Daily website scraper that builds a Google Sheet history

Every morning at 6am (keep the schedule configurable), scrape a structured listing page and append each item as a new row to a Google Sheet so I build a dated history automatically. This is a deterministic capture with no interpretation or summarization: fixed selectors go in, rows come out, one run per day, and the sheet accumulates a clean time series.

Use Browserless Scrape Elements to extract structured JSON from the fully rendered target page using CSS selectors. Make the target URL configurable, and define a selector-to-column map so each field maps to a named column, for example product name, price, and availability, or the title, location, and date of a job or event listing. Because Browserless renders JavaScript, selector-based extraction works on dynamic sites that a plain HTTP fetch would miss. Pull one record per item on the page.

If Scrape Elements returns no matching elements, skip the run and write nothing so the sheet never logs empty or junk rows. Only continue to the Google Sheets step when there is at least one matched item.

For each matched item, use Google Sheets Append Values to add a new row after the last row of the destination sheet. Map each scraped field to its column following the selector-to-column map, and include a run-date column set to the date the workflow ran. Append only, never overwrite existing rows, so past records stay intact and history accrues.

Keep the target URL, the selector-to-column map, the schedule, and the destination spreadsheet and sheet configurable. The sheet's columns should match the selector map plus the run-date column.