01
Step 1
Start with shopper requirements, catalog attributes, current availability and recommendation constraints.
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Spark playbook scenarios · Spark: AI Store Assistant
Recommend products based on stated shopper needs
Shoppers need help choosing among products, but generic recommendations do not reflect their needs. In this case, the immediate task is to recommend products based on stated shopper needs. The workflow should produce a reasoned product shortlist or recommendation dialogue, using the merchant's actual records and constraints.
Topic
AI Shopping and Product Recommendations
Target keyword
shopify personalized product recommendations
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 recommend products based on stated shopper needs.
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 shopper requirements, catalog attributes, current availability and recommendation constraints]. Match stated needs to supported product attributes, explain tradeoffs and ask targeted questions where preferences are missing.
Return a reasoned product shortlist or recommendation dialogue 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.
Shoppers need help choosing among products, but generic recommendations do not reflect their needs. In this case, the immediate task is to recommend products based on stated shopper needs. The workflow should produce a reasoned product shortlist or recommendation dialogue, 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
Match stated needs to supported product attributes, explain tradeoffs and ask targeted questions where preferences are missing.
03
Step 3
Deliver a reasoned product shortlist or recommendation dialogue; 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.
Should the most expensive product always be recommended?
No. Fit with the shopper's requirements and constraints is more important than price alone.
Why explain recommendation reasons?
It lets shoppers judge whether the suggested product actually addresses their needs.
What information is needed to investigate this use case?
Start with shopper requirements, catalog attributes, current availability and recommendation constraints. 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.
Related scenarios
Continue with adjacent or same-topic scenarios
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Next step
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