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A subject line decides whether the email gets opened at all. To learn which of two works better on your list, send each to a comparable group and compare. Brew does this with a one-off flow: a manual-audience automation with a Percentage split. Set to 50/50, it sends about half the audience subject A and half subject B. Each path has its own numbers.
Before you start. You need a verified sending domain and a finished email. You also need a saved audience of opted-in contacts.
Every marketing recipient must have opted in to hear from you. Importing or syncing contact data into Brew is not permission to email it. See What You Can Send.

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1. Make Two Copies of the Email

Open the email on the canvas and clone it from the toolbar. Keep the body identical. The subject line should be the only difference, or you won’t know which change moved the result. Two copies give each path its own row in analytics. Name them so you can tell them apart, such as Launch, subject A and Launch, subject B.

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2. Generate the Flow

Open Home and describe the test:
Brew opens the flow with the trigger, the split, and both sends. Click each Send Email node and confirm it sends the right copy with the right subject. If the trigger isn’t set to your audience yet, click it and use Change trigger.

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3. Test Both Paths

Click Test automation and fire a test to your own address. A test sends you down one path only, so check that subject. Then send a test of the other copy with its subject.

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4. Run It

Check the contact count on the trigger node, then launch the run with Run now or Schedule. The automation shows Sending while the run is in flight and Sent when it completes. Skip Gradual send for a test. Batches that go out hours apart make the two paths harder to compare.

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5. Read the Result

Wait a day or two, then open the automation in analytics. Email steps lists both copies, each with its own sent, opened, and clicked. Compare rates, not raw counts, since the two paths rarely get exactly the same number of sends:
  • Opens are the subject line’s direct effect, but they overcount. Apple Mail Privacy Protection and other privacy features open mail automatically, and Brew can’t filter every one. See Key Metrics.
  • Clicks are a stronger signal. Someone who clicked read the email.
A small audience gives noisy results. If A and B differ by a point or two, call it a tie and test again later. A difference that repeats across sends is worth acting on.

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6. Use What You Learned

A percentage split doesn’t pick a winner or send it to the rest of the list. Take the lesson to your next send instead: the shorter subject, the question, the number in the first word. The flow stays in your Automations list. For the next test, swap in new copies and subjects in chat, and run it again. Each run keeps its own history.

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From an Agent or Code

Over MCP:
  • clone_email copies the design exactly, without AI.
  • save_automation saves the flow: a manual-audience trigger on the saved audienceId, a split node with mode: "percentage" and leftPercentage: 50, and one send node per path. Each send node pins its own design and subject.
  • test_automation runs one path. Pass scenario: { splits: [{ nodeId: "<split node id>", branch: "left" }] }, then again with "right", to test each one. Use the node id stored on the saved flow.
  • run_automation with dryRun: true returns the recipient count. The real launch returns a confirmation request on OAuth and organization connections. See Confirmation.
Over the API the launch is POST /v1/automations/{automationId}/run with an Idempotency-Key. For the result, GET /v1/analytics/events with the automationId and groupBy=emailId,eventType counts open and click events per copy. These are events, not people, so a reader who opens twice counts twice. Divide by each copy’s sends for a rate. Per-Contact Engagement covers the counts.

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