The Microsoft Advertising blog recently published a post about how to optimize content for AI Search Answers. I found it unusual that this topic appeared on the Microsoft Advertising blog rather than on the Bing Search blog because (a) it’s an advertising-focused blog, and (b) the author, Krishna Madhavan, is a member of the Bing team, not the ads team. The post, titled "Optimizing Your Content for Inclusion in AI Search Answers, " covers how to structure your content, use schema, avoid common mistakes, writing techniques, and more. The blog explains that a fundamental difference between traditional search and AI search lies in how content is presented in the results. As stated, “In traditional search, visibility meant appearing in a ranked list of links.
In AI search, ranking still happens, but it’s less about ordering entire pages and more about which pieces of content earn a place in the final answer. ” The author also notes, “AI assistants don’t read a page top to bottom like a person would. They break content into smaller, usable pieces — a process called parsing. ” He concludes with several key points: - Traditional SEO remains crucial: ensure crawlability, metadata, and internal linking are solid foundations. - Structure content effectively: use schema, clear headings, and modular layouts. - Write clearly: maintain precision in language, context, and punctuation. - Make answers snippable: employ concise, self-contained phrasing in lists, Q&As, and tables. Once again, what strikes me as odd is that this was posted on the advertising blog.
How to Optimize Content for AI Search Answers: Insights from Microsoft Advertising Blog
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