The data check — only send records that meet your conditions

The data check decides which records a pipeline is allowed to send. It uses the same conditions editor as a list's own triggers — field · operator · value, grouped with AND and OR — plus whatever the target itself always needs. A record that doesn't meet it waits under Entries as Check instead of being sent.

Where to find it#

Open a pipeline, go to the Flow tab and click the pencil on Data check. With nothing set, it reads "None – every contact is sent."

Building conditions#

Add conditions the same way as in a list trigger: pick a field, an operator and a value, then AND condition to add another requirement to the same group or OR group for an alternative set of conditions. A pipeline can check:

• Contact fields — the record's content types (e-mail, first name, company, job title, country …), since a pipeline takes records from any list and from Saved, never a specific list's own columns.
• E-mail verification — whether the address is valid, business, catch-all, disposable and so on.
• Pipeline marks — whether the record is already waiting in, or was already sent to, another pipeline.

The target's own requirements#

Some targets always need a field, shown as a fixed tag above your conditions — for example HubSpot always needs an e-mail address. These apply on top of whatever conditions you add and can't be removed.

What happens to records that don't meet it#

They wait under Entries with the status Check: "Missing: …" names an empty required field, "Not met: …" names an unmet condition. Nothing is sent and nothing is written to the History until the record changes. Enrich or edit it, then click Send again (or, on an automatic pipeline, it is rechecked by itself on the next run) — it passes if it now meets every condition.

Preview while editing#

While you edit the conditions, a line below them shows "x of y waiting entries meet this" so you can see the effect before saving. With more than 500 entries waiting, only the first 500 are checked for the preview; saving still applies the check to every entry.

Older pipelines#

A pipeline set up before this conditions editor existed shows its old "required fields" as "is not empty" conditions automatically — nothing changes in what it sends, and saving it once converts it to the new form.

Related topics: send-records-to-a-pipeline · pipelines-overview · automatic-release · pipeline-marks · list-triggers.

FAQ#

What is a pipeline's data check?#

It's a set of conditions — field, operator, value, grouped with AND and OR — that a record must meet before a pipeline sends it. Set it under Data check on the pipeline's Flow tab; without any conditions, every record is sent.

What fields can a pipeline's data check look at?#

The record's contact fields (e-mail, name, company, job title, country …), its e-mail verification result, and whether it's already in or was already sent to another pipeline. It can't check a specific list's own columns or statuses, since one pipeline can take records from any list.

Why is my record stuck with the status "Check"?#

It doesn't meet the pipeline's data check yet — "Missing: …" names an empty required field, "Not met: …" names an unmet condition. Fill or enrich the record and click Send again; it's rechecked and goes out once it passes.

Does a target like HubSpot add its own requirement to the data check?#

Yes, some targets always need a field — HubSpot and the other CRMs always need an e-mail address — shown as a fixed tag above your own conditions. It applies on top of whatever you add and can't be turned off.

How do I combine several conditions in a data check?#

Conditions in the same group all have to be true (AND); add another group with OR group for an alternative set of conditions. For example "country is Germany AND job title contains Head" OR "seniority is VP".

Can I see how many waiting entries would pass before I save the data check?#

Yes, a line under the conditions shows "x of y waiting entries meet this" as you edit, checking up to the first 500 waiting entries. Save applies the check to every entry, not just the ones previewed.

When is a held-back record checked again?#

On a manual pipeline, when someone clicks Send again. On an automatic pipeline, it's rechecked by itself on every run, so a record that becomes complete later goes out without anyone clicking anything.

What happened to the old "required fields" setting?#

It still works exactly as before, shown as "is not empty" conditions in the same editor. Nothing about what the pipeline sends changes; saving the pipeline once converts it to the new form.