Voice assistants and AEO: Siri, Alexa and Google Assistant

The rise of spoken search queries

Spoken search queries are no longer a niche. More than 40 percent of all adults use a voice assistant daily, via smartphones, smart speakers or car infotainment systems. Apple Siri, Amazon Alexa and Google Assistant are the three dominant platforms, each with hundreds of millions of active users. And with the integration of AI language models into these assistants, the way they generate answers is fundamentally changing.

For website owners and content creators, this shift has direct consequences. Voice assistants typically give a single answer to a question, rather than a list of links. There is no page 1 with ten results; there is only position zero, the answer that gets read aloud. This makes voice search an extreme form of Answer Engine Optimization: if you are not the answer, you do not exist.

The integration of generative AI into voice assistants is accelerating this trend. Apple has connected Siri to Apple Intelligence, Google Assistant integrates Gemini and Amazon is experimenting with LLM-powered Alexa answers. The traditional voice assistant that only processed simple commands is evolving into a full-fledged AI conversation partner that can answer complex informational questions with source attribution.

Siri and Apple Intelligence: the closed ecosystem

Apple Siri holds a unique position. It is the voice assistant on more than 2 billion active Apple devices, from iPhones and iPads to Macs, Apple Watches and HomePods. With the integration of Apple Intelligence, Siri gains access to advanced language models that can process more complex questions.

Siri's approach to web answers has historically depended on multiple sources. For factual questions, Siri uses data from Apple Maps, Wikipedia, Wolfram Alpha and (via Safari) Google or Bing search results. With Apple Intelligence, this is shifting toward a more integrated system where the language model can synthesize information from multiple sources.

• Siri retrieves web answers primarily via the default search engine (Google in most markets, Bing is optional).
• Wikipedia is a prominent source for definition questions and factual information.
• Apple Maps is the primary source for location-based questions.
• Schema.org markup, particularly speakable schema, helps Siri identify suitable fragments for spoken answers.
• Apple Intelligence can perform on-device processing, making some answers faster and more privacy-friendly.

Google Assistant and Gemini: the most powerful combination

Google Assistant, now increasingly powered by Gemini, is the voice assistant with the strongest search foundations. The platform has direct access to Google's search index, Knowledge Graph and the AI Overviews we discuss extensively in our article on how AI Overviews are changing search results. This makes Google Assistant the voice assistant that benefits most directly from good Google SEO.

When a user asks Google Assistant a question, the system goes through a process similar to a regular Google search, but with an extra step: it selects a passage suitable for reading aloud. This is where speakable schema becomes relevant. Google has specifically introduced a Speakable structured data type that indicates which sections of a page are suitable for text-to-speech reading.

<!-- Speakable Schema.org markup for voice assistants -->
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Article title",
  "speakable": {
    "@type": "SpeakableSpecification",
    "cssSelector": [
      ".article-summary",
      ".article-intro"
    ]
  },
  "url": "https://example.com/article"
}
</script>

<!-- Alternative: specific XPath selectors -->
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebPage",
  "speakable": {
    "@type": "SpeakableSpecification",
    "xpath": [
      "/html/head/title",
      "/html/body/article/p[1]"
    ]
  }
}
</script>

The combination of Google's search index, Gemini's language model and the Speakable schema makes Google Assistant the most advanced voice assistant for informational questions. Your optimization strategy here is a direct extension of your broader Schema.org implementation, supplemented with specific voice optimization.

Amazon Alexa: the living room as search platform

Amazon Alexa has a different dynamic than Siri and Google Assistant. The platform is primarily present via Amazon Echo devices, Fire TV and other Alexa-enabled devices. The usage context is often the home situation: cooking, relaxing, household questions. This influences the type of search queries Alexa processes.

Alexa's sources for informational answers are diverse. The platform uses Bing as its primary web search source, supplemented with Wikipedia, Amazon's own data (for product-related questions) and Alexa Skills (third-party apps). With the integration of AI language models, Alexa's ability to answer complex questions is becoming increasingly stronger.

• Alexa uses Bing as its primary search layer for web questions, making Bing SEO relevant for Alexa visibility.
• Wikipedia is a frequent source for definition and factual questions.
• Alexa Skills offer an alternative route to visibility, comparable to apps in an app store.
• Product-related questions are primarily answered with Amazon data.
• The home context of much Alexa usage makes local and practical information particularly relevant.

An interesting fact is that Alexa and Microsoft Copilot share the same underlying search layer: Bing. This means that the Bing optimization strategies you apply for Copilot also affect your Alexa visibility. Consult our article on robots.txt configuration to ensure that both Bingbot and other relevant crawlers have access to your content.

Content optimization for voice search

Voice search optimization requires a different approach than traditional text optimization. Spoken search queries are fundamentally different in structure and intent from typed queries.

1. Write in conversational language. Spoken questions use natural language ("How do I make my website suitable for AI?") rather than keywords ("website AI suitable make").
2. Answer questions directly in the first sentence of each section. Voice assistants select the fragment that answers the question most concisely.
3. Keep answers between 30 and 50 words for the core passage. Voice assistants typically do not read more than two to three sentences.
4. Use FAQ structures with H3 headings containing natural question sentences.
5. Implement Speakable Schema.org markup to help voice assistants select the most suitable fragments.
6. Optimize for long-tail keywords that match spoken question patterns.

The overlap with broader AEO principles is significant. Content that scores well for voice assistants typically also scores well in featured snippets, AI Overviews and as a source for AI answer engines. The focus on direct, concise answers in natural language is a universal principle that strengthens your entire content strategy. Ensure your E-E-A-T signals are in order, because voice assistants preferentially select sources considered trustworthy and authoritative.

The future: multimodal voice assistants

The next evolution of voice assistants is multimodality. Siri on the iPhone can already combine screen content with spoken questions. Google Assistant on Pixel phones can combine visual input (camera, screen) with speech. Amazon shows visual results alongside spoken answers on Echo Show devices.

This multimodal development has consequences for your content strategy. In addition to text suitable for reading aloud, your pages must also contain visually appealing elements that can be displayed on a screen. Think of structured tables, infographics with alt text and images with descriptive captions. It is no longer sufficient to optimize only for spoken output.

• Add descriptive alt texts to images so voice assistants can describe visual content.
• Use structured tables for comparisons and overviews that can be presented both spoken and visually.
• Implement Open Graph and Twitter Card meta tags for attractive visual previews.
• Ensure your content is responsive and displays well on smart displays of all sizes.

Voice search is the ultimate test for your content. If your answer is good enough to be read aloud in a single sentence while remaining complete and accurate, then you have content that also excels in every other AI channel.

Key takeaways

• Voice assistants typically give a single answer to a question, making only "position zero" count and voice search an extreme form of AEO.
• Siri uses Google or Bing plus Wikipedia; Google Assistant relies on Google's search index and Gemini; Alexa uses Bing as its primary web search source.
• Speakable Schema.org markup helps voice assistants select suitable fragments for spoken answers.
• Conversational language, direct answers in 30 to 50 words and FAQ structures are the pillars of voice search optimization.
• Multimodal voice assistants combine speech with visual output, making images, tables and visual structure part of your optimization.

Frequently asked questions

The future of search is spoken. Websites that start with voice search optimization now are building a lead that becomes increasingly difficult to close as voice assistants become smarter and more popular.