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Doing the loop once by hand is fine for a pilot. For live programmes you want it to run on its own. Workflows chain the steps together and run them on a schedule, so a fresh, optimised decision is ready whenever you need it.

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What a workflow can chain

Sync data

Pull the latest from your batch data sources before anything else runs.

Train / retrain

Refresh a model on the newest data so it doesn’t drift.

Generate predictions

Score the current population with the up-to-date model.

Export

Deliver the resulting decision to your connected tools.

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A typical recurring campaign

1

Sync the latest supporter & gift data

2

Retrain the model so it reflects recent behaviour

3

Score the eligible population

4

Produce the optimised decision

5

Export it to your campaign tool

Scheduled to run before each appeal, this means your team always works from a current, optimised list — with no manual clicks.
Screenshot to add — the workflow builder showing a chained sync → train → score → export pipeline and its schedule.
Streaming data sources flow continuously and aren’t scheduled; workflows are for batch steps. See Connect a data source for the batch vs streaming distinction.

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Keeping an eye on it

Every workflow run — and each step within it — is tracked on the Monitoring page, colour-coded by success, in-progress or failure, so you can confirm the pipeline ran and catch problems early.