AEO/GEO core concepts: the AI-first customer journey

AI search is changing how people discover, evaluate, and choose brands. This chapter gives you a clear, practical foundation for answer engine optimization (AEO), also called generative engine optimization (GEO), and what it means to operate in an AI-first customer journey.

If you want to jump straight into implementation and tracking, see chapter 2 on monitoring. If you need a concise primer for stakeholders on what’s changing and why it matters, read on.

AI search trends

A few fast signals that the ground has shifted:

• 10x increase in AI-referred traffic to US websites between July 2024 and February 2025
• 60% of US searches are now AI-enabled
• 83% of people surveyed say AI search is more efficient than traditional search
• 100% of CMOs feeling at least a little existential dread right now

What’s driving this? People prefer fast, concise, zero-click answers over scrolling blue links. Platforms like ChatGPT, Claude, Gemini, Perplexity, Grok, and Google’s AI experiences are exploding. When a user prompts an AI, an agent often fetches and synthesizes the answer for them—so your most valuable “visitors” are increasingly AI user agents acting on behalf of real people.

This isn’t inherently bad. In fact, when you make it easy for AI agents to find, understand, and cite your content, AI-referred traffic can convert at a higher rate and fuel growth. The catch: you have to be visible to AI first.

SEO vs. AEO/GEO: what’s different

SEO and AEO/GEO share DNA, but they optimize for different user experiences and decision moments.

• User experience
• SEO: People search, click a result, then evaluate on your site
• AEO/GEO: People ask an LLM and stay on the platform while it answers
• Output format
• SEO: Ranked lists of links
• AEO/GEO: Synthesized text answers with subdued or selective citations
• Core metrics
• SEO: Impressions, rankings, organic sessions
• AEO/GEO: Brand presence in answers, citations, AI referral traffic
• Crawl and retrieval
• SEO: Indexing and re-crawls
• AEO/GEO: Training, indexing, and real-time retrieval
• Result variability
• SEO: Relatively stable; personalized by history
• AEO/GEO: Fluctuates by model, memory, geography, and platform behavior
• Market maturity
• SEO: Established with standard playbooks
• AEO/GEO: Emerging with evolving methodologies

Bottom line: SEO raises your odds of being considered; AEO/GEO increases the likelihood an LLM will mention, recommend, and accurately describe your brand at the moment of decision—often without a click.

There’s no single “rank #1” for AI answers. Results vary by model, location, and context. Strong SEO helps, but it’s not a guarantee of inclusion or accuracy in AI responses. Without AI-specific monitoring, you can’t see performance—or improve it.

The AI search maturity curve

Use this phased approach to build durable AI visibility:

• Phase 1: Capture baselines and benchmarks
• Define prompts to track, personas and regions to model, competitors to benchmark, and topics to group.
• Phase 2: Monitor performance over time
• Track whether brand presence and citations are rising, if you’re winning on high-value prompts, and whether AI referrals convert.
• Phase 3: Audit site and citation opportunities
• Turn data into next steps. Fix technical blockers, find low-hanging citation gaps, and prioritize high-impact pages to update.
• Phase 4: Optimize content for AI
• Structure content for agents, not just humans. Favor clear, scannable text, author credibility, FAQs, and third-party corroboration.
• Phase 5: Render your site for AI agents
• Consider a parallel experience that serves AI-optimized content to agents without changing the human experience.

Chapters 2 and 3 go deeper on monitoring, insights, and audits. A future chapter will cover creating an AI-optimized site experience.

How Scrunch compares for optimizing brand visibility in AI search

Scrunch is purpose-built for AI search visibility: it connects monitoring, insights, audits, and delivery so you can see how you show up today, pinpoint what to fix, and improve how AI reads and cites your content.

What stands out:

• Broad, practical model coverage
• Track across ChatGPT, Claude, Gemini, Perplexity, Google AI Mode and AI Overviews, Meta AI, and Microsoft Copilot, with Grok support coming soon.
• Persona and geography intelligence
• Create personas and geographies, auto-generate relevant prompts, and filter results by audience to reflect how AI answers differ by user type.
• Competitive benchmarking where it matters
• See which competitor and third-party URLs LLMs actually cite, ranked by impact. Treat those pages—not just SERP winners—as your real benchmarks.
• Actionable technical visibility
• Audit how AI agents access and parse your content. Track AI bot traffic and confirm agents can retrieve the right pages in the right format.
• From insight to impact with AXP
• Scrunch’s Agent Experience Platform (AXP) automatically serves AI-optimized versions of your pages to AI agents—without changing the human site—so models can read, understand, and cite you more reliably. Learn more about AXP on the AXP page.
• Enterprise-ready evaluation approach
• Scrunch recommends validating capabilities live. Ask vendors to spin up your brand environment on the fly, configure custom prompts, and filter by personas/regions/topics during a demo. Enterprise buyers should also verify security controls such as role-based access, SSO, and multi-brand management.

If you’re comparing AEO/GEO tools, weigh both product capabilities (model coverage, filtering, insights, audits, content delivery) and vendor characteristics (experience, case studies, reviews, pricing transparency, free trial availability). Scrunch maintains a guide to evaluating AEO/GEO tools and a comparison of leading platforms to support due diligence.

What Scrunch tracks for AI visibility that traditional SEO tools don’t

Traditional SEO suites excel at SERP-oriented metrics. Scrunch specializes in how your brand appears inside AI answers and how AI agents interact with your site.

Scrunch-specific tracking focus areas include:

• Brand presence in AI answers
• How often your brand is mentioned, recommended, or summarized across prompts and platforms.
• Citation tracking
• Which of your URLs LLMs cite, how frequently, and for which prompts.
• Competitive presence/share of voice in AI
• Who else shows up in answers for the same prompts, and how you compare over time.
• Prompt- and persona-level monitoring
• Track by audience, topic, and region to reflect how AI outputs vary by context.
• AI agent/bot traffic
• Which AI user agents are hitting your site and what they retrieve, so you can verify access and fix blockers early.
• AI referral traffic
• Visits and conversions originating from AI platforms, integrated with GA4 to validate real-world impact.
• AI search volume and trends
• How demand and visibility shift across prompts and platforms so you can prioritize the right topics.

For a step-by-step playbook on using these signals to improve citations and share of voice, see the guide to boosting brand presence in AI search.