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As of 13 August 2026, AI can analyse your UK website traffic.
This still needs a person who signs their name to it.
Can you do it?
15 minutesto a draft.
30 minutesto something you’d act on.
Cost, all in£0
Skill neededchat-fluent
Who has to check ityou
What the alternative costsA human analyst remains the alternative when the data is incomplete or the decisions are high-stakes; no comparable price is provided in the available tool data.
If this goes wrong: you mistake tracking noise or correlation for a marketing insight and spend time or budget responding to it.
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, chat-fluent skill, and roughly 30 minutes until you can act on the result.
How to actually do it
- Open your website analytics platform, such as GA4, and select a date range that answers the business question you want to investigate.
- Export the relevant report as CSV or XLSX, including the metrics and dimensions needed for the question, such as sessions, users, conversions, source, medium, device and landing page.
- Write down the metric definitions, conversion events, attribution setting, date range, any comparison period and known changes to campaigns, consent settings, tagging or the website.
- Remove individual identifiers, email addresses, full IP addresses and any other unnecessary personal data from the export before uploading it.
- Paste the supplied prompt into a chatbot, replace the bracketed sections with your business objective and export description, and attach or paste the cleaned data.
- Ask the model to produce the analysis and calculation table, then compare its totals, date ranges and percentage changes with the original analytics report.
- Check each proposed explanation against campaign records, website releases and tracking changes, and label unsupported explanations as hypotheses rather than findings.
- Send the checked findings to the relevant colleague or decision-maker with the source export and definitions attached.
Prompt
Analyse the UK website traffic data pasted or attached below. Treat the data as descriptive, not proof of causation. First state the date range, rows, columns, missing values and any apparent tracking or sampling limitations. Then report the main changes in users, sessions, views, engagement, conversions and conversion rate where those fields exist, comparing periods only when the periods are comparable. Break findings down by the available dimensions, such as channel, source, device, landing page, location and campaign. Show the calculation behind every percentage change and do not invent missing figures. Separate confirmed findings from hypotheses. For each hypothesis, list the additional evidence needed to test it. Flag unusual values, inconsistent definitions, duplicate rows and possible changes in tracking. Finish with a short list of practical next actions ranked by likely usefulness and ease of checking. Use UK English, pounds where the data contains pounds, and plain language. Do not identify individual visitors or infer sensitive characteristics. Ask concise questions before analysing if the file, metric definitions, date range or business objective is missing. Business objective: [insert objective]. Analytics platform and export description: [insert details]. Data: [paste or attach export]
Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.
What it gets wrong
- AI cannot access your analytics account, so you must export the correct report and supply its definitions.
- It cannot tell from traffic data alone whether a campaign, website change or outside event caused a change.
- It cannot reliably recognise a silent tagging, consent or attribution change without your implementation history.
- It cannot decide which traffic movement matters to your business without your objectives and commercial context.
- It can produce a polished explanation from incomplete data, so the original report remains the authority for totals.
Even on a YES, the friction has a name: verification cost, judgement under ambiguity and private data access.
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 Google Analytics data?
- Yes. Export the relevant GA4 report and give the model the metric definitions, date range, business objective and known tracking changes. It can calculate comparisons and suggest explanations, but you must check the figures against GA4.
- Can AI tell me why my website traffic went down?
- It can identify patterns and list plausible causes, such as a channel change or tracking problem. It cannot prove the cause from traffic data alone, so check the hypotheses against campaign records, website changes and tracking tests.
- Is it safe to upload my website analytics to AI?
- Upload a cleaned aggregate export and remove unnecessary identifiers before sharing it. Do not upload individual visitor records when totals and grouped reports answer the question.
- What data do I need to give AI to analyse my website traffic?
- Give it the export, date range, comparison period, metric definitions, dimensions, conversion definitions and your business question. Also record campaign, consent, tagging and website changes that could affect the numbers.
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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