URL enrichment is the practice of turning a list of web addresses into usable data: you hand a tool a column of URLs, it fetches each page, extracts the values you want, and writes them back into rows and columns. The underlying technique is web scraping, and the thing doing the fetching is a scraper. What makes it enrichment rather than a one-off scrape is the shape of the job: the URLs are already rows in your list, and the output lands beside them as page text, a company description, a price, a job title.
How URL enrichment works
The engine does three things for every URL. It fetches the page, sending an HTTP request the way a browser would. It parses the response, locating the data within the HTML, sometimes after rendering JavaScript so the page looks the way a human would see it. It extracts and stores the chosen values into a structured output. A good engine also handles the messy reality of the web: retrying a slow page, backing off when a site rate-limits, and skipping a dead link without crashing the whole run.
URL enrichment vs the native import functions
Google Sheets ships with IMPORTXML and IMPORTHTML, which are lightweight scrapers for static pages. They read the raw HTML a server returns, so they cannot see content that JavaScript builds in the browser, and they cap out at roughly 50 calls per sheet. A dedicated engine runs the requests on a server outside the spreadsheet, renders dynamic pages, retries failures, and scales to thousands of URLs without hitting the six-minute Apps Script limit.
URL enrichment in ReplyLabs
ReplyLabs runs URL enrichment from inside Google Sheets, in a feature called Enrich. You select a column of URLs, pick an engine, and results stream back into a new column. Only URLs that return data are charged, and the in-house engine auto-falls back to another when a page resists. Retrieved page text is most useful as input to an AI step, which is why Enrich and AI usually run together.