How to Export Prompt Data in AmICited

Sometimes you need a prompt’s data outside AmICited, for a spreadsheet analysis, a client report, or to share with a teammate. The Export button pulls that prompt’s data out in one click.

Quick Steps

• Open a prompt detail page and set the date range, engines, and country filters to the scope you want.
• Click Export in the top-right action bar to generate a downloadable file of that prompt’s data.
• The file reflects citation status, rank position, source URLs, and competitor mentions for the filtered scope.
• Open it in a spreadsheet for pivot analysis, or drop it straight into a report.
• Use export for deeper analysis, stakeholder reporting, and point-in-time archiving.

What is prompt data, and why export it?

A “prompt” in generative engine optimization (GEO) is a specific question or query that a real customer might type into ChatGPT, Perplexity, Gemini, or Google AI Overviews, things like “best project management software for remote teams” or “who are the top payroll providers in Ireland.” Prompt tracking is the practice of running the same prompt on a schedule across AI engines and recording what comes back: whether your brand is mentioned, where it ranks in the answer, which sources the AI cited, and what competitors showed up alongside you. Each tracked prompt accumulates its own history of AI citations , rank positions, and source URLs over time, and that history is the raw material behind every chart AmICited shows you.

“Prompt data” simply means that underlying record: every answer an AI engine has given for one prompt, across every date, model, and country you monitor it in. It’s the evidence layer beneath aggregate metrics like share of voice or your overall AI visibility score : those numbers are calculated from thousands of individual prompt-and-answer pairs, and exporting lets you see the pairs themselves rather than just the summary.

This distinction between summary metrics and underlying data matters more in AI search than it did in traditional SEO. A classic keyword rank tracker gives you one number per keyword per day, position 1 through 100, full stop. A prompt, by contrast, produces a full generated answer each time it’s run: a paragraph of text, a list of cited sources, and sometimes a shifting cast of competitors mentioned alongside you, none of which is fully captured by a single “cited: yes/no” flag. That richness is exactly why exporting is useful. A dashboard can summarize it, but only the underlying rows let you see, for example, that you’re cited consistently on Perplexity but only intermittently in Google AI Overviews, or that a specific competitor started appearing in your answers the same week they published a new comparison page.

Exporting matters because dashboards are built for scanning, not for the kind of ad hoc slicing that real analysis requires. You might want to compare citation rates between ChatGPT and Gemini for a single prompt, chart a competitor’s rank trend by hand, or hand a client the raw numbers behind a claim in your monthly report. None of that is a dashboard feature: it’s a spreadsheet or BI tool problem, and it starts with getting the data out. That’s what the Export button is for: it takes whatever a prompt’s detail page is currently showing and turns it into a file you can open anywhere.

Where to find it

Export is the button in the top-right action bar of any prompt detail page, next to Generate article and Compare a URL. You’ll land on a prompt detail page whenever you click into an individual prompt from your prompt list, a dashboard chart, or search; the export option travels with you wherever that prompt shows up.

How to use it

1. Scope it first. Adjust the page filters (date range, engines, country) so the export contains exactly the window you care about. Because the export is filter-aware, a broad “last 90 days, all engines” view and a narrow “last 7 days, ChatGPT only” view of the same prompt produce two very different files, so decide which one answers your question before you click.
2. Click Export. AmICited generates a downloadable file of the prompt’s data, built from whatever is currently on screen: citation status, rank position, source URLs, and competitor mentions for each date and engine in scope.
3. Open it in your tool of choice, a spreadsheet for pivot analysis, or drop it straight into a report.

What it’s good for

• Deeper analysis: slice and pivot the data in a spreadsheet in ways the dashboard doesn’t. This is the natural next step after you’ve used AmICited to find which prompts trigger AI to mention your brand : once you know which prompts matter, exporting lets you dig into exactly how your citations behave on them, engine by engine.
• Reporting: hand stakeholders or clients the underlying numbers behind your AI-visibility story, rather than asking them to trust a screenshot. This is especially useful if you’re assembling recurring AI visibility reports for stakeholders , where a finance or marketing lead wants to see the source data, not just the summary slide.
• Archiving: keep a point-in-time snapshot of a prompt’s performance to compare against later, which is useful before a site migration, a content refresh, or a competitor’s product launch that might shift how AI engines describe the category.

Working with the exported data

Once the file is in a spreadsheet, a few habits make the export more useful. First, treat each row as a single answer for a single date and engine; don’t average across engines until you’ve looked at them separately, since ChatGPT, Perplexity, Gemini, and AI Overviews frequently diverge on the same prompt even in the same week. Second, if you’re building a trend chart, sort by date first and engine second so gaps in citation (days where your brand didn’t appear at all) are visible rather than silently smoothed over by an average. Third, when you’re comparing competitors named in the same answers, keep the source URLs column intact: it tells you not just that you were cited, but where from, which is often the more actionable finding.

If you’re regularly exporting the same handful of high-value prompts, it’s worth building a lightweight prompt library so exports stay consistent from month to month (the same prompt set, the same filters, the same file structure) rather than re-scoping from scratch every time. For teams that need this on a recurring basis without a person clicking Export each cycle, pairing manual exports with automating reports with AI visibility APIs is the natural next step: the API pulls the same underlying prompt data programmatically, so recurring dashboards and client reports update themselves.

When to use export versus the dashboard

Export isn’t a replacement for AmICited’s dashboards; it’s a complement for the moments the dashboards can’t fully serve. If you want a fast read on how a prompt or a whole account is trending, the dashboard and the underlying AI rank tracker are built for exactly that: visual, filterable, no download required. Reach for export when you need to leave AmICited: feeding a client’s existing reporting template, running a statistical comparison a chart can’t show, or archiving a baseline before a change you’re about to make. Agencies managing several client accounts tend to lean on export most heavily, since portfolio-wide reporting often has to match a template the client already expects; if that’s your situation, it’s worth seeing how AmICited’s agency tooling handles multi-client reporting more broadly.

For programmatic or large-scale pulls, combine exports across your priority prompts, or pair this with the dashboard views for the aggregate picture. Export is most valuable once you already know which prompts you’re tracking and why; if you’re still building out that list, start with AmICited’s broader AI visibility tooling to identify the prompts, engines, and competitors worth watching, then use export to turn the ones that matter into the spreadsheets, reports, and archives your team actually works from.