Optimise for Siri, Google Assistant, and Alexa. Conversational SEO strategies for the voice-first search era.
Voice SearchConversational SEOAI Assistants
Voice search continues growing as smart speakers and voice assistants become ubiquitous. For Melbourne businesses, optimising for conversational queries is essential for capturing voice-driven traffic.
How Voice Search Differs
Voice searches are fundamentally different from typed queries:
Longer queries – Voice uses natural language, not keyword shorthand
Question format – "What is..." rather than just keywords
Local intent – High percentage of "near me" queries
Single answer expected – Voice returns one answer, not a list
Voice SEO Reality: Voice assistants typically read from featured snippets or top results. If you want voice visibility, you need position zero or strong local pack presence.
Voice Search optimisation Strategies
1. Target Conversational Keywords
Research and target full question phrases: "What's the best coffee shop in South Yarra" rather than "coffee shop South Yarra."
2. Provide Direct Answers
Structure content with clear questions as headings and concise answers (40-60 words) immediately following. This format wins featured snippets.
3. Optimise for Local
Many voice searches have local intent. Ensure your local SEO is strong—GBP optimised, citations consistent, reviews strong.
4. Use FAQ Schema
FAQPage schema helps search engines identify Q&A content, increasing chances of being selected for voice responses.
5. Ensure Mobile Speed
Most voice searches happen on mobile. Fast-loading, mobile-optimised pages are essential.
For comprehensive AI and voice search strategies, explore our AI Search optimisation services.
Voice Search and AI Assistant Optimisation
Voice search and AI assistants are converging. Optimising for voice increasingly means optimising for AI search. Here's how Melbourne businesses can capture this growing channel.
Voice Search Patterns
Voice searches differ from typed searches:
Conversational: "Hey Google, who's the best electrician in Hawthorn?"
Question-based: "What does a switchboard upgrade cost in Melbourne?"
Location-specific: "Find a plumber near me"
Action-oriented: "Call the nearest emergency electrician"
Content Structure for Voice
Format content so voice assistants can easily extract and read answers:
Use question-based headings matching voice queries
Provide concise answers (29 words average for voice results)
Follow brief answers with comprehensive supporting content
Optimise for featured snippets (often become voice results)
Voice + AI Convergence
Voice assistants increasingly use AI models similar to ChatGPT. Content optimised for AI search naturally performs well in voice search—the same comprehensive, well-structured approach works for both.
Frequently Asked Questions
How is voice search different from typed search?
Voice searches are longer, more conversational, and often phrased as questions. Users say 'What's the best Italian restaurant near me' rather than typing 'Italian restaurant Melbourne'. Voice also expects a single, direct answer.
How do I optimise content for voice search?
Target conversational, question-based queries. Provide direct, concise answers (40-60 words ideal). Use natural language, implement FAQ schema, optimise for local queries, and ensure fast page loading for mobile devices.
Does voice search affect local SEO?
Yes, significantly. Many voice searches have local intent ('near me' queries). Optimise your Google Business Profile, ensure NAP consistency, target local conversational queries, and focus on 'near me' variations.
What types of queries work best for voice search?
Voice search favors informational queries (how, what, why, when), local queries (near me, in Melbourne), direct questions, and action-oriented requests. Optimise for these patterns with clear, direct answers.
Will voice search replace typed search?
Voice search complements rather than replaces typed search. It's growing for local, quick-answer, and hands-free queries but typed search remains dominant for research and complex topics. Optimise for both.
Voice search and AI assistants are converging. Optimising for voice increasingly means optimising for AI search. Here's how Melbourne businesses can capture this growing channel.
Voice Search Patterns
Voice searches differ from typed searches:
Conversational: "Hey Google, who's the best electrician in Hawthorn?"
Question-based: "What does a switchboard upgrade cost in Melbourne?"
Location-specific: "Find a plumber near me"
Action-oriented: "Call the nearest emergency electrician"
Content Structure for Voice
Format content so voice assistants can easily extract and read answers:
Use question-based headings matching voice queries
Provide concise answers (29 words average for voice results)
Follow brief answers with comprehensive supporting content
Optimise for featured snippets (often become voice results)
Voice + AI Convergence
Voice assistants increasingly use AI models similar to ChatGPT. Content optimised for AI search naturally performs well in voice search—the same comprehensive, well-structured approach works for both.
Frequently Asked Questions
How does voice search relate to AI SEO?
Voice search and AI search are converging. Voice assistants like Siri, Alexa, and Google Assistant increasingly use AI models similar to ChatGPT to answer queries. Optimising for voice search often means optimising for AI—both favour conversational content, direct answers, and comprehensive coverage of user questions.
What voice search queries should Melbourne businesses target?
Target conversational queries that start with question words (who, what, where, when, why, how) and location-specific queries ('near me,' 'in Melbourne,' 'in [suburb]'). These reflect how people naturally speak to voice assistants and are often the same queries that AI systems answer.
How do I optimise content for voice search?
Optimise for voice by using conversational language, providing direct answers in the first paragraph, creating FAQ content, implementing speakable schema markup, and ensuring your Google Business Profile is complete. Voice search optimisation and AI SEO are highly complementary strategies.
What's the ideal content length for voice search?
Voice search answers are typically 29 words on average. While your overall content should be comprehensive, include concise, quotable answers that voice assistants can read aloud. Structure content with clear questions and direct answers that AI systems can easily extract and cite.
Do voice search and AI search require different strategies?
The strategies are largely aligned but with some differences. Voice search emphasises brevity and speakability, while AI search values comprehensiveness. The best approach covers both: comprehensive content with clear, concise key points that can be cited in both voice and text AI responses.