Voice search queries are structurally different from typed queries: they are longer (5-7 words vs. 2-3), phrased as full questions, and optimized for spoken consumption rather than screen reading. The content that wins voice results is not the most comprehensive content on a topic - it is the content with the most directly extractable answer in the shortest sentence. This guide covers the formatting rules, the schema requirements for local voice search, and the reading-level standard that separates voice-eligible content from content that reads awkwardly when spoken aloud.
Check reading time and sentence length
Voice search answers average 29 words when read aloud. Use the word counter to check that your direct-answer paragraphs target this range and that your overall article sentence length stays accessible.
Audit heading phrasing for conversational query matching
Voice queries are phrased as full questions. Your H2 and H3 headings should mirror this phrasing to signal relevance to voice query intent.
How voice assistants select the spoken result
When a user asks a voice assistant a question, the assistant needs to produce a single spoken response - unlike Google Search, which displays 10 results for the user to evaluate. The selection process is a two-step filter: first, is this page a top-5 organic result for the query? Second, does this page have a directly extractable 29-word answer in the right format?
Pages that rank in the top 5 but have no extractable direct-answer paragraph are passed over. Pages that have a perfect answer format but rank outside the top 10 are also passed over. Both conditions must be met. The implication: voice search optimization is a second-order optimization on top of a solid organic ranking. Fix the ranking first, then optimize the answer format.
The content format that wins voice results
The direct-answer paragraph is the fundamental unit of voice optimization. Every page section that might answer a voice query needs one. The formula:
- An H2 or H3 heading phrased as a full question matching the voice query (e.g. "How long does it take to get a passport?").
- A first sentence that answers the question completely and reads naturally when spoken aloud. Target 25-35 words for the opening sentence.
- Supporting detail in the following sentences. The voice assistant reads the opening sentence; the supporting sentences serve the user who clicks through to read the full answer.
Avoid answer formats that are awkward when spoken aloud: bullet lists, tables, and numbered lists all create unnatural pauses when read sequentially. For voice-targeted content, convert list-based answers into flowing prose paragraphs.
Local voice search and the near-me query
The most commercially valuable voice search queries are local: "where is the nearest pharmacy", "what time does X close", "best pizza near me". These queries are primarily voice-initiated (users speak them on mobile or to smart speakers) and require both on-page content and LocalBusiness schema to answer reliably.
Without LocalBusiness schema, a voice assistant answering "what time does [your business] close?" has to parse unstructured text to find the hours. With LocalBusiness schema including openingHours, address, and telephone, the assistant reads structured machine-readable data and can answer the query reliably even if it never visits the page in detail.
The biggest mistake: writing for screen readers, not for voice
Most content is formatted for people sitting at a screen who can scan, skip, and re-read. Voice search rewards content formatted for a listener who hears a single spoken response and cannot rewind. The specific failures are: complex sentence structures with multiple subordinate clauses (hard to parse when spoken), dense jargon and technical vocabulary (inaccessible when heard), and answer blocks that begin with caveats or context rather than the direct answer.
The reading-level test is the fastest proxy for voice eligibility. Content that scores above grade 10 on the Flesch-Kincaid scale almost never wins voice results - not because Google explicitly penalizes complexity, but because simpler sentences are more extractable and more natural to read aloud. Write at grade 8-9 for voice-targeted sections. This does not mean writing less accurate or less expert content - it means using shorter sentences and more common vocabulary to convey the same information.
The second mistake is ignoring TTFB (time to first byte). Voice assistants need to receive the HTML quickly to extract the answer. A server response time over 200ms puts you at a disadvantage for voice result selection relative to pages on faster infrastructure.
What a clean voice search optimization workflow looks like
- Identify your voice-eligible pages: those ranking in the top 5 for question-format queries ("how to", "what is", "where is", "how much does").
- For each page, paste the key answer paragraph into the Word Counter above. Check the speaking time estimate - it should be under 15 seconds (roughly 30-35 words).
- Read the opening sentence of each answer block aloud. If it sounds unnatural when spoken, rewrite it. The voice test is subjective but reliable: if you would not say it in conversation, a voice assistant should not say it either.
- Check your page's Flesch-Kincaid reading ease score using a tool or plugin. For voice-targeted content, target a score above 60 (grade 8-9 level).
- Use the Header Tags Checker to audit heading phrasing. Rewrite any headings that use jargon or truncated phrasing - "Voice Optimization Tips" becomes "How do I optimize content for voice search?"
- If you have a local business, implement or update LocalBusiness schema with openingHours (ISO 8601 format), address (PostalAddress), and telephone. Validate in Google's Rich Results Test.
- Confirm your server TTFB using PageSpeed Insights. If it is above 200ms, investigate server-side caching or CDN configuration before further voice optimization.
Voice search optimization - quick check
5 randomized questions drawn from a pool of 10. Different every time you take it. Takes about two minutes.
Next up in AEO
- How to Get Cited by Perplexity, SearchGPT and AI Overviews - the direct-answer writing format for voice search is the same format AI retrieval systems prefer for citation extraction.
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