Voice Search Optimisation.

Voice search optimisation is the practice of structuring content to appear in responses delivered by voice assistants — Google Assistant, Apple Siri, Amazon Alexa, and Microsoft Cortana. Voice search queries differ from typed queries in length, phrasing, and intent, requiring specific content strategies to capture these growing conversational search interactions.

Voice Query Characteristics

Voice queries are significantly longer and more conversational than typed queries (average 4-7 words vs. 2-3 words). They frequently begin with question words: 'who', 'what', 'where', 'when', 'why', 'how'. They are more often local in intent ('where is the nearest', 'open now') and action-oriented ('call', 'navigate to', 'add to cart').

Content Optimisation for Voice

Content most likely to be selected for voice responses: featured snippet content (Google reads the featured snippet as the voice answer), FAQ-structured pages with natural conversational questions as headings, concise answers (40-50 words) directly following the question heading, local content with complete Google Business Profile data, and structured data (FAQPage, Speakable schemas).

Voice Search and AI Assistant Overlap

The distinction between voice search and AI assistants is blurring. Siri, Alexa, and Google Assistant increasingly use LLMs to generate conversational responses rather than reading a single page snippet. Optimising for voice search and optimising for AI answer engines (AEO/GEO) increasingly requires the same content characteristics: factual, concise, well-structured, question-answering content.