize answers.
“The numbers from 2025 were a revealing lead indicator,” said Hayden Bond, Founder and Chief Strategist at Plate Lunch Collective. “Whether someone uses ChatGPT, Google’s AI Mode, or Gemini, they’re providing dramatically more context than they ever typed into traditional search: constraints, preferences, specific situations. That’s a 900% increase in the information they’re sharing about what they actually want.”
The shift changes how content gets discovered in AI-assisted search. When AI systems like ChatGPT, Google’s Gemini, and AI Overviews receive a detailed query, they search multiple sources for content addressing the user’s specific context. Keyword-based optimization focused on short phrases that recalled ranked documents or web pages. Plate Lunch Collective works with and advises businesses on how to structure content so AI systems can extract and cite relevant answers when users describe their actual situations.
“We’re seeing this pattern across our entire client base: from airline staffing agencies in the Pacific Rim to luxury resorts in the Caribbean, from transportation providers in Costa Rica to hospitality operations in Canada,” Bond explained. “A Costa Rican resort doesn’t just optimize for ‘luxury accommodation’ anymore. Potential guests describe complete scenarios to AI: ‘What Costa Rican resorts have ocean-view suites under $400, offer both zip-lining and surfing, accommodate families with teenagers, and include transportation from Liberia airport?’ AI platforms, including Google’s own AI features, search for content that addresses those specific constraints together, then synthesize an answer citing the most relevant sources.”
This pattern, what Bond calls “super intent,” requires businesses to address the specific combinations of needs users actually describe, not just individual keywords. A business optimized for generic terms won’t surface when AI platforms search for content covering multiple specific constraints simultaneously. Industry data shows that AI-referred traffic, while smaller in volume, converts at significantly higher rates, with visitors spending 68% more time on websites than those from traditional organic search.
The implication for digital visibility extends across all AI-assisted search interfaces: ChatGPT, Google’s Gemini and AI Mode, Perplexity, voice assistants, and browser agents. Plate Lunch Collective’s approach focuses on structuring content around the scenarios and constraint combinations users actually describe in detailed queries. Plate Lunch Collective works with businesses to optimize their entire digital presence for AI retrieval, from semantic structure and schema implementation to intent-driven content strategies that address the specific scenarios users actually describe.
“2025 showed us the pattern in the data,” Bond said. “Users provide 900% more context to AI-assisted search than they ever gave traditional search. AI systems, including Google’s own, retrieve content based on how well it addresses that full context. In 2026 visibility will depend on how well businesses structure their entire digital presence to answer detailed questions people are asking across all these platforms.”
Key Questions About the Shift to AI-Assisted Search
What is “super intent”?
“Super intent” refers to the detailed, multi-faceted queries users submit to AI assistants, which combine multiple constraints like location, budget, and specific features. This contrasts with traditional, short keyword searches.
How does optimizing for AI search differ from keyword-focused approaches?
AI systems match content to the full context of a user’s query. Content optimized for generic terms like “luxury resort” won’t surface when users specify constraints on price, amenities, and location. Effective optimization requires addressing the specific needs, wants and expectations users describe.
How does this shift impact businesses in 2026?
Businesses must restructure their content to directly answer the specific, combined needs that users describe in long-form queries. Visibility in 2026 depends on providing context-rich answers, not just matching keywords.
About Plate Lunch Collective
Plate Lunch Collective is a Hawaii-based AI-native digital marketing consultancy specializing in retrieval layer optimization, optimizing the technical and semantic infrastructure determining how AI systems discover and cite businesses.
Hayden Bond
Plate Lunch Collective
+1 8086571074
email us here
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