AI Knows Us Weekly Visibility Health Check (Retention)
A checklist with 7 steps: Open the multi-brand client management area and select the client workspace.
By InnovaAI ResearchPublished
What are the steps?
AI Knows Us Weekly Visibility Health Check (Retention)
- 01
Open the multi-brand client management area and select the client workspace
Confirm the workspace still points at the client's live website URL and the correct city and language settings before reading any numbers, since a stale URL invalidates the week's comparison.
- 02
Pull the weekly named-in-answer report across all five engines
The service re-checks ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews every week. Read named-in-answer rate, position when named, and which sources the AI read for each engine separately rather than as one blended figure.
- 03
Compare the watched buyer question count against the plan ceiling
GEO Growth watches 100 buyer questions and GEO Scale watches 300. If the client's category has outgrown the ceiling, flag the upgrade before adding questions, because unwatched questions produce no reporting evidence for the retainer.
- 04
Audit the answer-first pages published that period
GEO Growth schedules 20 pages a month and GEO Scale 40. Verify each page went live on the client's own site, not a staging URL, and that the answer appears in the first paragraph where the AI can lift it.
- 05
Review source citation coverage for the vertical
Check which review sites and directories the engines cited and whether the client is listed on each. Missing listings are the fastest lever on named-in-answer rate and belong in the delivery queue for the coming week.
- 06
Log movement against last week and write the client-facing summary
State the delta in named-in-answer rate, the questions that flipped to named, and the questions still unanswered. Keep the summary to the movement plus the next action so the retainer fee is justified by evidence, not activity.
- 07
Escalate any engine that has gone flat for three consecutive weeks
A single flat engine usually means the cited sources changed. Re-run the question research for that engine and re-check the citation list before the next reporting cycle.
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