Unlike traditional search engines where "evergreen" content can perform well for years, LLMs place a higher value on the freshness of content. To stay relevant in AI-driven search, marketers must consistently update, iterate on, and expand upon their core content pieces.
As users shift from keywords to conversational prompts in AI browsers, SEO strategy must also evolve. The focus should be on creating 'answer-ready' content that directly and comprehensively addresses likely user questions, positioning your brand as a primary source for the AI to cite.
To signal recency to Large Language Models (LLMs), marketers must include specific time periods (e.g., year, quarter, month, or 'Updated [Date]') directly in content titles. This simple change makes content over 50% more likely to appear in AI-generated results on platforms like ChatGPT, which are rapidly replacing traditional search.
Escape the content creation hamster wheel by focusing on optimization, not just volume. Instead of writing new posts on similar topics, identify existing high-performing articles and update them with new information, better formatting, and fresh insights. This simplifies your process and boosts search rankings.
The dominance of AI tools like ChatGPT, which favor new and recently updated information, is rendering traditional 'set it and forget it' evergreen content obsolete. AI citations are, on average, nearly a year newer than traditional search results, signaling a fundamental shift in content strategy that marketers must adapt to.
Users now ask AI models highly specific, long-form questions, not short search terms. HubSpot's CEO advises creating more detailed content with better citations and case studies to provide authoritative answers for these complex queries and remain visible.
The future of search isn't just about Google; it's about being found in AI tools like ChatGPT. This shift to Generative Engine Optimization (GEO) requires creating helpful, Q&A-formatted content that AI models can easily parse and present as answers, ensuring your visibility in the new search landscape.
The average age of content cited in AI search results is only 86 days and is decreasing by 10-15% each quarter. This rewards brands that continuously update existing content, not just publish new articles. A "publish and forget" strategy is now obsolete; consistent refreshes are mandatory for visibility.
AI's preference for recency extends beyond the content to the webpage itself. Pages that haven't been updated in over a year are more than twice as unlikely to be cited by AI models. This means marketers must continuously update the pages, not just the content on them, to maintain visibility in AI search.
Marketers must evolve from SEO to GEO, optimizing content for how brands appear in LLM results. This requires a new content strategy that treats the LLM as a distinct persona or channel, creating content specifically for it to crawl and ensuring accurate brand representation.
As users increasingly get answers from AI assistants, marketing strategy must evolve from Search Engine Optimization (SEO) to Generative Engine Optimization (GEO). This means creating diverse, authoritative content across multiple platforms (podcasts, PR, articles) with the goal of being cited as a trusted source by AI models themselves.