Filter an export by columns
A collected table is almost always wider than the job needs: rows without a contact, the wrong region, the wrong price. The usual answer is to run the collection again with different settings — and pay twice. Here the filter works on the finished file: pick your completed task, and the engine reads that table's own columns and keeps only the rows that match.
Features
- Columns come from your own export — every tool has its own set
- Seven conditions: filled, empty, contains, does not contain, equals, greater, less
- Up to three conditions at once, e.g. "has Email" and "salary above 40,000"
- You see how many rows each condition removed, not just the total
- The result is a separate file; the original task stays untouched
- Spends no row limit and no collection accounts: the source is not queried again
How it works
Pick a finished export
Take a table you have already collected — no need to re-run the source.
Set conditions on the columns
Columns come from your own export — each tool has its own set.
Apply the filter
Rows are dropped instantly, without spending plan limits or the account pool.
Download the result
The same Excel format with the same columns, saveable as a separate base.
FAQ
Does filtering consume my plan's rows?
No. The filter works on a file you already received and paid for: the source is not queried again and no collection accounts are used. You can filter the same export as many times as you like.
How is this different from filtering in Excel?
The result stays a service task: it appears in your history, exports in the same format with the same columns, and can be saved to CRM or put on Monitoring. The status also states how many rows each condition removed.
What if no row matches?
You will be told exactly that, with a suggestion to relax or remove a condition. We never present an empty result as a successful collection.
Can I filter the export of any tool?
Yes — any completed task that has an export file: job postings, companies, products, audiences, new buildings. The conditions are the same; the columns are the ones present in that particular table.
How do I drop rows without a phone or email?
Use the "empty" and "filled" conditions — that is exactly what they are for. A common case: keep only companies with a phone so the list is ready for calls.