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Step 1
Start with traffic time series, source and device segments, event quality and known campaign changes.
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Spark playbook scenarios · Spark: AI Store Assistant
Assess evidence of suspicious automated traffic
Traffic changes sharply or appears inconsistent with normal customer behavior. In this case, the immediate task is to assess evidence of suspicious automated traffic. The workflow should produce a traffic anomaly report and investigation rules, using the merchant's actual records and constraints.
Topic
Traffic Anomalies and Alerts
Target keyword
shopify bot traffic detection
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 assess evidence of suspicious automated traffic.
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 traffic time series, source and device segments, event quality and known campaign changes].
Identify the affected segments, compare against a suitable baseline and distinguish suspicious patterns from confirmed bot activity.
Return a traffic anomaly report and investigation rules 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.
Traffic changes sharply or appears inconsistent with normal customer behavior. In this case, the immediate task is to assess evidence of suspicious automated traffic. The workflow should produce a traffic anomaly report and investigation rules, 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
Identify the affected segments, compare against a suitable baseline and distinguish suspicious patterns from confirmed bot activity.
03
Step 3
Deliver a traffic anomaly report and investigation rules; 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.
Does unusual traffic prove a bot attack?
No. Campaigns, tracking changes and referral behavior can also produce unusual patterns.
Why review conversion and engagement alongside sessions?
They help distinguish potentially useful visits from traffic that adds volume without relevant behavior.
What information is needed to investigate this use case?
Start with traffic time series, source and device segments, event quality and known campaign changes. These inputs establish the relevant scope and help separate an actual issue from missing information or an unsuitable comparison. Without them, the result should remain a proposed approach rather than a confirmed diagnosis.
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Next step
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