Agent Traffic to a Spreadsheet Dashboard

export_agent_traffic gives you a CSV of raw crawl events — every hit from GPTBot, ClaudeBot, PerplexityBot, and other AI crawlers, with a timestamp, path, and status code. That’s exactly what you want for a dashboard and exactly what you don’t want to read row by row. This workflow has Claude do the export and the pivoting in one pass, so you land on a chart, not a CSV.

Tools used in this workflow

Tool	Required?	Used for
Scrunch MCP	Required	Exporting the agent traffic CSV
Google Sheets MCP or Excel MCP	Required (choose one)	Building the pivoted, chartable workbook

Google Sheets
Excel

Replace the bracketed values, then paste the whole thing into Claude.

For [site domain] in Scrunch, export the last [30/60/90] days of agent traffic and turn it into a Google Sheets dashboard.

Step 1 — Export the data:
Export agent traffic for [site domain] from [start date] to [end date], aggregated by day.

Step 2 — Build the raw data tab:
Create a new Google Sheet called "[site domain] Agent Traffic — [month/year]". Add a "Raw Export" tab and load the exported rows: date, bot name, path, hit count.

Step 3 — Build the pivot:
On a new "By Bot" tab, pivot the raw data into: one row per date, one column per bot (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and any others present), with hit count as the value. Add a Total column.

Step 4 — Chart it:
Create a stacked area chart on a "Chart" tab plotting hit count over date, broken out by bot, using the "By Bot" tab as the source.

Step 5 — Summarize:
Which bot crawls [site domain] most? Is total crawl volume trending up or down over the period? Are there any days with an unusual spike or drop worth flagging?

What you get: A three-tab spreadsheet — raw export, a per-bot pivot, and a stacked area chart — that turns a flat CSV into something you can actually read crawl trends off of at a glance.

Replace the bracketed values, then paste the whole thing into Claude.

For [site domain] in Scrunch, export the last [30/60/90] days of agent traffic and turn it into an Excel dashboard.

Step 1 — Export the data:
Export agent traffic for [site domain] from [start date] to [end date], aggregated by day.

Step 2 — Build the raw data sheet:
Create a new workbook called "[site domain] Agent Traffic — [month/year]". Add a "Raw Export" worksheet and load the exported rows: date, bot name, path, hit count.

Step 3 — Build the pivot:
On a new "By Bot" worksheet, pivot the raw data into: one row per date, one column per bot (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and any others present), with hit count as the value. Add a Total column.

Step 4 — Chart it:
Create a stacked area chart on its own worksheet plotting hit count over date, broken out by bot, using the "By Bot" sheet as the source.

Step 5 — Summarize:
Which bot crawls [site domain] most? Is total crawl volume trending up or down over the period? Are there any days with an unusual spike or drop worth flagging?

What you get: A three-sheet workbook — raw export, a per-bot pivot, and a stacked area chart — that turns a flat CSV into something you can actually read crawl trends off of at a glance.

Tips

Correlating crawl volume with presence gains

If a bot’s crawl volume to a specific path jumped recently, check that page’s citation rate in Scrunch for the same window — a crawl spike followed by a citation increase is a strong signal that the crawl directly fed a retrieval or indexing update.

Filtering to specific paths

Add “filtered to paths starting with [/blog/ or /docs/]” to Step 1 if you only care about crawl activity on a specific site section rather than the whole domain.

Spotting bots that aren't crawling you at all

If a bot you expect to see (e.g. PerplexityBot) shows zero or near-zero hits across the whole period, that’s worth investigating on its own — check robots.txt isn’t blocking it and that the relevant pages are reachable without JavaScript rendering.

Re-running this monthly

Keep the same workbook and ask Claude to append the new month’s export as additional rows on “Raw Export” rather than creating a new file each time — the pivot and chart will pick up the extended range automatically if they’re built off the full sheet rather than a fixed row range.

Measure AI Visibility's Impact on Traffic

Pair crawl activity with Google Analytics to see whether crawl attention is turning into referral traffic.

Which Cited Pages Actually Convert

Go one step further and check whether the pages getting crawled are the same ones driving citations and conversions.

​Tips

Measure AI Visibility's Impact on Traffic

Which Cited Pages Actually Convert

Tips