Step 1
Collect the sales measures the merchant wants watched, the reporting cadence, the recipient for each measure, the action each alert starts and the historical variation of each measure used for setting levels.
Notifications fire for every small move, so the team has started ignoring them. In this case, the immediate task is to define actionable sales performance notifications. The workflow should produce sales and order alert rules with example messages, using the merchant's watched measures, cadence and the action each alert starts.
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.
Act as a Shopify operations specialist.
Help me define actionable sales performance notifications.
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: [the sales measures to watch, the reporting cadence, the recipient for each measure, the action each alert starts, and the historical variation of each measure used for setting levels]. Set each threshold from the measure's own observed variation so a move is reported only when it exceeds the merchant's stated tolerance against a matched comparison period, and define the evaluation window, the order status filter and the completeness check that must pass before an alert is allowed to fire.
Return sales and order alert rules with example messages 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.Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.
Collect the sales measures the merchant wants watched, the reporting cadence, the recipient for each measure, the action each alert starts and the historical variation of each measure used for setting levels.
Set each threshold from the measure's own observed variation so a move is reported only when it exceeds the merchant's stated tolerance against a matched comparison period, and define the evaluation window, the order status filter and the completeness check that must pass before an alert is allowed to fire.
Deliver the alert rules with the measure, comparison, threshold, owner, action and an example message for each, then verify them against the supplied records by replaying recent periods and counting how many alerts would have fired and how many of those were worth acting on.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
It names the measure, the comparison period, the size of the move, the owner and the next check to run. Without all five the recipient cannot act, and the rule should be dropped rather than left firing into a channel nobody reads.
From the measure's own observed variation, so the level sits outside normal movement yet inside the merchant's stated tolerance. The boundary is a very small measure: where variation is dominated by a handful of orders, the rule is set on order counts instead.
Cap the set at what an owner can actually review, replay recent periods to count how many alerts would have fired, and remove any rule where most of those would not have been acted on. Recipients and quiet hours belong in the rule, not in an afterthought.
Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.
Ciwi Spark builds Shopify-native AI tools and agents around the workflows merchants actually run: research, ads, translation, and customer support. Stop rewriting the same prompts by hand.