As of 13 August 2026, AI can analyse your SEO performance.
This still needs a person who signs their name to it.
Can you do it?
15 minutesto a draft.
1 hourto something you’d act on.
Cost, all in£0
Skill neededpower-user
Who has to check ityou
What the alternative costsA no-code AI analytics tool such as Akkio can analyse business data, but its pricing is not specified here.
If this goes wrong: you misread a traffic change, prioritise the wrong SEO work and spend time or budget fixing a problem that was not the cause.
What to actually do
Hand it to a person
The route this page recommends
A person who owns the outcome does this end to end, worth it when the failure is dear.
Use a tool built for this
Second choiceDo it yourself
The distant thirdA chat interface, power-user skill, and roughly 1 hour until you can act on the result.
How to actually do it
- Open Google Search Console and export Performance data for the chosen date range and comparison period, including queries, pages, clicks, impressions, click-through rate and average position.
- Open GA4 and export the relevant organic-search landing-page, engagement and conversion data for the same periods, keeping the date ranges and attribution settings visible.
- Export ranking data from your rank tracker if you use one, then gather your sitemap, recent website or content changes, known outages and the business goals for organic search.
- Remove unnecessary personal or confidential data, label each file with its source and date range, and paste the tables and context into the prompt.
- Ask the model to separate measured findings, calculations, hypotheses and recommendations, and to identify missing data instead of filling gaps.
- Compare every reported figure and calculation with the original Search Console, GA4 and rank-tracker exports, then check whether the proposed causes match your change log and known technical events.
- Open the affected pages and Search Console reports, test the highest-priority issues, and record which actions you will implement, defer or reject with the evidence for each decision.
Prompt
Analyse the SEO performance data below for [WEBSITE OR BUSINESS] over [DATE RANGE], comparing it with [COMPARISON PERIOD]. Use only the supplied data and clearly label anything that cannot be established from it. Do not invent figures, search rankings, causes, conversions or Google updates. Start with a short executive summary, then provide: 1) organic clicks, impressions, click-through rate and average position trends; 2) the pages, queries and countries or devices driving change; 3) pages and queries losing performance; 4) technical or content hypotheses, ranked by evidence and confidence; 5) anomalies or data-quality limitations; 6) five prioritised actions with expected objective, required evidence, owner, effort and risk; and 7) a list of checks I should complete in Google Search Console, GA4 and the website before acting. Distinguish correlation from causation. Preserve the supplied figures and show the calculation for any derived metric. Data sources and notes: [PASTE EXPORTS, TABLES OR NOTES HERE]. Website changes during the period: [PASTE CHANGE LOG HERE]. Business goals and important landing pages: [PASTE CONTEXT HERE].
Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.
What it gets wrong
- AI cannot see current website conditions, crawl errors or ranking changes unless you provide a current export or connect an appropriate data source.
- AI cannot prove that a content or technical change caused a traffic movement from trend data alone.
- AI cannot know which commercial pages, audiences or products matter most without your business context.
- AI cannot reliably distinguish a tracking change, seasonal effect, algorithm change and competitor movement when the supplied data does not contain evidence for the distinction.
Even on a YES, the friction has a name: judgement under ambiguity, verification cost and real time truth.
How we scored this
Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.
| Axis | Score (0–2) |
|---|---|
| Output | 2 |
| Inputs | 2 |
| Verification | 1 |
| Liability | 1 |
| Effort delta | 2 |
| Total | 8 / 10 |
The methodology and its thresholds are published in full.
FAQ
- Can ChatGPT analyse my SEO data?
- Yes. Give it labelled exports from Google Search Console, GA4 and any rank tracker, and it can compare periods, find changes and draft a report. Check its calculations and treat explanations of causes as hypotheses unless your data supports them.
- What data do I need for an AI SEO analysis?
- Use Search Console performance exports, GA4 organic landing-page and conversion data, ranking data if available, your sitemap and a record of recent website changes. Include the comparison period and your business goals, because traffic alone does not show whether SEO performance improved.
- Can AI tell me why my Google rankings dropped?
- It can suggest and rank possible causes from the evidence you provide, such as a technical change, content change or change in query demand. It cannot prove the cause from rankings alone, so check Search Console, your website, analytics settings and change log before acting.
- Is AI SEO analysis accurate?
- The figures can be accurate when they are copied correctly from your source exports and the model shows its calculations. The interpretation is less certain: verify the data and test recommendations before changing important pages or spending money.
Nearby answers
Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.
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