Highlights
Run enrichments from the table and follow progress live
Enrichment status columns are now active controls, not just a record of the last result. Hover an empty or completed status cell to run the enrichment for that row, or select a range and choose Run on N items from the floating menu.
While the run is working, statuses, counts, and errors update in the table. If you switch tabs and come back, Datablist resynchronizes the progress. You can retry a failed row or run an enrichment on a small selection without reopening the full configuration flow.
Improvements
Broader profile coverage in LinkedIn People Profile Scraper
The LinkedIn People Profile Scraper has an additional lookup path for profiles that are missing or stale in the usual flow.
When a profile is available, the enrichment maps it to the same Datablist outputs—including name, headline, location, current role, experience, education, languages, and profile URL—so your existing mappings continue to work. This improves coverage when you enrich a mixed list of LinkedIn profile URLs.
Company domain finder avoids directory and marketplace pages
Find Company domains from Company names is better at separating an official company website from directories, marketplaces, review sites, and translation pages that happen to rank for the same name.
For example, a search for a local company is less likely to return its listing on a business directory. The matcher also handles normal website paths such as /en/about-us more carefully, so a valid official site is not rejected simply because the result is not the homepage.
Data sources now map all matching output columns at once
When a data source returned several fields that already existed in your collection, Datablist could auto-map only part of them because mappings were applied one by one.
Output auto-mapping now applies the full set in one step. If a remote CSV contains Name, Website, and Country and those columns already exist, all three are mapped together; you can review the mapping and start the import without reconnecting missing fields.
Detect Language from a Text now returns confidence
Detect Language from a Text now adds a Language Confidence output alongside the language name and ISO code. The values—High, Medium, Low, or Very Low—help you decide which rows can move forward automatically and which need review.
Detection also checks several parts of long text instead of relying only on the opening characters, and it rejects strings made only of noise such as numbers and punctuation. For example, you can route high-confidence French support messages to a translation workflow while filtering uncertain rows first.
More sources and enrichments available on the Free plan
We opened more of the enrichment catalogue to Free plan users. This includes List URLs from a Sitemap file, Import from one or many remote CSV or JSON files, LinkedIn People Profile Scraper, Find Company domains from Company names, and Detect Language from a Text, among others.
You can now test a complete workflow before upgrading: import one remote file or a sitemap, enrich a sample, review the output, and export the collection. Credit-based tools still consume credits, and remote file import is limited to one URL at a time on the Free plan.
New template: Find LinkedIn School Pages with Google Search
We added Find LinkedIn School Pages with Google Search to the template catalogue.
Start with a column of school names and the template prepares a site-specific query for each row. For example, HEC Paris becomes a search focused on LinkedIn school pages, so you can build a clean list of school URLs without writing the query yourself.
Renewal date, payment method, and billing address in one place
Account billing now shows when your plan renews, the payment method on file, and your billing address once an invoice exists.
Before this update, you often had to leave Datablist or contact us to confirm those details. Now you can check the essentials from Billing and open support from the same account area when something needs attention.
Safer credit checks for concurrent LinkedIn Search Scraper runs
Several long-running LinkedIn Search Scraper jobs could pass the balance check at the same time because each run saw credits already spent, but not credits committed to work still in progress.
Datablist now reserves the estimated credits for an unfinished search and releases the reservation when results arrive. If you start two large searches at once, the second run sees the credits already committed to the first, reducing failed jobs and unexpected credit usage.
Follow our guide to scraping LinkedIn profile details to prepare your inputs and map the returned fields.