Question 1

What is AI Search optimization?

Accepted Answer

AI Search optimization is the work of making an organization easier for search engines and AI answer systems to find, understand, verify, cite, and recommend.

Question 2

What is answer engine optimization?

Accepted Answer

Answer engine optimization focuses on improving how an organization appears in systems that synthesize answers instead of only listing links. These systems include ChatGPT, Claude, Gemini, Copilot, Perplexity, and Google AI Overviews.

Question 3

What is generative engine optimization?

Accepted Answer

Generative engine optimization is another term for improving visibility in generative AI systems. Kumu treats it as part of AI Search optimization.

Question 4

What is LLM visibility?

Accepted Answer

LLM visibility is the degree to which large language models can recognize, retrieve, summarize, and accurately describe an organization.

Question 5

Can Kumu guarantee that an AI system will cite a company?

Accepted Answer

No. No agency can guarantee inclusion in a specific AI answer. Kumu improves the evidence, structure, clarity, and third-party signals that make inclusion more likely.

Question 6

What does Kumu test?

Accepted Answer

Kumu tests owned website signals, search visibility, AI-answer behavior, third-party verification, structured data, page-level evidence, crawlability, channel presence, and user action pathways.

Question 7

What is the Kumu Brand & Signal Benchmark?

Accepted Answer

The Kumu Brand & Signal Benchmark is an evidence-led assessment that measures Brand Integrity and Signal Architecture side by side.

Question 8

What is the difference between SEO and AI Search optimization?

Accepted Answer

SEO helps pages appear in search results. AI Search optimization also helps answer systems understand what an organization is, why it is credible, what it offers, and whether it should be cited or recommended.

Question 9

What is llms.txt?

Accepted Answer

llms.txt is an emerging way to give AI systems a concise map of important pages and context. Kumu treats it as an emerging signal, not a pass/fail requirement.

Question 10

Why doesn't ChatGPT mention my company?

Accepted Answer

Usually because one of the earlier steps failed. Before a model can mention you it has to retrieve your content, understand what you do, categorize you correctly, and find evidence it can trust. Missing structure, vague positioning, thin proof or blocked crawling all stop the process before recommendation.

Question 11

Why does an AI system describe my company incorrectly?

Accepted Answer

AI systems assemble descriptions from whatever is easiest to retrieve and most consistently repeated — often outdated pages, directories or third-party summaries. When your own properties don't state your positioning and offerings explicitly, the model fills the gap from weaker sources.

Question 12

How do I get my brand into AI answers?

Accepted Answer

Make your content retrievable, state plainly what you offer and who it is for, mark it up so machines can parse it, and support every claim with verifiable evidence. Then measure whether the answers change. Kumu's benchmark scores each of those layers so you can act in priority order.

Question 13

How is AI search visibility measured?

Accepted Answer

By testing what AI systems actually return about you, and by scoring the underlying conditions that determine those answers. Kumu measures fifteen dimensions across the Brand Integrity and the Signal Architecture Review, producing two Indexes and the Signal Gap between them.

Question 14

Does structured data help with AI search?

Accepted Answer

Yes, indirectly but materially. Structured data removes ambiguity about what an entity is, what it offers and how items relate, which makes correct categorization and citation more likely. It is not a ranking trick and it cannot compensate for missing substance.

Question 15

Do I still need SEO if I invest in AI search?

Accepted Answer

Yes. Traditional search still drives significant discovery, and much of the technical foundation — crawlability, performance, information architecture — serves both surfaces. AI search optimization adds entity clarity, evidence and comparison readiness on top of it.

Question 16

How long does it take to see improvement in AI answers?

Accepted Answer

Technical and structural fixes can register within weeks once systems re-crawl. Trust and citation signals move more slowly, typically over one to two quarters. This is why re-measurement against a fixed baseline matters more than week-to-week observation.

Question 17

How much does an AI search benchmark cost?

Accepted Answer

Kumu's Phase 1 benchmark is $500 and delivers first findings in 3–5 days. Phase 2, the full fifteen-dimension review with competitor comparison and a Transformation Roadmap, is scoped to the organization.

Question 18

Who should own AI search visibility inside a company?

Accepted Answer

It sits across marketing, content and engineering, which is why it is often unowned. The practical answer is that marketing owns the outcome and the benchmark gives engineering and content a shared, evidence-based list of what to change.

Issue	Recommended change	Expected digital outcome
Poor offering architecture	Restructure product and project pages	Better retrieval and easier comparison
Weak audience language	Rewrite positioning and page copy	Stronger relevance and comprehension
Weak action pathways	Redesign CTAs and the conversion journey	Greater opportunity for inquiry and conversion

Find the gaps. Fix what matters. Measure the difference.

Measure. Prioritize. Improve. Prove.

See what's costing you visibility, trust and conversion.

Know exactly what to fix first.

Be found.

Be understood.

Be trusted.

Be chosen.

Turn the findings into better digital performance.

Run the same benchmark again.

Three entry points. One methodology.

How findable is your brand?