01
Step 1
Collect the alert types and their thresholds, the channel each one uses, the quiet periods and coverage hours configured, and the severities the merchant treats as exempt from any limit.
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Spark playbook scenarios · Spark: AI Store Assistant
Control notification frequency and quiet periods
One ongoing condition keeps generating separate messages, and the team has started ignoring the channel. In this case, the immediate task is to control notification frequency and quiet periods. The workflow should produce an alert management specification and message templates that group repeated events and set sending windows and severity exceptions.
Topic
Alert Rules and Notification Management
Target keyword
shopify notification frequency settings
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 control notification frequency and quiet periods.
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 alert types and their thresholds, the channel each one uses, the configured quiet periods and coverage hours, and the severities treated as exempt from any limit]. Give each alert type a grouping window so repeated events from one open condition update a single notification, set the sending windows and the severity exceptions that bypass them, and mark any condition that keeps firing after grouping as a rule defect rather than raising the frequency limit.
Return an alert management specification and message templates with each rule verified against the supplied records 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.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.
02
Step 2
Give each alert type a grouping window so repeated events from one open condition update a single notification, set the sending windows and the severity exceptions that bypass them, and mark any condition that keeps firing after grouping as a rule defect rather than raising the frequency limit.
03
Step 3
Deliver the alert management specification and message templates with the grouping window, sending window and exceptions recorded per type, then verify each rule against the supplied records by confirming that one open condition produces one notification inside the window.
FAQ
Common questions when running this scenario
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
Why does one condition still produce several messages?
Because the rule has no grouping window, so each evaluation opens a new notification instead of updating the open one. With a window the condition produces a single message revised until it clears, and extra messages after that point to a rule defect rather than a frequency setting.
What must a quiet period policy state?
The hours covered, the severities allowed through regardless, and how suppressed notifications are delivered afterwards. Without the third item a genuine incident that happened overnight simply disappears and the team never learns it occurred.
Should every alert type share the same limit?
No, limits are set per type and per channel by how quickly the underlying condition can change, while urgent severities bypass them. One limit applied everywhere either floods the channel during an incident or delays the message that had to arrive immediately.
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Next step
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