Answer Engine Optimization: The Complete AEO and GEO Guide for 2025

Reading time: 22 minutes

If you read our Great Decoupling article, you know what changed in search economics.

This guide explains how to optimize for it.

Specifically, you’ll learn:

• The difference between Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO).
• What the Princeton GEO research actually found (and how to apply it).
• Platform-specific tactics for Google AI Overviews, Perplexity, Microsoft Copilot, Claude, and Gemini.
• How to spot and avoid “AI visibility” scams.
• Where Surmado Scan, Signal, and Solutions fit into your optimization workflow.

This is the tactical companion to the strategic overview. Let’s get specific.

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TLDR: The New Optimization Disciplines

• Traditional SEO gets you into the top 10 organic results.
• Answer Engine Optimization (AEO) makes your content easy to extract for snippets and direct answers.
• Generative Engine Optimization (GEO) convinces AI systems to cite you when they synthesize answers.
• The Princeton GEO study found that adding expert quotes boosts visibility by roughly 41%, statistics by about 30%, and citations by around 30%.
• Each platform behaves differently. Google AIOs pull mostly from top-10 results. Perplexity rewards freshness and authority. Copilot leans heavily on LinkedIn for B2B queries.
• No one can guarantee placement in AI answers. Anyone promising that is running a scam.
• Surmado Signal ($25) tests your visibility across 7 platforms. Scan ($25) fixes technical barriers. Solutions ($50) gives you the strategic playbook.

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The Vocabulary: SEO vs AEO vs GEO

Before we get tactical, you need to understand the three distinct disciplines.

Traditional SEO

Traditional Search Engine Optimization optimizes for ranking in the list of results.

The goal is to appear in positions 1-10 when someone searches for a keyword.

Core tactics:

• Keyword research and targeting.
• Backlink building.
• Technical site health (speed, mobile-friendliness, crawlability).
• Content that matches search intent.

Traditional SEO is still the foundation. Studies show a 92% correlation between pages ranking in the top 10 organically and pages cited in AI Overviews.

You cannot skip traditional SEO and jump to GEO. The AI reads the top results. If you’re not in the top 10, you’re statistically unlikely to be read by the AI in the first place.

Answer Engine Optimization (AEO)

AEO treats the search engine as a question-answering machine.

The goal is to make your content easy to extract for direct answers, featured snippets, voice responses, and AI summaries.

Core philosophy: concision and structure.

Primary tactics:

1. The 40-60 Word Direct Answer

Place the answer to the question in the first 40-60 words immediately following a question-based heading.

Example:

## Do you offer same-day HVAC repair in Dallas?

Yes. We offer 24/7 emergency HVAC repair with same-day service in Dallas,
including weekends and holidays. Our service call fee is $89, which includes
diagnosis. Repairs start at $150. Call 214-555-1234 to schedule.

This format makes it trivial for the AI to identify the question and extract the answer.

2. Question-Based Headings (H2/H3)

Structure content around actual user queries.

Instead of:

• “Our Services”
• “Pricing Information”
• “Contact Details”

Use:

• “What HVAC services do you offer in Dallas?”
• “How much does HVAC repair cost?”
• “Do you offer emergency service?”

This mirrors how users phrase questions to AI systems.

3. FAQ and HowTo Schema Markup

Schema markup is the native language AI systems prefer.

Implementing FAQPage schema tells the AI explicitly:

• This is a question.
• This is the accepted answer.
• These are the relationships between concepts.

AEO is about reducing friction between the user’s question and your answer.

Generative Engine Optimization (GEO)

GEO is newer and more technical.

The goal is to optimize for how Large Language Models select sources during the synthesis process.

Unlike AEO, which targets extraction of pre-written answers, GEO targets the model’s training biases and citation preferences.

The Princeton GEO Study

In 2024, researchers at Princeton conducted the first large-scale empirical study of GEO tactics.

They tested various content modifications across 10,000 queries and measured impact on citation probability.

Key findings:

Tactic	Impact on Visibility
Adding expert quotes with attribution	+41%
Including clear statistics and data	+30%
Adding inline citations to sources	+30%
Improving readability and fluency	+22%
Using domain-specific terminology	+21%
Simplifying language	+15%
Authoritative voice and tone	+11%
Keyword stuffing	-9%

What this tells us:

LLMs are biased toward content that looks evidentiary.

Expert quotes (+41%) work because the model uses quotation marks and attribution as a proxy for credibility.

Statistics (+30%) signal factual density.

Inline citations (+30%) show that the content itself is building on authoritative sources, creating a chain of trust.

Conversely, keyword stuffing (-9%) degrades the text’s natural flow, which the model detects through perplexity scores.

The Consensus Engine Theory

LLMs generate text based on probability. They favor information that appears consistently across their training data.

This creates what we call the “Consensus Engine” effect.

If your business hours are listed as “Mon-Fri 9-5” on your website but “Mon-Sat 8-6” on Yelp, the AI loses confidence. It may omit your hours entirely to avoid hallucinating incorrect information.

GEO strategy is about building consensus.

Your NAP (name, address, phone), hours, services, and value propositions must be identical across:

• Your website
• Google Business Profile
• Bing Places
• Yelp
• LinkedIn
• Facebook
• Apple Maps

Consistency reduces noise. The AI can triangulate the facts with high confidence.

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Comparison Table: SEO vs AEO vs GEO

Aspect	Traditional SEO	AEO	GEO
Goal	Rank in top 10 results	Be extracted for direct answers	Be cited in AI-generated synthesis
Target Systems	Google/Bing organic rankings	Featured snippets, voice search, AI summaries	LLM citation in ChatGPT, Claude, Gemini, Perplexity
Primary Metric	Keyword rankings, organic traffic	Snippet ownership, voice response frequency	Citation frequency, Share of Voice in AI answers
Core Tactics	Backlinks, keywords, technical health	40-60 word answers, Q&A format, FAQ schema	Expert quotes, statistics, consensus building, inline citations
Content Style	Comprehensive, keyword-optimized	Concise, question-focused, structured	Evidentiary, citable, authoritative
Success Signal	Position 1-3 in SERPs	Featured snippet or “People Also Ask” inclusion	Brand mentioned in AI Overview or Perplexity answer

The key insight: You need all three.

SEO gets you into the pool of pages the AI reads.

AEO makes your content easy to extract.

GEO makes the AI choose you over competitors when synthesizing the final answer.

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Platform-Specific Optimization Tactics

Each AI platform behaves differently. A one-size-fits-all approach fails.

Here’s what works for each major platform.

Google AI Overviews: The Hybrid Engine

Google AI Overviews are not a separate search engine. They are a summarization layer on top of traditional Google Search.

How it works:

1. Google runs your query through its traditional ranking algorithm.
2. It identifies the top 10-20 results.
3. The LLM reads those pages and synthesizes a summary.
4. The summary appears at the top of the SERP as the AI Overview.

Key finding: Research shows a 92% correlation between domains ranking in the traditional top 10 and domains cited in AI Overviews.

This means traditional SEO is the prerequisite. If you can’t crack the top 10, the AI won’t read you.

Optimization tactics for Google AIOs:

1. Technical Prerequisites

• JavaScript rendering: AI Overviews are generated in near-real-time. If your content requires heavy client-side JavaScript to render, the AI may time out before reading it. Use server-side rendering or ensure text is present in the initial HTML response.

• Schema markup: Controlled tests show that pages with valid, comprehensive schema are significantly more likely to be cited. Essential types: LocalBusiness, FAQPage, Article, HowTo, Product, Service.

• Robots.txt: Ensure you’re not blocking Googlebot. AI Overviews use the same crawler as traditional search. If you block it, you’re invisible.

2. Content Architecture

• The 40-word answer block: Place direct answers immediately after question-based H2 tags. This is the format the AI extracts most reliably.

• Semantic HTML structure: Pages cited in AIOs score roughly 20% better on heading hierarchy and navigation structure. Use logical H1 > H2 > H3 progression.

• Information gain: Google has explicitly stated a preference for content that adds new information to the corpus. Publish original survey data, unique case studies, or contrarian viewpoints backed by evidence.

3. The Citation Advantage

One large study found that brands cited within the AI Overview text earn about 35% more organic clicks than brands that appear in the traditional results below but are not cited.

Being cited is a badge of authority. It signals to the user that this brand is the definitive source.

4. Ads in AI Overviews

As of mid-2025, ads can appear above or below the AI Overview container.

This creates “Sponsored Citations” for brands willing to pay.

However, ads typically do not appear inside the generated text itself. The AI maintains separation between synthesis and promotion.

Perplexity AI: The Citation-First Engine

Perplexity brands itself as an “Answer Engine” focused on transparency and source attribution.

For researchers, academics, and B2B buyers, Perplexity is increasingly the first search destination.

How it works:

Perplexity uses a three-layer (L3) reranking system.

1. Broad retrieval of candidate results.
2. Reranking based on quality and relevance signals.
3. Synthesis with inline citations.

Optimization tactics for Perplexity:

1. Domain Authority Bias

Perplexity exhibits a strong preference for established, authoritative domains.

If you’re a low-authority blog competing with WebMD or Mayo Clinic, you’re unlikely to be cited unless you’re the sole source of a specific fact.

Strategy: Focus on niche expertise. Be the only source for a specific data point, case study, or local insight.

2. Freshness as a Core Signal

Perplexity updates its index multiple times daily.

Content with recent publication or update dates receives a significant ranking boost.

Tactic: Add “Last updated: [Date]” to your articles and actually update them. Refresh statistics, add new case studies, incorporate recent developments.

3. Engagement Metrics

Unlike Google, which relies heavily on links, Perplexity appears to weigh post-click engagement.

Higher scroll depth and longer session durations correlate with sustained citation frequency over time.

Implication: Your content must be genuinely useful and readable, not just optimized for extraction.

4. Focus Modes and Multi-Channel Optimization

Perplexity offers “Focus Modes” that restrict search to specific datasets.

To maximize visibility, you need a presence across multiple channels:

• All (Default): Requires standard technical SEO and high domain authority.
• Academic Mode: Restricts to scholarly papers. Publish white papers, research reports, or get cited in academic journals.
• Reddit Mode: Restricts to Reddit. Participate authentically in relevant subreddits. Ensure your brand is mentioned in high-engagement threads.
• YouTube Mode: Searches video transcripts. Create detailed video descriptions and ensure accurate closed captions.

5. The Wikipedia Gateway

Perplexity treats Wikipedia as ground truth.

If your brand or industry has a Wikipedia entry, ensure it’s accurate and neutral.

If you’re cited as a reference on relevant Wikipedia pages, your authority score in Perplexity increases significantly.

You cannot ethically manipulate Wikipedia. But you can:

• Ensure your brand meets Wikipedia’s notability guidelines.
• Get mentioned in press coverage that Wikipedia editors can cite.
• Provide accurate, neutral information to editors when they request it.

Microsoft Copilot: The B2B and Enterprise Engine

Microsoft Copilot (formerly Bing Chat) is unique due to its integration with LinkedIn, Microsoft 365, and the Microsoft Graph.

For B2B brands, Copilot is the most important platform because it’s embedded in the tools your customers use every day.

Optimization tactics for Microsoft Copilot:

1. LinkedIn as the Primary Data Source

Copilot has privileged access to LinkedIn data.

For B2B queries, it pulls heavily from:

• Company Pages
• Personal profiles of founders and executives
• Job postings
• Company updates and articles

Critical tactic: Optimize your LinkedIn presence with the same rigor as your website.

LinkedIn Company Page optimization:

• Complete 100% of fields (description, industry, size, specialties, website).
• Write a clear “About” section with specific service offerings, not vague marketing speak.
• Post regularly (at least 1-2x per week) to signal activity and recency.
• Use LinkedIn Articles to publish thought leadership that Copilot can cite.

Personal profiles for founders/executives:

• Detailed “About” sections that clearly state expertise and company role.
• Regular activity (posts, comments, shares) to signal thought leadership.
• Recommendations and endorsements that reinforce key skills.

2. Clarity Over Cleverness

Microsoft’s documentation emphasizes “Clarity Signals.”

Copilot prefers content that is unambiguous and explicit.

Bad example: “We deliver excellence in innovative solutions for forward-thinking enterprises.”

Good example: “We sell industrial HVAC systems for manufacturing facilities in Ohio. We handle installation, maintenance, and 24/7 emergency repair.”

Vague marketing language is ignored. Concrete, specific language is indexed and retrieved.

3. Citations and Footnotes

Copilot is the most aggressive platform at providing citations.

It places footnotes within the text and a “Learn More” list at the bottom.

This makes it a high-value target for referral traffic if you can get cited.

Strategy: Provide clear, citable statistics and data points in your content. Use specific numbers, dates, and attributions that the AI can footnote.

4. Local SEO and Bing Places

For local businesses, Copilot relies on Bing Places.

Many businesses optimize their Google Business Profile but neglect Bing Places.

Critical tactic: Ensure absolute consistency in NAP data across Bing Places, Google Business Profile, and your website.

A disconnect between Google and Bing is a common failure point for Copilot visibility.

5. B2B Brand Lift Measurement

Microsoft provides specific API tools for measuring “Brand Lift” and B2B performance.

Agencies working with B2B clients should explore LinkedIn’s Brand Lift Testing to quantify how campaigns influence Copilot’s perception of a brand.

Claude: The Long-Context Research Engine

Claude (by Anthropic) operates differently from search-first platforms.

It’s often used as a reasoning engine where users upload documents or ask it to analyze topics in depth.

How users interact with Claude:

• Upload PDFs, articles, or reports for analysis.
• Ask it to compare multiple sources.
• Request deep research on a topic using its browsing capability.

Optimization tactics for Claude:

1. The Definitive Guide Strategy

Claude’s distinct advantage is its large context window (up to 200,000+ tokens).

It excels at reading entire books or comprehensive reports.

Strategy: Produce long-form, comprehensive content.

“The Definitive Guide to X” format works exceptionally well.

Short, thin content is less likely to be utilized by users leveraging Claude for deep research.

2. Structured, Scannable Long-Form

Long doesn’t mean unreadable.

Claude processes structure well. Use:

• Clear section headings (H2, H3).
• Bulleted lists for key points.
• Tables for comparative data.
• Inline citations and footnotes.

This makes it easy for Claude to extract specific information when a user asks a follow-up question.

3. ClaudeBot User Agent Management

Control over Claude’s access is managed via the ClaudeBot user agent in robots.txt.

The dilemma:

• Blocking ClaudeBot prevents the model from training on your content. This protects your IP but guarantees Claude won’t “know” about your brand in future iterations.

• Allowing ClaudeBot lets the model learn from your content. This builds long-term visibility but risks your content being synthesized without attribution.

Recommendation for brands seeking visibility: Allow ClaudeBot.

The visibility benefits of having Claude cite you in future versions outweigh the IP risks for most businesses.

4. Research Mode and Multi-Source Citations

Claude’s “Research Mode” performs multi-step analysis across multiple sources.

Brands that appear across multiple high-quality domains stand the best chance of being synthesized.

Strategy: Get mentioned in:

• Industry publications
• Review sites
• Forum discussions (Reddit, Hacker News)
• News articles

This multi-source presence gives Claude triangulation points for verification.

5. Constitutional AI and Safety Filters

Claude uses “Constitutional AI” with strong safety guardrails.

Content that borders on unethical, manipulative, or factually dubious is filtered out.

Implication: Ethical, safe, well-sourced content is a prerequisite for visibility in Claude.

Gemini: The Multimodal and Workspace Engine

Gemini is Google’s native multimodal model, distinct from Google AI Overviews.

It powers the “AI Mode” assistant and integrates deeply with Google Workspace (Docs, Sheets, Gmail, Drive).

Optimization tactics for Gemini:

1. Citation Patterns: Competitors vs Publishers

Analysis of Gemini’s citation behavior reveals interesting patterns.

For niche B2B verticals (specialized finance software, industrial equipment), Gemini pulls roughly 50% of citations directly from competitor websites.

This is distinct from Google Search, which leans more on industry publications.

Implication: For B2B, your competitor’s blog is your biggest rival for AI visibility, not just their ads or rankings.

Strategy: Publish better, more detailed content than your competitors. Original research, detailed case studies, and transparent pricing information are high-value targets.

2. Discussion Forums for Technical Queries

For developer tools and technical queries, Gemini heavily weighs Reddit and Hacker News.

Strategy for technical products:

• Participate authentically in relevant subreddits.
• Answer questions on Stack Overflow.
• Engage on Hacker News when your product is mentioned.

This builds the multi-source consensus Gemini uses for technical recommendations.

3. Video SEO and Multimodal Optimization

Gemini processes video, images, and audio natively.

Unlike traditional search which reads alt text, Gemini analyzes the pixel data of images and the audio of videos.

Video optimization tactics:

• Accurate, detailed titles and descriptions.
• High-quality transcripts (not auto-generated).
• On-screen text and graphics that match the spoken content.

Image optimization tactics:

• High-quality, relevant imagery that explicitly depicts the subject matter.
• Proper file naming (not IMG_1234.jpg).
• Alt text that matches what’s actually in the image.

4. Google Workspace Integration

Gemini has deep access to Google Workspace data for users who enable it.

For B2B brands, this means:

• Email signatures and domains matter.
• Shared Google Docs and Sheets referencing your brand build entity recognition.
• Calendar invites and meeting notes mentioning your product create usage signals.

Strategy: Encourage customers to use Google Workspace integrations if your product has them. Each interaction is a signal.

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Technical Infrastructure for AI Visibility

Underpinning all content strategies is technical infrastructure.

AI crawlers are less forgiving than traditional search bots. They have lower tolerance for latency and ambiguity.

Robots.txt and AI User Agents

The robots.txt file has evolved from a simple allow/disallow list to a granular permission system.

Key user agents to know:

• Googlebot: Used for both traditional search and AI Overviews.
• GPTBot: OpenAI’s crawler for ChatGPT training.
• ClaudeBot: Anthropic’s crawler for Claude training.
• PerplexityBot: Perplexity’s crawler.
• Bingbot: Microsoft’s crawler for Bing and Copilot.

The strategic choice:

Blocking AI training bots (GPTBot, ClaudeBot) protects your IP but results in zero visibility in those tools.

For marketing purposes, the visibility benefits usually outweigh the IP risks.

Recommendation: Allow AI crawlers unless you have specific legal or competitive reasons to block them.

Advanced Schema Implementation

Schema markup is the Rosetta Stone for AI.

It translates human concepts into machine-readable entities.

Critical schema types for AI visibility:

LocalBusiness Schema

{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "name": "ABC Heating & Air",
  "description": "24/7 emergency HVAC repair with same-day service",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "123 Main St",
    "addressLocality": "Dallas",
    "addressRegion": "TX",
    "postalCode": "75201"
  },
  "telephone": "+1-214-555-1234",
  "priceRange": "$$",
  "openingHours": "Mo-Fr 08:00-18:00",
  "sameAs": [
    "https://www.facebook.com/abcheating",
    "https://www.linkedin.com/company/abcheating"
  ]
}

FAQPage Schema

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [{
    "@type": "Question",
    "name": "Do you offer same-day HVAC repair?",
    "acceptedAnswer": {
      "@type": "Answer",
      "text": "Yes. We offer 24/7 emergency HVAC repair with same-day service in Dallas, including weekends and holidays."
    }
  }]
}

Validation is critical.

Use Google’s Rich Results Test to validate schema.

Broken schema is worse than no schema. It sends conflicting signals to AI systems.

Nested schema builds relationships.

Nesting Review schema inside Product schema, or Author schema inside Article schema, establishes the connections that build E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness).

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How to Spot and Avoid AI Visibility Scams

The anxiety around AI adoption has created a marketplace for fraudulent services.

Here’s how to protect yourself.

Red Flag #1: “Guaranteed Placement” in AI Answers

The scam: Agencies promising “guaranteed inclusion” in ChatGPT, Gemini, or Google AI Overviews.

Why it’s impossible:

LLMs are non-deterministic. Their output varies based on:

• Temperature settings (randomness factor).
• User history and context.
• Random seed generation.

No external party has administrative access to insert a brand into model weights or guarantee a specific output.

The reality: You can optimize for higher probability of citation, but no one can guarantee it.

Red Flag #2: “We’ll Submit Your Site to AI” Services

The scam: Services offering to “submit your site to ChatGPT” or “register your business with AI search engines.”

Why it’s a scam:

There is no submission process for LLMs.

AI models discover businesses organically through:

• Web crawling.
• Indexing of public data (Google Business Profile, LinkedIn, Yelp).
• Training on existing web data.

There is no paid “AI listing” program. Anyone claiming to sell this is lying.

Red Flag #3: Bot Farms and Query Spam

The scam: Services that “train” AI models by spamming them with thousands of questions about your brand using bot farms.

Why it fails:

Interactions in a chat interface are not immediately fed back into the model’s training set.

Training happens in distinct, infrequent epochs (months or years apart).

Spamming queries into a live chatbot:

• Consumes API tokens.
• May trigger rate limits or bans.
• Does not “teach” the AI to recommend your brand to other users.

It’s a waste of money.

Red Flag #4: Black Hat GEO Tactics

The tactics:

• AI-generated article spinning to create mass content.
• Hidden keyword stuffing in white text.
• Cloaking (showing different content to AI crawlers than to users).

Why they fail:

Modern LLMs evaluate text quality using:

• Perplexity: A measure of how natural text sounds.
• Burstiness: Variation in sentence length and structure.

AI-generated “slop” often has low perplexity and unnatural burstiness patterns.

These are easily detected and downgraded by quality filters.

The Princeton GEO study showed that keyword stuffing reduces visibility by roughly 9%.

How to Identify Legitimate Services

Good signs:

1. Transparency about methodology. They explain what they can and cannot control.

2. Focus on measurement, not magic. They test current visibility and give you a roadmap for improvement.

3. Clear deliverables. They provide reports, audits, and action plans, not vague promises.

4. Realistic timelines. They acknowledge that building AI visibility takes weeks or months, not days.

5. No guaranteed placements. They talk about probability, not certainty.

Surmado’s approach:

We test how AI systems currently talk about your business (Signal).

We identify technical and structural issues blocking AI visibility (Scan).

We give you a strategic playbook for improvement (Solutions).

We never promise guaranteed placement because it’s technically impossible.

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Where Surmado Fits: Measurement and Strategy

The shift to answer engines requires new tools and new metrics.

Surmado offers three products designed for this era.

Surmado Signal: AI Visibility Testing ($25)

What it does:

Tests how 7 AI platforms talk about your business across 5 buyer personas.

Platforms tested:

• Google AI Overviews
• ChatGPT (OpenAI)
• Perplexity
• Claude (Anthropic)
• Gemini (Google)
• Grok (xAI)
• DeepSeek

What you get:

• Presence Rate: How often you’re mentioned (0-100%).
• Authority Score: How confidently AI systems recommend you (0-100%).
• Platform breakdown: Which platforms mention you most.
• Ghost Influence: How often competitors are mentioned instead of you.
• Citation analysis: What AI systems say about you and where they get the information.

Why this matters:

Traditional rank trackers tell you where you rank on Google.

Signal tells you what AI systems actually say about you when users ask for recommendations.

This is the new success metric: Share of Voice in AI answers.

Async and API-friendly:

Signal reports run asynchronously (about 15-30 minutes).

You can call the API, get a job ID, and receive results via webhook when complete.

Perfect for agencies managing multiple clients or devs building custom dashboards.

Cost: $25 (1 credit).

Surmado Scan: Technical Foundation for AI Visibility ($25)

What it does:

Audits your site for technical and structural issues that block AI systems from reading you.

What Scan checks:

• Schema markup (LocalBusiness, FAQ, HowTo, Product, Service).
• Core Web Vitals (LCP, CLS, INP).
• Crawlability and indexability.
• Mobile performance.
• Heading hierarchy and semantic HTML.
• Accessibility and security.

Why this matters:

AI systems can’t cite you if they can’t read you.

Scan identifies the structural barriers preventing AI platforms from understanding your business.

What you get:

A prioritized action plan. 5-10 fixes ranked by impact.

Each issue includes:

• Why it matters for AI visibility.
• How to fix it (with code examples where relevant).
• Expected impact on citation probability.

Cost: $25 (1 credit).

Surmado Solutions: Strategic Guidance ($50)

What it does:

Runs a six-AI adversarial debate analyzing your business, competitive landscape, and market positioning.

What Solutions delivers:

• Prioritized recommendations with ROI analysis.
• Multi-quarter roadmap connecting SEO, AEO, and GEO tactics.
• Real Options Valuation for high-uncertainty decisions.
• Adversarial critique to stress-test assumptions.

Why this matters:

The AI era requires strategic decisions, not just tactical fixes.

Solutions answers:

• Which content should you cut? (Kill zone avoidance)
• Which content should you double down on? (Proprietary data, hyper-transactional)
• How do you sequence experiments over 90 days?
• Which platforms should you prioritize?

For agencies:

Solutions helps you rewrite retainer proposals around answer engines and Share of Voice instead of old-school “we’ll get you to #1 for keyword X” promises.

Cost: $50 (2 credits).

Credits and Bundles: Agency Leverage

How credits work:

One credit = $25.

Most reports cost 1-2 credits.

The $100 bundle:

6 credits for $100. That’s effectively 2 free reports compared to buying credits individually.

Why bundles matter for agencies:

Agencies can buy a $100 bundle, then mix and match:

• Scan for quick audits.
• Signal for AI visibility tests.
• Solutions for bigger engagements.

No subscription. No minimums. No lock-in.

You can resell the value however you want.

Example agency workflow:

1. Client onboarding: Run Scan + Signal ($50 total, 2 credits).
2. Store baseline metrics in your CRM.
3. Run Signal monthly via API to track changes ($25/month, 1 credit).
4. Run Solutions quarterly for strategic guidance ($50/quarter, 2 credits).

The bundle gives you flexibility and margin without subscription overhead.

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The 5-Phase Implementation Playbook

Here’s how to actually implement AEO and GEO.

Phase 1: Clarity Audit (Week 1)

Objective: Establish a single, unambiguous digital identity.

Actions:

1. Audit NAP (name, address, phone) across all directories:

   • Google Business Profile
   • Bing Places
   • Yelp
   • Apple Maps
   • Facebook
   • LinkedIn

2. Check for inconsistencies in:

   • Business hours
   • Service descriptions
   • Category selections
   • Website URLs

3. Document every discrepancy.

Why this matters:

AI models function as consensus engines.

If your hours differ across platforms, the AI loses confidence and may exclude you from “Open Now” queries to avoid hallucination errors.

Metric: Aim for 100% consistency across all tier-1 directories.

Phase 2: Technical Signal Boosting (Week 2)

Objective: Translate business data into machine-readable format.

Actions:

1. Implement LocalBusiness schema with these properties:

   • name
   • description
   • address (full PostalAddress object)
   • telephone
   • priceRange
   • openingHours
   • areaServed
   • sameAs (links to social profiles)

2. Add FAQPage schema for your most common customer questions.

3. Run Google’s Rich Results Test to validate.

4. Fix any Core Web Vitals issues flagged by Surmado Scan.

Why this matters:

This disambiguates your entity.

It tells the AI “This is a plumber in Chicago” in its native code language.

Phase 3: Content Engineering for Answers (Weeks 3-4)

Objective: Capture Q&A voice queries with snippable content.

Actions:

1. Create a “Questions We’re Asked” section on your website.

2. Write 5-10 questions real customers ask.

3. Answer each question in the first 40-60 words immediately after the question heading.

4. Follow with bulleted details or supporting paragraphs.

5. Apply the Princeton GEO tactics:

   • Add at least one expert quote per topic (even if the expert is you, properly attributed).
   • Include specific statistics and data.
   • Add inline citations to authoritative sources.

Example format:

## How much does HVAC repair typically cost in Dallas?

HVAC repair in Dallas typically costs between $150-$800 depending on the issue.
Simple repairs like thermostat replacement start at $150. Compressor or evaporator
coil repairs range from $400-$800. Our service call fee is $89, which includes
diagnosis and is credited toward repair costs.

According to the National Average HVAC Repair Cost study (2024), Dallas prices
are roughly 12% above the national average due to high summer demand.

### Common Dallas HVAC Repairs and Costs:
- Thermostat replacement: $150-$250
- Refrigerant recharge: $200-$400
- Compressor repair: $400-$800
- Evaporator coil repair: $500-$800

Why this matters:

This targets the “snippable” format preferred by Google AI Overviews, Perplexity, and voice assistants.

It reduces friction for the AI to extract the answer.

Phase 4: Reputation Management Loop (Ongoing)

Objective: Feed the sentiment analysis engine with structured review data.

Actions:

1. Request reviews from recent customers.

2. Guide them to mention specific features in their reviews:

   • “same-day service”
   • “transparent pricing”
   • “good for kids”
   • “emergency availability”

3. Respond to every review (positive and negative).

4. In your response, use semantic keywords that reinforce the association:

   • “We’re glad you appreciated our same-day service.”
   • “Transparency in pricing is one of our core values.”

Why this matters:

AI systems read review content to determine “best for” recommendations.

The owner’s response confirms the context of the review, strengthening the entity-attribute association.

Phase 5: The B2B and Developer Layer (If Applicable)

Objective: Win Microsoft Copilot and enable programmatic visibility tracking.

Actions for B2B brands:

1. Optimize your LinkedIn Company Page:

   • Complete 100% of fields.
   • Write a clear, specific “About” section.
   • Post regularly (1-2x per week minimum).

2. Optimize key executive profiles:

   • Detailed “About” sections.
   • Regular activity (posts, comments).
   • Recommendations that reinforce key skills.

3. Ensure Bing Places is complete and matches Google Business Profile exactly.

Actions for developers and agencies:

1. Set up API access to Surmado Signal and Scan.

2. Build a monthly monitoring workflow:

   • Run Signal via API.
   • Store results in your CRM or BI tool.
   • Track Presence Rate and Authority Score over time.

3. Create client dashboards showing:

   • AI visibility trends.
   • Platform-by-platform breakdown.
   • Competitive benchmarking.

Why this matters:

Copilot relies heavily on LinkedIn and the Microsoft Graph.

For B2B, this is the primary channel for AI discovery.

For agencies, API integration lets you offer “AI visibility monitoring” as a service without manually running tests every month.

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The Bottom Line

The optimization landscape has split into three distinct disciplines.

Traditional SEO remains the foundation. You must rank in the top 10 for AI systems to read you.

Answer Engine Optimization (AEO) makes your content easy to extract. Concise answers, question-based headings, and FAQ schema are the core tactics.

Generative Engine Optimization (GEO) convinces AI systems to cite you. Expert quotes, statistics, inline citations, and cross-platform consistency are the differentiators.

The Princeton GEO research gives us quantitative benchmarks:

• Expert quotes: +41% visibility
• Statistics: +30% visibility
• Inline citations: +30% visibility
• Keyword stuffing: -9% visibility

Each platform behaves differently:

• Google AI Overviews: Pull from top-10 results. Optimize for traditional SEO first, then add snippable structure.
• Perplexity: Rewards freshness, authority, and multi-channel presence.
• Microsoft Copilot: Leans heavily on LinkedIn for B2B queries.
• Claude: Prefers long-form, comprehensive guides.
• Gemini: Analyzes multimodal content (video, images).

Beware of scams. No one can guarantee AI placement. Anyone promising that is lying.

Surmado helps you measure and optimize:

• Signal ($25): Test AI visibility across 7 platforms.
• Scan ($25): Fix technical barriers to AI readability.
• Solutions ($50): Get strategic guidance for the AI era.

The businesses that master AEO and GEO in 2025 will own their categories in answer engines.

The ones that ignore it will watch competitors get cited while they wonder why their rankings don’t matter anymore.

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Sources Used in This Article

This article synthesizes findings from:

• Princeton University GEO Research (2024): Empirical study of 10,000 queries measuring impact of content tactics on LLM citation probability.
• Seer Interactive / Dataslayer (2025): Large-scale analysis of AI Overviews impact on CTR and traffic.
• Pew Research Center (2025): User behavior study on clicking patterns when AI summaries appear.
• Search Engine Land: Platform-specific optimization research for Perplexity, Copilot, and Google AIOs.
• Microsoft Learn: Official documentation on LinkedIn integration with Copilot and B2B optimization.
• Multiple industry case studies: Authoritas, BrightEdge, Semrush, SE Ranking.

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Related Reading:

• AI Overviews, Zero-Click Search, and Why Your Traffic Looks Broken
• What is Generative Engine Optimization (GEO)?
• AI Visibility: How ChatGPT, Claude, and Gemini Discover Your Business
• Schema Markup for GEO
• Technical GEO Implementation Checklist

Take Action:

• Test Your AI Visibility with Signal ($25, 1 credit)
• Audit Your Technical Foundation with Scan ($25, 1 credit)
• Get Strategic Guidance with Solutions ($50, 2 credits)
• Get All Three: Complete Visibility Suite ($100, 6 credits bundle)