Highlights
Turn cross-collection matches into usable result files
Cross-collection matching previously offered one detailed group download, which was useful for inspection but awkward for the next business step. The new Result files workspace creates a CSV for the exact outcome you need: Matched records, Needs-review records, Unmatched records, a Match crosswalk, or Detailed match groups.
For example, compare an event-attendee list with your CRM, select the attendee list as the source, download Unmatched records for net-new leads, then use the crosswalk to retain every attendee-to-CRM relationship. Row-based files keep the strongest candidate and include confidence and match reasons.
Improvements
Broader coverage in LinkedIn People Profile Scraper
LinkedIn People Profile Scraper now has an additional lookup path for profiles that do not require freshly fetched pictures. That gives cached and less commonly indexed profiles another chance to return structured data before the enrichment falls back or reports no result.
A LinkedIn URL that previously returned nothing may now produce the same mapped fields—such as full name, headline, location, current company, experience, education, and languages—without changing your configuration. Picture-dependent runs kept their existing lookup path at this stage.
Import jobs from Indeed search URLs
Indeed Jobs Scraper used to require rebuilding a search from keywords, locations, and country inside Datablist. You can now paste one or more public Indeed Job Search URLs and import the listings from searches you already refined on Indeed. Keyword-and-location searches remain available as an alternative.
Before launching, Datablist shows the estimated credit requirement from the number of URLs—or the number of keyword × location combinations—and the result limit. For example, two keywords across two cities create four searches, so you can see and adjust the maximum cost before the run starts.
Safer matches in Find Company domains from Company names
Find Company domains from Company names now compares normalized company identities across more candidate data while applying stricter website ownership rules. It rejects a hosted page when the domain belongs to the platform rather than the company and can use a row's country to separate businesses with the same name.
For example, a vacation rental listed on airbnb.com/rooms/... is no longer accepted as if Airbnb were the rental company's own website. For an ambiguous name such as Notion, adding the country helps prioritize the matching local company, and unreachable candidates no longer displace a verified live site.
Waterfall Email Finder waits for slow lookups without getting stuck
Some email lookups finish asynchronously. Waterfall Email Finder and Waterfall Personal Email Finder now keep polling those searches until they reach a final result, while using clear time limits and fallback behavior when a search takes too long.
For example, if a work-email lookup is still processing, Datablist waits for its final found/not-found answer instead of treating the intermediate state as the result. A timed-out path does not hold the whole run indefinitely; the waterfall can continue and avoids repeating the same lookup unnecessarily.
Follow our guide to scraping Indeed jobs for lead generation to build a job-based prospecting workflow.