# How can you tell whether your brand appears in AI answers?

Ask useful questions without naming the brand, then check mentions, cited sources and raw answers. Separate spontaneous presence from questions that already supply the brand name.

Mara Ellison

Verified on 2026-11-12

Dated sources and documented limitations: see the data protocol and the legal notice.

## Define a useful corpus

Collect presales, comparison and problem-solving questions. Annotate market, language, intent and whether the brand is named. Avoid selecting only questions that favor you.

## Keep signals separate

Retain question, date, model, native or web mode, full answer and cited links. A bot visit, a citation and a click are different events. An absent citation in one collection does not establish universal invisibility.

## Decide from the answers

Review cited pages and priority questions. The public AI Labs Audit case shows why good answer structure alone does not establish spontaneous presence. Repeat the same corpus after changes to observe outcomes without guaranteeing them.

## A mini corpus to start

Three unbranded questions are enough for a first reading: for example "Which AI visibility audit tools provide white-label client reports?", "Which tool tracks AI answers daily?" and "What does tracking 25 questions cost?". For each answer, record the date, the queried surface, the text, the brand mentioned if any and the cited URL. Mention rate = usable answers naming the brand / usable answers.



## ai-labs-audit-public-demo-site

- id: ai-labs-audit-public-demo-site
- byline: Mara Ellison
- productId: ai-labs-audit
- product: AI Labs Audit
- plan: Public demo
- planLabel: Public demo
- category: demo
- criterion: site
- label: Your site as seen by AI
- value: 65
- displayValue: 65/100 (B)
- unit: score/100
- unitLabel: score out of 100
- period: 2026-11-10T03:01
- periodLabel: 2026-11-10T03:01
- currency: null
- billing: null
- billingLabel: 
- scope: demo
- evidenceStatus: observed
- sourceUrl: https://ailabsaudit.com/portal/v1twjxrnnfChnnKJSX-V_wyXtpxPbYNgwZjoXXFduNg/dashboard
- verifiedAt: 2026-11-11
- context: Public AI Labs Audit portal, read-only review on 11 November 2026. Last audit displayed: 10 November 2026 at 03:01, All markets, EN/FR. Displayed indicator, not a Help4Web measurement or a vendor benchmark.
- state: available

## ai-labs-audit-public-demo-readiness

- id: ai-labs-audit-public-demo-readiness
- byline: Mara Ellison
- productId: ai-labs-audit
- product: AI Labs Audit
- plan: Public demo
- planLabel: Public demo
- category: demo
- criterion: readiness
- label: Ready for AI answers
- value: 84
- displayValue: 84/100 (B+)
- unit: score/100
- unitLabel: score out of 100
- period: 2026-11-10T03:01
- periodLabel: 2026-11-10T03:01
- currency: null
- billing: null
- billingLabel: 
- scope: demo
- evidenceStatus: observed
- sourceUrl: https://ailabsaudit.com/portal/v1twjxrnnfChnnKJSX-V_wyXtpxPbYNgwZjoXXFduNg/dashboard
- verifiedAt: 2026-11-11
- context: Public AI Labs Audit portal, read-only review on 11 November 2026. Last audit displayed: 10 November 2026 at 03:01, All markets, EN/FR. Displayed indicator, not a Help4Web measurement or a vendor benchmark.
- state: available

## ai-labs-audit-public-demo-sample

- id: ai-labs-audit-public-demo-sample
- byline: Mara Ellison
- productId: ai-labs-audit
- product: AI Labs Audit
- plan: Public demo
- planLabel: Public demo
- category: demo
- criterion: sample
- label: Total demo corpus size
- value: null
- displayValue: Global corpus not verified
- unit: 
- unitLabel: 
- period: null
- periodLabel: 
- currency: null
- billing: null
- billingLabel: 
- scope: gap
- evidenceStatus: observed
- sourceUrl: https://ailabsaudit.com/portal/v1twjxrnnfChnnKJSX-V_wyXtpxPbYNgwZjoXXFduNg/dashboard
- verifiedAt: 2026-11-11
- context: The screenshot does not establish the global corpus. The public text heatmap describes a filtered view, not necessarily every scenario. Full raw data is still needed.
- state: not_verified

Documentary review of official pages archived on 11 November 2026. Prices and allowances are publisher declarations. Three scores were observed in an authentic public portal screenshot, displaying an audit dated 10 November 2026 at 03:01. No paid accounts tested and no audit launched by Help4Web. Units and scope differ: no shared score or performance ranking. Missing information remains unknown. Send corrections to contact@help4web.net.

## Errata

Any correction to a published value is logged here with its date, the affected row identifier and the corrected value.

No correction published so far.

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