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Step 1
Start with event logs, test journey, browser and consent conditions, pixel configuration and order identifiers.
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Spark playbook scenarios · Spark: AI Store Assistant
Identify duplicate pixel events and likely sources
Marketing reports are missing or duplicating events, making campaign measurement unreliable. In this case, the immediate task is to identify duplicate pixel events and likely sources. The workflow should produce a tracking diagnosis and repeatable test plan, using the merchant's actual records and constraints.
Topic
Conversion Tracking and Pixel Issues
Target keyword
shopify pixel duplicate events
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 identify duplicate pixel events and likely sources.
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: [provide event logs, test journey, browser and consent conditions, pixel configuration and order identifiers]. Trace expected events through the journey, compare event IDs and timestamps and separate consent or access limitations from implementation failures.
Compare event IDs, timestamps and sending implementations to distinguish legitimate separate purchases from duplicated events.
Return a tracking diagnosis and repeatable test plan 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.Scenario & problem
When does this scenario usually come up?
Start with the business context, the trigger, and the expected output before moving into the execution steps.
Marketing reports are missing or duplicating events, making campaign measurement unreliable. In this case, the immediate task is to identify duplicate pixel events and likely sources. The workflow should produce a tracking diagnosis and repeatable test plan, using the merchant's actual records and constraints.
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
Trace expected events through the journey, compare event IDs and timestamps and separate consent or access limitations from implementation failures.
03
Step 3
Compare event IDs, timestamps and sending implementations to distinguish legitimate separate purchases from duplicated events.
04
Step 4
Deliver a tracking diagnosis and repeatable test plan; verify the result against the supplied records and identify unresolved inputs.
FAQ
Common questions when running this scenario
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
Why can a purchase be counted twice?
Multiple implementations or retries may send the same event without effective deduplication. Compare event identifiers before changing the setup.
Does a missing browser event mean the order never happened?
No. Tracking can be incomplete while an order exists. Reconcile measurement evidence with actual order records.
Should all repeated-looking purchase events be deleted?
No. Confirm that they represent the same transaction. Different orders may have similar values and timestamps.
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Next step
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