How LocalAnswer Achieved 50% More Citations with AEO

LocalAnswer, a leading business directory platform, achieved a remarkable 50% increase in citations by strategically implementing Answer Engine Optimization (AEO) throughout 2025-2026. Their success came from systematically restructuring content to directly answer specific local business queries and optimizing for AI-powered search engines like ChatGPT, Perplexity, and Google's AI Overviews.

Why This Matters

Citations remain the backbone of local SEO, but traditional citation strategies are becoming less effective as AI search engines reshape how users discover local businesses. In 2026, over 60% of local searches now involve AI-powered platforms that prioritize factual, well-structured answers over traditional keyword optimization.

LocalAnswer recognized that AI engines prefer content that directly answers questions with clear, factual information. Instead of generic business listings, they needed to create citation-worthy content that AI systems could confidently reference and quote. This shift from keyword-focused to answer-focused content became their competitive advantage.

How It Works

LocalAnswer's AEO strategy focused on three core elements that AI search engines value most:

Structured Answer Formats: They restructured business profiles using question-and-answer formats. Instead of "John's Pizza serves delicious Italian food," they wrote "What type of cuisine does John's Pizza serve? John's Pizza specializes in authentic Italian cuisine, featuring hand-tossed pizzas and traditional pasta dishes."

Entity-Rich Content: Each business listing included specific entity information that AI engines could easily parse: exact addresses, phone numbers, business categories, hours of operation, and service areas. They used schema markup to make this data machine-readable.

Source Authority Signals: They added verification badges, customer review summaries, and cross-references to other authoritative local sources. AI engines prioritize information from sources they perceive as trustworthy and well-connected within their knowledge graphs.

Practical Implementation

LocalAnswer implemented their AEO citation strategy through four key phases:

Phase 1: Query Research and Mapping

They identified the most common questions potential customers ask about local businesses in each category. For restaurants, this included "What are the hours?", "Do they offer delivery?", and "What's their specialty?" They then mapped each business listing to answer these specific queries.

Phase 2: Content Restructuring

Every business profile was rewritten in a Q&A format targeting these identified queries. They created standardized templates that ensured consistent, AI-friendly formatting while maintaining unique, accurate information for each business.

Phase 3: Technical Optimization

They implemented comprehensive schema markup, created XML sitemaps specifically for AI crawlers, and added structured data for local business information. They also optimized page load speeds and mobile responsiveness, as AI engines factor technical performance into their source selection.

Phase 4: Authority Building

LocalAnswer established partnerships with local chambers of commerce, Better Business Bureau chapters, and industry associations. They created cross-referential content that linked their listings to these authoritative sources, building the entity relationships that AI engines use to validate information.

Monitoring and Refinement

They tracked which business profiles appeared most frequently in AI search results using tools like AnswerThePublic and monitoring ChatGPT responses to local queries. This data informed continuous content optimization and helped identify new question patterns to target.

Key Takeaways

• Structure content as direct answers to specific questions rather than generic descriptions—AI engines strongly prefer this format for citations

• Implement comprehensive schema markup and entity-based optimization to help AI systems easily parse and validate your business information

• Build authority through cross-references and partnerships with established local organizations that AI engines already trust

• Monitor AI search results regularly to identify which content formats and information types get cited most frequently in your market

• Focus on factual accuracy and consistency across all platforms, as AI engines cross-reference information and penalize conflicting data