Your website ranks on page one for your target keywords. Your content gets shared on social media. Your brand is well-known in your industry. But when potential customers ask ChatGPT, Perplexity, or Claude AI about your product category, your brand never gets mentioned.
Welcome to the new reality of search.
While marketers focus on traditional SEO metrics, a fundamental shift is happening. Gartner analysts predict a 25% decline in traditional search engine volume by 2026 due to AI chatbots and virtual agents. When Google's AI Overviews appear in search results, click-through rates plummet from 28% to 11% on desktop and from 38% to 21% on mobile.
If users get answers directly from AI without clicking through to websites, traditional SEO strategies become less effective at driving traffic and leads.
Some brands are already winning in this new landscape. They're getting cited by AI tools, earning mentions in generated responses, and capturing visibility that competitors don't know exists yet.
This new discipline, called Generative Engine Optimization (GEO) or AI Engine Optimization (AEO), requires a fundamental rethinking of content strategy, technical optimization, and brand authority building.
The way people interact with search is changing rapidly. On AI platforms, average query length has jumped to 10-11 words, significantly longer than traditional 3-4 word search queries. Users ask complete questions instead of typing fragmented keywords.
These platforms source and present information differently:
Each platform has different sourcing mechanisms, requiring a more nuanced approach than traditional SEO.
While most companies are still figuring out AI search implications, early adopters report impressive results.
M8L.com implemented a focused 90-day AI optimization strategy including structured content creation, enhanced expertise signals, and original research publication. Result: 187% increase in ChatGPT citations and 43% boost in referral traffic.
A B2B SaaS company organized content around "Predictive Maintenance" with 10 interconnected posts covering the topic comprehensively. Within three months, ChatGPT-4 began citing their articles as authoritative resources, contributing to a 28% overall web traffic increase.
What made these companies successful? Three key factors:
Each AI platform has specific optimization requirements. Success means understanding where each platform sources information and tailoring your approach accordingly.
Platform |
Primary Sources |
Key Optimization Focus |
Content Priority |
ChatGPT |
Training data + Bing search index |
Bing SEO, clear content structure |
Direct answers, Q&A format |
Gemini/AI Overviews |
Google search + Knowledge Graph |
Traditional Google SEO, E-E-A-T signals |
Rich, authoritative content |
Perplexity |
Real-time web + diverse sources |
Fresh content, citation-worthy sources |
Structured formatting, credible linking |
Claude |
API documents, user uploads |
Data-rich content for visualization |
Enterprise value propositions |
Deepseek |
Training data + optional web search |
Technical content, reasoning transparency |
Well-structured, data-driven content |
At the same time, you can't use a one-size-fits-all approach:
AI systems don't randomly select content for responses. They look for specific characteristics signaling authority, clarity, and usefulness.
Lead with answers, then elaborate:
Credibility indicators AI systems recognize:
Make content AI-parseable:
Getting found by AI requires ensuring content is technically accessible to AI crawlers and retrieval systems. Many websites inadvertently block the very bots they want to attract.
Your website is one piece of the AI visibility puzzle. These systems draw information from across the web, making a broader digital presence critically important.
Build a consistent and authoritative entity for your brand across the entire web. Ensure your brand name, products, executives, and core topics are discussed consistently on your website, in PR coverage, on forums, in YouTube videos, and on review sites. AI systems connect these dots to validate expertise and determine trustworthy sources worth citing.
Platforms like Reddit were core components of training data for many foundational models and remain preferred sources for answer engines like Perplexity. These platforms provide real-world, conversational context that AI systems value.
Best practices:
Video content increasingly gets referenced by AI systems. Perplexity and Google's AI Overviews regularly cite YouTube content, especially videos with accurate, human-reviewed transcripts that make content "readable" and "citable" for AI systems.
Key optimization tactics:
Earn mentions on authoritative sites that AI systems recognize as trustworthy sources. A single citation in a respected industry publication or academic paper can be more valuable than dozens of mentions on low-authority sites.
Wikipedia consideration: A well-maintained, neutral Wikipedia page can significantly influence AI responses since Wikipedia is a common source in training datasets and retrieval systems.
Traditional SEO metrics tell only part of the story in an AI-driven search landscape. You need new ways to measure visibility and impact.
Traditional SEO Metrics |
AI Visibility Metrics |
Tracking Method |
Organic traffic |
Citation frequency in AI responses |
Manual testing + specialized tools |
Keyword rankings |
AI answer inclusion rate |
HubSpot AI Search Grader, Writesonic GEO Tool |
Click-through rates |
Referral traffic from AI platforms |
Google Analytics 4 custom segments |
Time on page |
Context and sentiment of AI mentions |
Manual analysis + Peec AI |
Conversion rate |
Engagement from AI-referred users |
Enhanced "How did you find us?" forms |
Direct attribution from AI mentions to business outcomes remains difficult due to indirect influence and current tracking limitations. Many AI interactions don't result in immediate clicks but influence later branded searches or direct website visits.
As SEO expert Crystal Carter of Wix notes, marketers should adapt "how did you find us" forms to directly attribute leads from AI assistants. Successful measurement requires combining quantitative data with qualitative analysis.
Practical steps:
Companies winning in AI search aren't waiting for perfect tools or complete clarity. They're experimenting, measuring, and iterating based on results.
Start with systematic testing rather than trying to optimize for every platform simultaneously. Pick 1–2 AI platforms most relevant to your audience, focus initial efforts there, and expand as you learn what works.
We're in the early stages of AI search optimization. Brands that start building AI visibility now will have significant advantages over competitors who wait for landscape maturation.
At Roketto, we've been tracking these trends and adapting strategies accordingly. Our HyperContent approach creates comprehensive, interconnected content clusters around specific topics, naturally aligning with how AI systems evaluate topical authority. Our emphasis on original research and data-driven insights gives clients the unique content that AI platforms increasingly prefer to cite.
The technical foundation we build for traditional SEO translates directly to better AI accessibility:
Success in AI search requires understanding how different AI platforms source information, what content characteristics they prioritize, and how to measure visibility where traditional metrics fall short.
The question isn't whether AI will reshape how people find information. The question is whether your brand will be visible when they do.
Ready to audit your brand's AI visibility? We're offering complimentary AI Search Assessments to help businesses understand where they stand in this evolving landscape. Contact us to learn how your content performs across major AI platforms and get specific recommendations for improvement.