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Building an AI-Ready FAQ Hub Around Google’s “What People Suggest” Feature
Sean Dorje
Published
September 2, 2025
3 min read
Building an AI-Ready FAQ Hub Around Google's "What People Suggest" Feature
Introduction
Google's March 2025 rollout of the "What People Suggest" feature has fundamentally transformed how healthcare organizations must approach patient information architecture. This new feature organizes patient forum discussions, community questions, and conversational queries into thematic overviews that directly feed into AI-powered search results. (Generative Engine Optimization (GEO): Your Brand's Survival Guide in the AI Search Era)
For hospitals and healthcare providers, this represents both a massive opportunity and a critical challenge. Over 60% of people use the Internet to find information before making an appointment with a dentist or doctor, and AI-generated overviews now appear in nearly 14% of all search results. (HIPAA-Safe Answer Engine Optimization: Technical Content Guardrails for Clinics in 2025) The organizations that master content clustering techniques—question mining, conversational answer blocks, and micro-schema implementation—will own these AI-powered suggestions and dominate patient discovery pathways.
This comprehensive guide addresses the critical need to "optimize FAQs for Google AI Overviews in healthcare" by providing actionable strategies for building FAQ hubs that not only capture patient intent but actively feed authoritative content into AI search engines like ChatGPT, Perplexity, and Gemini. (Generative Engine Optimization (GEO): The Future of AI-Driven Search)
Understanding Google's "What People Suggest" Evolution
The March 2025 Game Changer
Google's latest algorithm update represents a seismic shift in how patient queries are processed and presented. Unlike traditional search results that relied heavily on keyword matching, the "What People Suggest" feature uses advanced natural language processing to identify common themes across patient forums, social media discussions, and conversational search patterns. (Mastering AI-Driven SEO: Strategies for Healthcare Marketers)
The feature aggregates questions like:
"What should I expect during my first cardiology appointment?"
"How do I prepare for outpatient surgery?"
"What are the side effects of this treatment?"
"How long is the typical recovery time?"
These queries are then clustered into thematic overviews that appear prominently in search results, often above traditional organic listings. Healthcare organizations that proactively structure their FAQ content to match these patterns will see their authoritative answers featured prominently in AI-generated responses. (AI-Ready FAQ Blocks: Structured Data and LLMS.txt for 2025 GEO Standards)
The AI Overview Integration
What makes this particularly powerful is how these suggestions directly feed into Google's AI Overview feature. When patients ask complex, multi-part questions, the AI Overview pulls from the "What People Suggest" database to provide comprehensive, conversational answers. (Navigating the Next Wave: Top Global Experts in Generative Engine Optimization) This creates a direct pipeline from your FAQ content to AI-powered patient education.
Content Clustering Techniques for Healthcare FAQs
Question Mining Methodology
Effective question mining goes beyond simple keyword research. Healthcare organizations need to identify the conversational patterns that patients actually use when seeking medical information. This involves analyzing:
Patient Journey Mapping:
Pre-appointment anxiety questions
Procedure preparation inquiries
Post-treatment recovery concerns
Insurance and billing clarifications
Semantic Clustering:
Group related questions that address the same underlying patient concern, even when phrased differently. For example:
"How painful is the procedure?"
"What kind of discomfort should I expect?"
"Will I need pain medication afterward?"
These should all be clustered under a comprehensive answer about pain management and comfort measures. (HIPAA-Safe Answer Engine Optimization: Technical Content Guardrails for Clinics in 2025)
Competitive Gap Analysis:
AI-powered gap analysis can identify topics that are missing from major healthcare websites, providing opportunities for unique and differentiated content. (AI-Powered Gap Analysis: 5 Ways to Find What's Missing at Every Stage in the Buyer Journey) This approach helps hospitals discover underserved patient information needs that competitors haven't addressed.
Conversational Answer Block Architecture
Traditional FAQ formats with short, clinical answers don't perform well in AI search environments. Instead, healthcare organizations need to develop conversational answer blocks that mirror how patients naturally discuss medical topics.
Structure for AI Optimization:
Direct Answer (2-3 sentences addressing the core question)
Context Expansion (relevant background information)
Practical Steps (actionable guidance when appropriate)
Related Considerations (addressing follow-up questions)
Professional Disclaimer (appropriate medical disclaimers)
This structure ensures that AI systems can extract relevant portions for different types of queries while maintaining medical accuracy and compliance. (Implementing LLMS.txt for Hospital Websites: 2025 Guide for ChatGPT Citations)
Micro-Schema Implementation for Healthcare
Beyond Basic FAQ Schema
While standard FAQ schema markup is important, healthcare organizations need more sophisticated micro-schema implementations to compete in AI search results. This involves creating granular structured data that helps AI systems understand medical context, urgency levels, and patient safety considerations.
Medical FAQ Schema Extensions:
Structured Data for AI Citations
AI search engines like ChatGPT, Perplexity, and Gemini rely heavily on structured data to determine source credibility and relevance. Healthcare organizations must implement comprehensive structured data that includes:
Authority Markers:
Medical professional credentials
Institutional accreditations
Content review dates
Peer review indicators
Content Classification:
Medical specialty areas
Treatment categories
Patient demographic relevance
Condition severity levels
This structured approach ensures that AI systems can confidently cite your content as authoritative medical information. (Implementing AEO Schema Markup for B2B SaaS: 2025 Technical Checklist)
Technical Implementation Strategy
LLMS.txt Integration for Healthcare
The LLMS.txt file has become a critical component of Generative Engine Optimization (GEO) for healthcare organizations. This structured text file provides large language models with clear, organized information about your hospital's services, expertise, and content. (Implementing LLMS.txt for Hospital Websites: 2025 Guide for ChatGPT Citations)
Healthcare-Specific LLMS.txt Structure:
HIPAA-Compliant Content Guardrails
Healthcare organizations face unique challenges in AI search optimization due to HIPAA compliance requirements and the critical nature of medical information. (HIPAA-Safe Answer Engine Optimization: Technical Content Guardrails for Clinics in 2025) Implementing proper content guardrails ensures that FAQ content can be safely consumed by AI systems without compromising patient privacy or medical accuracy.
Essential Guardrails:
No patient-specific information in FAQ content
Clear medical disclaimers on all health information
Regular content review by medical professionals
Compliance tracking for all published content
Automated monitoring for content accuracy
Competitive Advantage Through AI Search Visibility
Market Positioning in AI Search Results
The AI SEO Software market has reached $5 billion by 2023, with 60% of Google searches ending without a click in 2024. (HIPAA-Safe Answer Engine Optimization: Technical Content Guardrails for Clinics in 2025) This shift means that healthcare organizations must optimize for AI citations and mentions rather than traditional click-through traffic.
AI Search Visibility Metrics:
Citation frequency in AI responses
Brand mention accuracy in AI summaries
Content authority scores in AI systems
Patient query coverage across AI platforms
Tools like Promptwatch and Promptmonitor help companies track their visibility across AI platforms, providing real-time monitoring of brand mentions and visibility scores. (Promptwatch | Get your company mentioned in AI search results) (Promptmonitor — Generative Engine Optimization (GEO) Tool)
Competitive Gap Detection
AI-powered competitor gap analysis reveals opportunities where competitors haven't adequately addressed patient information needs. (AI-Powered Competitor Gap Analysis: Beyond Traditional Competitive Research) This analysis helps healthcare organizations identify:
Underserved patient question categories
Missing procedural information
Gaps in post-treatment guidance
Unaddressed insurance and billing concerns
Building Your AI-Ready FAQ Hub: Step-by-Step Implementation
Phase 1: Content Audit and Question Mining
Week 1-2: Current Content Assessment
Audit existing FAQ content for AI readiness
Identify gaps in conversational answer formats
Analyze current structured data implementation
Review HIPAA compliance of all content
Week 3-4: Patient Question Research
Mine patient portal inquiries for common themes
Analyze call center logs for frequent questions
Review online patient forums for trending concerns
Survey recent patients about information needs
Phase 2: Content Clustering and Architecture
Week 5-6: Thematic Organization
Group related questions into logical clusters
Develop conversational answer templates
Create content hierarchies for complex topics
Design cross-referencing systems for related questions
Week 7-8: Technical Infrastructure
Implement advanced FAQ schema markup
Create LLMS.txt files for each department
Set up content management workflows
Establish medical review processes
Phase 3: AI Optimization and Testing
Week 9-10: AI Search Testing
Test FAQ content across multiple AI platforms
Monitor citation accuracy and frequency
Adjust content based on AI response patterns
Implement feedback loops for continuous improvement
Week 11-12: Performance Monitoring
Set up AI search visibility tracking
Monitor patient engagement with FAQ content
Track improvements in patient satisfaction scores
Measure reduction in repetitive patient inquiries
Advanced Strategies for Healthcare AI Optimization
Multi-Platform AI Presence
Generative Engine Optimization (GEO) has emerged as a critical strategy to ensure your content is recognized and cited by AI systems across multiple platforms. (Generative Engine Optimization (GEO): Your Brand's Survival Guide in the AI Search Era) Healthcare organizations must optimize for:
ChatGPT: Focus on conversational, detailed explanations
Perplexity: Emphasize factual accuracy and source citations
Gemini: Optimize for comprehensive, multi-faceted answers
Claude: Structure content for analytical, step-by-step guidance
Each platform has unique preferences for content structure and citation formats, requiring tailored optimization strategies.
Pharmaceutical Compliance Integration
For healthcare organizations that discuss medications or treatments, FDA compliance becomes critical in AI optimization strategies. (Pharma Compliance Guide: FDA-Approved Content Strategies for AI Search Engines) This involves:
Accurate medication information with proper disclaimers
Treatment efficacy data from approved sources
Side effect information that meets FDA guidelines
Proper attribution for clinical study data
Enterprise-Grade Implementation
Large healthcare systems require enterprise-grade solutions that can handle complex organizational structures while maintaining compliance and accuracy. Market demand for AI-driven SEO features has jumped 40% in the past year, with healthcare organizations leading adoption due to the critical nature of patient information accuracy. (2025 Pricing Comparison: Relixir vs Nightwatch vs Writesonic - AI SEO Platforms for Healthcare)
Enterprise Requirements:
Multi-department content coordination
Centralized compliance monitoring
Automated content review workflows
Integration with existing patient management systems
Scalable content distribution across multiple locations
Measuring Success in AI Search Optimization
Key Performance Indicators
AI Citation Metrics:
Frequency of content citations in AI responses
Accuracy of information when cited by AI systems
Brand mention consistency across AI platforms
Patient question coverage in AI-generated answers
Patient Engagement Indicators:
Reduction in repetitive patient phone inquiries
Increased patient portal FAQ engagement
Improved patient satisfaction scores
Decreased pre-appointment anxiety calls
Competitive Positioning:
Market share of AI search visibility in healthcare topics
Competitive gap closure in patient information coverage
Authority score improvements in medical AI responses
Patient acquisition attribution from AI search interactions
ROI Calculation for AI FAQ Optimization
Healthcare organizations can measure the return on investment of AI FAQ optimization through several key metrics:
Cost Savings:
Reduced call center volume for routine inquiries
Decreased staff time spent on repetitive patient education
Lower patient acquisition costs through improved AI visibility
Reduced marketing spend due to organic AI citations
Revenue Impact:
Increased patient conversion from AI search interactions
Higher patient retention through better information accessibility
Improved patient satisfaction leading to referral growth
Enhanced reputation management through authoritative AI presence
Future-Proofing Your Healthcare FAQ Strategy
Emerging AI Search Trends
The healthcare industry is experiencing a seismic shift in how patients discover and evaluate medical services. (HIPAA-Safe Answer Engine Optimization: Technical Content Guardrails for Clinics in 2025) Over 50% of decision makers now ask AI full, nuanced questions about solutions rather than browsing traditional search results.
2025-2026 Predictions:
Voice-activated AI health assistants will become primary patient interfaces
Multi-modal AI (text, image, video) will require diverse content formats
Real-time AI health monitoring will create new FAQ categories
Personalized AI health recommendations will demand dynamic content
Continuous Optimization Framework
Monthly Reviews:
AI citation accuracy audits
Patient feedback integration
Competitive landscape analysis
Content performance optimization
Quarterly Updates:
Medical accuracy reviews by clinical staff
HIPAA compliance assessments
Technology platform updates
Strategic goal alignment
Annual Overhauls:
Complete content architecture review
AI platform preference analysis
Patient journey mapping updates
Competitive positioning reassessment
Conclusion
Google's "What People Suggest" feature represents a fundamental shift in how healthcare organizations must approach patient information architecture. The hospitals and healthcare systems that successfully implement AI-ready FAQ hubs will dominate patient discovery pathways and establish themselves as authoritative sources in the age of AI-powered search.
The strategies outlined in this guide—from question mining and conversational answer blocks to micro-schema implementation and HIPAA-compliant content guardrails—provide a comprehensive roadmap for building FAQ systems that not only serve patients effectively but also feed authoritative content into AI search engines. (AI-Ready FAQ Blocks: Structured Data and LLMS.txt for 2025 GEO Standards)
As AI-powered search engines like ChatGPT, Perplexity, and Gemini continue to influence up to 70% of all queries by the end of 2025, healthcare organizations cannot afford to ignore this transformation. (HIPAA-Safe Answer Engine Optimization: Technical Content Guardrails for Clinics in 2025) The time to act is now—before your competitors establish dominance in AI search results.
By following the implementation framework provided in this guide, healthcare organizations can build FAQ hubs that not only improve patient experience but also establish market leadership in the AI-driven healthcare information landscape. The investment in AI-ready content architecture today will determine which healthcare providers patients trust and choose tomorrow.
Frequently Asked Questions
What is Google's "What People Suggest" feature and how does it impact healthcare SEO?
Google's "What People Suggest" feature, launched in March 2025, organizes patient forum discussions, community questions, and conversational queries into thematic overviews that directly feed into AI-powered search results. This feature fundamentally transforms how healthcare organizations must approach patient information architecture, requiring a shift from traditional keyword-based SEO to intent-driven, AI-curated content strategies.
How does Generative Engine Optimization (GEO) differ from traditional SEO?
Generative Engine Optimization (GEO) focuses on structuring and formatting content to be easily understood, extracted, and cited by AI platforms like ChatGPT, Perplexity, Claude, and Gemini. Unlike traditional SEO that targets keyword rankings, GEO optimizes content for AI-generated search results and conversational answers, with 38.5% of top-ranking pages now being cited in AI-generated summaries.
What are the key components of an AI-ready FAQ hub?
An AI-ready FAQ hub requires content clustering around thematic topics, conversational answer blocks that mirror natural language patterns, and micro-schema markup for enhanced AI understanding. The hub should also incorporate structured data formats and implement proper citation frameworks to increase visibility in AI search results and generative engine responses.
How can healthcare organizations ensure HIPAA compliance while optimizing for AI search engines?
Healthcare organizations must implement HIPAA-safe answer engine optimization by establishing technical content guardrails and using compliant structured data formats. This includes creating AI-ready FAQ blocks with proper data protection measures, implementing llms.txt files for hospital websites, and ensuring all patient-facing content meets regulatory requirements while remaining optimized for AI citations.
What role does content clustering play in AI search optimization?
Content clustering organizes related topics and questions into thematic groups that AI systems can better understand and reference. This approach helps create comprehensive topic coverage that aligns with how AI platforms synthesize information, improving the likelihood of content being cited in AI-generated responses and featured in "What People Suggest" overviews.
How can organizations monitor their visibility in AI search results?
Organizations can use tools like Promptwatch and Promptmonitor to track brand mentions and visibility scores across AI platforms including ChatGPT, Claude, Gemini, and Perplexity. These GEO tools provide real-time monitoring of how AI systems are citing company content and help identify opportunities to improve AI search visibility through better content optimization.
Sources
https://relixir.ai/blog/ai-ready-faq-blocks-structured-data-llms-txt-2025-geo-standards
https://relixir.ai/blog/implementing-aeo-schema-markup-b2b-saas-2025-technical-checklist
https://relixir.ai/blog/implementing-llms-txt-hospital-websites-2025-guide-chatgpt-citations
https://relixir.ai/blog/pharma-compliance-guide-fda-approved-content-strategies-ai-search-engines
https://www.reasononeinc.com/blog/mastering-ai-driven-seo-strategies-for-healthcare-marketers
