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Spark playbook scenarios · Spark: AI Store Assistant

Design a replenishment email workflow

The team wants replenishment messages to run on their own, but no entry condition, wait step or suppression rule exists. In this case, the immediate task is to design a replenishment email workflow. The workflow should produce a replenishment reminder rule and email draft from the merchant's consumable range, repeat order history and allowed channels.

Topic
Reorder Reminders and Replenishment Emails
Target keyword
shopify replenishment email automation
Copyable AI prompt

A prompt you can drop directly into Spark

First replace every [bracketed] placeholder with real store scope and constraints, then add any actual records or data you have, and paste it into your preferred AI assistant or Spark agent. Spark will follow this page's workflow to produce structured output and verification steps.

ai-prompt.txt
Act as a Shopify operations specialist.
Help me design a replenishment email workflow.
My store context is [describe the business, products and target audience].

My scope is [specify the affected products, pages, customers or reporting period]. Use these inputs: [merchant-confirmed consumable SKUs, repeat order history with dates, per-customer email consent records, allowed channels, and the stated frequency cap and cooldown]. Define the entry trigger as a completed order containing a confirmed consumable SKU, the wait step from the stated cycle, suppression for later orders, unsubscribes and the frequency cap, and a follow-up branch after the stated number of days without a reorder.
Return a replenishment reminder rule and email draft for the specified task.
Show the relevant evidence or before-and-after examples and explain how I can verify the result.
If essential data is missing, ask for it and mark unsupported conclusions as unknown.
Do not invent metrics, product claims or customer facts.
For any publication, message, account or store change, use only connected tools within my explicitly authorized scope and report success only after verification; otherwise provide the draft or proposed steps.
Use in Spark
How to solve

A recommended resolution workflow

Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.

01

Step 1

Gather the merchant-confirmed consumable SKUs, repeat order history with dates, per-customer email consent records, allowed channels, and the stated frequency cap and cooldown.

02

Step 2

Define the entry trigger as a completed order containing a confirmed consumable SKU, the wait step from the stated cycle, suppression for later orders, unsubscribes and the frequency cap, and a follow-up branch after the stated number of days without a reorder.

03

Step 3

Deliver the workflow definition and email draft, then walk sample customers through it and verify that each suppression rule changes the send decision exactly as the records require.

FAQ

Common questions when running this scenario

Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.

What starts a customer in the flow?

Entry is a completed order containing at least one SKU the merchant has confirmed as consumable, with contact permission recorded at that moment. Durables in the same basket do not trigger entry on their own. Where the order contains several consumable SKUs, the wait step follows the longest stated cycle among them.

How does the suppression rule use later orders?

Before any send, the rule checks for a later order containing the same SKU and cancels that customer's pending message. Suppression is evaluated at send time, so a reorder placed during the wait step is still honoured. Customers whose later order sits unfulfilled are suppressed too, because the need the reminder addresses has been met.

Where in the flow is consent checked?

Consent is checked immediately before each send, not at entry, so an unsubscribe recorded during the wait step removes the customer before the message leaves. The check reads the merchant's permission record every time. Channels outside the allowed list are never used, even when contact details exist.

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