Featured snippets in Google Search display concise answers to user queries directly on the search results page, drawing content from webpages. Achieving a featured snippet relies on Google’s algorithms identifying content that directly and comprehensively answers a specific question a user poses, and as of December 2025, this process remains largely automated based on webpage structure and content relevance within the Australian Google index.
Google’s systems, currently utilising BERT and MUM models, analyse webpages for structured data – particularly question-and-answer formats, lists, tables, and definitions. Schema markup, implemented using code on a webpage, helps Google understand the content’s meaning and context; while not a direct ranking factor, it increases the likelihood of identification. In December 2025, Google Australia supports all schema types relevant to snippet eligibility. The ‘People Also Ask’ boxes and AI Overviews now frequently source information from featured snippets, amplifying their visibility. Google’s rollout of the Search Generative Experience (SGE) in Australia throughout 2026 will likely increase the importance of structured data for AI-powered answer generation. Google has announced that in 2027, further integration of multimodal data (images, video) will be considered for snippet eligibility.
Ultimately, featured snippets are awarded by Google’s algorithms based on content quality and its ability to directly answer user queries, rather than through direct submission or payment.
