USE CASE:
The careers page and page discovery
Read this if you need page discovery for the careers page and you would rather see the real options than a pitch. The tools we name are Mamba Labs Apify actors, priced per row, and Page Finder Extractor is the one pointed at the careers page.
The problem
Page discovery for the careers page stops being a lookup and becomes a project. The careers page sits at no fixed URL, because there is no convention and never was one, and page discovery has to work around it. Know this about the careers page before any page discovery: guessing the path works often enough to look reliable and fails silently when it does not. There are 4 runnable examples of page discovery for the careers page below.
The method
- Start with one of the careers page you already know, so a wrong page discovery answer is obvious rather than plausible.
- Run Page Finder Extractor across your list of the careers page, which carries 4 ready made setups for page discovery.
- Read ten rows of page discovery on the careers page by hand before you trust the rest of the list.
Traditional Search Tools
- A site search operator, for the careers page. Free, precise, and rate limited into uselessness past twenty companies.
- Google with a site operator. Free and precise. Fine for twenty companies, and rate limited into uselessness past that.
- Screaming Frog. Crawls a whole site and finds every page matching a pattern. Built for one site at a time rather than a list of hundreds.
- Guessing the URL. Try slash pricing. It works surprisingly often and fails silently, which is the problem.
- Search the site. A site search in Google with the term you want gets you there in one query per company. Reliable, and it is still one query per company.
Preconfigured tasks
A task is one of these actors with the inputs already filled in for a specific version of this job. Open one, swap in your own list, and run it without setting anything up from scratch.