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Research Lab

Data about AI visibility,
not marketing promises.

Breakdowns of peer-reviewed work, preprints and industry research on zero-click, the overlap between AI Overviews and the SERP, answer instability and citation bias. Every piece rests on the source catalogue.

May 2026

AI bot access: robots.txt for GPTBot, ClaudeBot, PerplexityBot, CCBot

Every platform has its own agent. robots.txt is access control, not removal from Search. The cheapest check in a GEO audit.

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May 2026

Structured data for AEO: what markup does and does not do

Explicit clues and Search eligibility — yes; a special schema for AI Overviews and a direct AI boost — no. The line between usefulness and overclaim.

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May 2026

How to write passage-ready content: a practical checklist

Editorial heuristics from retrieval research: claim first, self-contained block. Not a Google requirement to chop content up.

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May 2026

From keywords to prompt and query clusters

Target groups of questions and intents rather than individual keys. A practical strategy drawn from SEO/IR research, not a proven formula.

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May 2026

Zero-click: why the value of search is moving into the answer

A share of searches ends without a click to the open web, and an AI summary lowers the click-through. Three sources examined, with the methodological caveat (panel/clickstream).

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May 2026

AI Overviews versus the SERP top 10: how much does AI cite what already ranks

The overlap between organic rank and AI citation is partial and moving. Industry studies and empirical work examined, without invented percentages.

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May 2026

AI answer instability: why one measurement misleads

Answers and the set of cited sources change between runs. Why GEO monitoring has to be a repeatable process.

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May 2026

Citation bias: why an AI citation is not objective visibility

A different map of domains, bias by media type (in the scenario studied), and correctness ≠ faithfulness. Three papers examined.

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Enigma in practice

Stories from audits, not just theory

What we put into the product is not abstract SEO advice but the patterns that keep recurring in GEO audits: what the model saw, which source it cited, where the brand went missing, and which page has to be rewritten.

Cited definition

An Enigma field note is an anonymized audit story containing a checkable signal, the action the page owner took, and the limits of the data. The format helps people and AI understand not only what to do, but why the recommendation appeared at all.

B2B SaaS · brand visibility

The brand is mentioned, but the source belongs to someone else

In a typical B2B SaaS audit the brand shows up for a direct branded query, while comparison and buying-intent prompts lean on review sites or competitor pages. The problem is not the brand name — it is the absence of a cited methodology and a comparison of its own.

Evidence
The prompt matrix shows mentions without an owned citation; citation rows point to a third-party source as the basis of the answer.
Action
Publish a methodology page, comparison answer blocks, and an FAQ covering selection criteria.
Limitation
Client names and uplift figures are not shown without confirmed permission; impact stays N/A.
E-commerce · category intent

AI picks directories over your category pages

In e-commerce the model often cites marketplace directories, because the category page carries no short block on selection criteria, availability, returns and alternatives. The page exists — it just offers no answer-ready evidence.

Evidence
Citation context resolves to an external directory; the brand category is in the sitemap but does not cover source-authority intent.
Action
Add a buyer guide, a criteria table, a shipping and returns block, and an FAQ that matches the visible content.
Limitation
Demand estimates made without a live SEO export are labelled Estimated, never Measured.
Agency · multi-client governance

The content team and the technical team pull different levers

A recurring agency problem: an editor adds FAQs and comparisons while robots.txt, the CDN or a WAF quietly block some AI and user-requested agents. The content is citation-ready on paper and not always reachable in practice.

Evidence
The crawler checklist records the gap between the intended access policy and the rules bots actually meet.
Action
Split training crawler policy, retrieval/search access and user-triggered fetch agents into a separate decision table.
Limitation
The final policy follows the brand's legal position and should not be imposed by a template.
Research-led content · proof depth

The evidence is there, buried too deep

Research-led articles usually do have sources, but the claim, the date, the study limits and the action for the reader sit in different places. AI can lift a fragment out of context and lose the point of the recommendation.

Evidence
The content-gap audit flags long paragraphs with no opening claim and a weak link from claim to evidence.
Action
Rewrite sections as claim, argument, proof, limitation — and put a summary box ahead of the deep material.
Limitation
Where primary sources cannot be reached, the block is marked needs review rather than published as fact.
Ownership workflowHow a story becomes a backlog item
Input

URL, intent cluster, model, run date, and the visible fragment of the answer.

Evidence

Mention, citation, absorption, the cited source, a crawler finding or a content gap.

Decision

A specific page, answer block, schema, technical rule or source layer.

Guardrail

Unverified metrics stay N/A; client names are never published without permission.

Put the data to work.

Enigma measures AI visibility through repeated runs, with no promises of inclusion.

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