An AI visibility report does not change performance by itself. It shows mentions, sources, competitors, and Share of Voice, but it does not decide which actions should come first. The gap appears when the report is complete but there is still no AI search optimization plan.
This guide shows how to run a ChatGPT visibility audit, assign findings to SEO, content, and PR, and turn them into one prioritized generative engine optimization strategy for the quarter.
What the report needs before you can turn it into a plan
Before looking for insights, you should make sure that the report contains enough material. If it contains only "mentions for the period", the plan cannot be collected.
The working minimum that should be in the report is:
| Section | What does | show Why |
|---|---|---|
| Requests | List of requests that have been monitored | Without this, it is not clear in which scenarios you are present |
| Model responses | Raw response texts for each query and each model | Allows you to see the wording, context, and logic of the |
| Share of Voice | How often your brand is mentioned compared to competitors | Basis for prioritizing |
| Source map | URLs and domains that have cited models | Provides material for SEO and PR |
| Competitive map | Who consistently appears next to you and instead of you | Determines the reference group |
| Query coverage | Where we appear and where we don't | Detects gaps in topics |
| Date and model | When and where the measurement was taken | Required for comparison with the next measurement |
If any of this is missing, we start not with a plan, but with the completion of the report.
Read the four-layer report
The first step is not to "do everything at once", but to lay down the report into layers and look at each one separately.
- Requests. In which topics the brand is present, in which it is a failure.
- Model responses. What wording does AI use, what associations it has already collected.
- Sources. What are the answers based on, which domains to work with separately.
- Competitors. Who is repeated and due to what signals.
Separated layers are a prerequisite for an honest diagnosis. If you look at the "report as a whole", one of two conclusions is almost always drawn: either "we need more content" or "we need more PR". Both are too wide to work with.
Categorize problems, not just fix them
The same "brand does not appear" situation can have four different roots. And the solutions are different for everyone.
| Problem type | What does the report look like | Where do we go for a solution |
|---|---|---|
| Content | There are no pages that close a specific intent (comparison, FAQ, guide) | Content team |
| Structural | The pages are there, but the AI "doesn't get to" them or doesn't perceive them as relevant | SEO + technical team |
| Reputational (external) | The answers cite media, ratings, catalogs — and your brand is not there | PR + partnership |
| Positioning | The model cannot briefly explain who you are for and what your role is in the category | Marketing + Positioning |
Before writing problems, put a type next to each insight from the report. This immediately removes half of the "unnecessary" actions.
Base conclusions on recurring patterns rather than a single run. At minimum, repeat the check with another wording and another model. One measurement is a hypothesis, not a diagnosis.
How to translate insights into SEO tasks
An SEO block in the plan is needed when structural failures are visible: pages exist, but are either not cited or do not cover the desired intent.
Typical SEO tasks from the report:
- Create new pages for category queries, where the answers fail.
- Finalize the pages of services or products: a clear structure, response to a request, schema.org markup (
Product,Service,FAQPage,BreadcrumbList). - Expanding FAQ blocks on cited pages is the fastest way to increase the number of "fragments" suitable for citation.
- Check the availability of the site for AI crawlers (
GPTBot,ClaudeBot,Google-Extended,PerplexityBot) in robots.txt and CDN. - Update titles, descriptions, internal linking on pages that models already cite.
- Review canonical URLs. If AI cites a secondary version instead of the canonical page, investigate the technical and content signals.
The format of the task here should sound like this: "refresh the /service-x page: add a comparison block with alternatives, add a FAQ for 6 questions, set a FAQPage schema". Don't "boost SEO".
How to translate insights into content tasks
A content block appears where models simply have nothing to cite in your niche — and competitors do.
Signals for content tasks:
- AI cites competitors' explanatory pages ("what is...", "how it works...", "how is it different...").
- Comparisons on third-party sites, not yours, constantly appear in the answers.
- The brand is mentioned in a narrow context — and there are no materials that would expand its role.
- There is a demand for commercial queries, but there is no content for the scenarios of choice.
Typical content tasks:
- Create a series of explanatory articles for category demand.
- Make your own comparisons "X vs Y" - tabular, with selection criteria, honestly with pros and cons.
- Write industry cases with specific figures (budget, deadline, result).
- Gather a glossary of industry terms — this often becomes a cited source.
- Update old materials: dates, numbers, screenshots, links to recent research.
How to translate insights into PR tasks
PR is needed when the report shows: models consistently quote external platforms that do not have a brand or it is poorly presented.
Typical PR tasks:
- Expert columns in industry media on topics where there is a failure in answers.
- Applications for inclusion in ratings and selections (Clutch, G2, profile ratings, annual selections of industry media).
- Working with reviews and cases on platforms cited by AI in your niche.
- Participation in market research as a speaker or data source.
- Podcasts and YouTube reviews — transcripts are indexed and included in citations.
- Working with Wikipedia (if the brand meets the notability criteria) is a long but very influential signal.
The PR task should be specific: "to get into the annual AIN selection of automation services X", and not "to strengthen the presence in the media".
How to Prioritize: ICE Framework for AI visibility
When the list of tasks is already collected, the fastest way not to get scattered is to evaluate each one according to three parameters. Adapted version of ICE for AI visibility:
| Parameter | What do we evaluate | Scale |
|---|---|---|
| Impact | How many queries and how many models will this problem close | 1–10 |
| Confidence | How confident are you that the action will actually affect the mentions/quotes | 1-10 |
| Ease | How quickly can be implemented with existing resources | 1-10 |
The total provides a rough priority. Move the first 3-5 problems into the active plan and keep the rest in the backlog for review after the next measurement period.
There is another useful criterion - the effect on recurring patterns. A task that closes 8 requests at once is almost always more important than a task that closes one, even if the second one is done faster.
Build one plan, not three
A common mistake is to break down tasks separately by SEO, content, and PR, give them to three teams, and come back in a quarter. After a month, it turns out that the tasks are duplicated or contradict each other.
The work plan looks like a single sequence:
- Technical edits on the site (access for AI crawlers, schema, canonical URLs).
- Refinement of existing pages that are already cited or have a chance.
- Creating new content for identified failures.
- PR activities and work with external sources.
- Checkpoint: repeat the measurement after 4-6 weeks.
Consistency is important: there is no point in PR on a site that is unfinished and closed from AI bots.
What a well-defined task looks like
Weak staging:
- "Strengthen the content".
- "Do PR".
- "Improve visibility".
Strong formulation (the same task, but understandable to the team):
- "Create 3 explanatory articles for the queries "how to choose a CRM", "what is a pipeline", "CRM vs ERP" — by June 5. Expected effect: appearance in category queries ChatGPT and Perplexity."
- "Update /services/crm-implementation: add an FAQ of 8 questions, add a comparison table with 4 alternatives, add a schema FAQPage — by May 22."
- "Apply to the annual selection of AIN CRM solutions, provide a case with numbers for client X — by June 1."
- "Repeat the 24 core prompts in ChatGPT, Gemini, Claude, and Perplexity on June 15; compare share of voice with May 1."
The difference is in the specifics. The team should be clear about what to do, to what date and by what criterion to measure.
Checkpoints and Rhythm of Verification
AI visibility changes more slowly than positions on Google, but faster than brand metrics. Working rhythm:
- Baseline — at the start, before any actions.
- Control measurement - 4-6 weeks after the first wave of changes.
- Quarterly review - full report, prompt-pool review, and competitor reference-group update.
- Reactive measurement - after major model changes such as a ChatGPT release, Gemini update, or AI Overviews change.
There is no point in looking at "weekly fluctuations" between checkpoints—it's noise.
Common mistakes when making a plan
- Build a plan from one measurement. Without repeatability, the conclusions are weak.
- Close everything at once. Better 3 closed problems than 15 started ones.
- Ignore positioning. If the report shows that the model "doesn't understand who you are for," no SEO fix will close it.
- Act without a checkpoint. Without a second measurement, the team cannot tell whether the work changed the pattern.
- Confuse traffic and mentions. A page can give traffic, but not be cited by AI — and vice versa.
Frequently Asked Questions
How many tasks can be realistically closed in a quarter? Usually, 5-10 priorities are an honest horizon. More — either partially unfocused, or the team has the experience and resources for streaming work.
Is it possible to turn a report into a plan without the participation of SEO/PR teams? Technically, yes, but the quality of the staging will drop. It is better to involve people who will actually do tasks at the plan stage — they make the right clarifications.
How do you know if the plan "worked"? Not just one metric, but a shift in several: the share of voice has increased, mentions have appeared in failed queries, your domain has appeared in citations where it did not exist, the competitive map has shifted.
Do I need to redo the plan if the models have been updated? The entire plan does not need to restart, but a control measurement is necessary. Major model releases can change both answer behavior and cited sources.
What else to read
- How to Analyze AI-Based Sources
- How to Understand Why AI Recommends Competitors
- Which pages of the site are most often included in AI responses
- What Is AI Visibility And Why Businesses Are Not Enough Anymore SEO
How we do it in VYDAI
VYDAI structures the report so the plan follows from the evidence. For each prompt, you can see which models mention the brand, which URLs and domains they cite, which competitors appear beside it, and how share of voice changes between measurement periods. Views by prompt, model, source, and competitor provide the inputs for the action plan.
If you want to see how the report looks on your queries and competitors, you can create an account or see demo. The decision on which tasks to take on and in what order is yours; We will be there and show the logic.
