Voice assistants and AI search - is this a different optimization game entirely?

Voice assistants are definitely a different game. Here’s the landscape:

Voice vs. Chat AI - Key Differences:

The data supporting voice growth:

• 1 billion+ voice searches monthly globally
• 58% of US residents have tried voice search
• 8.4 billion voice assistants in use worldwide
• 162.7 million US voice assistant users projected

Voice hasn’t plateaued - it’s shifted:

Voice was “over-hyped” in 2018-2020, leading to some backlash. But it’s quietly grown into a consistent, significant channel - especially for:

• Local searches
• Quick fact queries
• Smart home users
• Accessibility needs

Platform-by-platform optimization guide:

Google Assistant (92M US users):

Data source: Google Search, Knowledge Graph

Optimize by:

• Winning featured snippets
• Google Business Profile (if local)
• FAQ and HowTo schema
• Mobile-first content

Amazon Alexa (77M users):

Data source: Bing, Wikipedia, Amazon

Optimize by:

• Bing SEO (often overlooked)
• Wikipedia presence (if notable)
• Amazon product listings (if selling)
• Alexa Skills (advanced)

Apple Siri (86M users):

Data source: Apple Maps, Google, Bing, Wolfram Alpha

Optimize by:

• Apple Maps listing
• Strong SEO fundamentals
• Structured data
• Local presence

Platform priority framework:

The universal truth:

All voice assistants pull from search. Strong SEO fundamentals help everywhere.

Content structure for voice assistant success:

The “speakable” test:

Read your content aloud. If it sounds awkward, AI won’t use it for voice.

Bad for voice: “Leverage synergistic methodologies to optimize cross-functional deliverables.”

Good for voice: “Use these three methods to improve how your teams work together.”

Question-answer format:

Structure content as natural Q&A:

Question heading: “How long does it take to implement [software]?”

Answer (first sentence): “Most companies implement [software] in 2-4 weeks.”

Supporting detail: “The timeline depends on company size and integration complexity…”

Why this works:

Voice assistants look for concise answers to specific questions. If your first sentence directly answers the question, you’re more likely to be selected.

Word count sweet spot:

Voice answers typically run 40-60 words. Your “answer paragraph” should hit this range.

Featured snippets = voice search gold:

Why snippets matter for voice:

Google Assistant frequently reads featured snippets as answers. Win the snippet, win the voice query.

Snippet optimization tactics:

1. Question as H2 heading - Match the exact query
2. Answer immediately below - 40-60 words
3. Use lists for “how to” - Numbered steps
4. Use tables for comparisons - Clear structure

Example structure:

## What is [your product category]?

[Product category] is [clear definition in 15-25 words].
It helps businesses [primary benefit] by [how it works].
Key features include [brief list].

Testing snippet eligibility:

1. Search your target question
2. Note current snippet holder
3. Analyze their format
4. Create better version of same format

Snippet format guide:

Local voice search optimization (for those who need it):

Why 76% of voice has local intent:

People use voice while:

• Driving (“Where’s the nearest…”)
• Walking (“Is there a… nearby”)
• At home (“What time does… close”)

Local voice optimization checklist:

Google Business Profile:

• Complete all fields
• Accurate hours
• Updated phone/address
• Photos
• Regular posts
• Review responses

On-site local signals:

• NAP consistency everywhere
• LocalBusiness schema
• Location pages (if multiple)
• Service area content

“Near me” optimization:

• Don’t literally use “near me” in content
• Focus on city/neighborhood names
• Local landmarks and references

Voice-specific local queries:

“What’s the best [category] in [location]?” “Is [business] open right now?” “Directions to [business]” “[Business] phone number”

For these to work:

Your Google Business Profile must be optimized and verified. Voice assistants pull local data from there primarily.

Voice commerce angle (if you sell products):

The market:

• $80 billion projected annually by 2025
• Alexa dominates voice shopping
• “Alexa, reorder [product]” is growing

E-commerce voice optimization:

1. Product listings on Amazon - Alexa defaults here
2. Clear product names - Speakable, unambiguous
3. Review volume - Voice assistants prioritize well-reviewed
4. Price point clarity - For voice comparison queries

Voice shopping queries:

• “What’s the best [product] under $100?”
• “Order more [product]”
• “Compare [product A] and [product B]”
• “Is [brand] good quality?”

For B2B (like OP):

Voice commerce is less relevant, but voice research matters:

“What’s the best project management software?” “Compare Salesforce alternatives” “How much does [software] cost?”

These happen more often than you’d think, especially from busy executives.

This clarifies a lot. Here’s my takeaway:

Voice assistants for B2B = secondary priority

Focus order:

1. ChatGPT/Perplexity (primary chat AI)
2. Google AI Overviews
3. Google Assistant (voice)
4. Alexa/Siri (lowest priority)

But there’s significant overlap:

Tactics that help voice also help chat AI:

• Conversational content structure
• Question-answer format
• Featured snippet optimization
• Clear, concise answers
• FAQ schema

What we’re implementing:

Already doing (doubles for voice):

• FAQ sections with schema
• Question-based headings
• Concise answer paragraphs

Adding for voice specifically:

• “Speakable” content test
• Definition content for our category
• Featured snippet targeting for key questions

Not prioritizing (B2B irrelevant):

• Local optimization
• Voice commerce
• Alexa Skills development

Measurement approach:

• Track featured snippet wins
• Monitor branded voice queries (when possible)
• Test voice assistants quarterly for key queries

Key insight:

Voice optimization isn’t a separate strategy for us - it’s a byproduct of good conversational content strategy. Chat AI is primary; voice is bonus.

Thanks everyone for the clarity!