01
Step 1
Collect the incomplete product records with their product IDs, the authoritative source material supplied per attribute, the target field schema, and the current value on record for each field so any overwrite can be compared against it.
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Spark playbook scenarios · Spark: AI Store Assistant
Enrich incomplete records from authoritative product sources
A supplier feed leaves core attributes blank across part of the catalog, and recorded values have no origin. In this case, the immediate task is to enrich incomplete records from authoritative product sources. The workflow should produce an enriched product data draft in which every filled value names its source and unstated attributes stay unresolved.
Topic
Product Data Enrichment
Target keyword
shopify product data enrichment
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 enrich incomplete records from authoritative product 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: [the incomplete product records with their product IDs, the authoritative source material supplied per attribute, the target field schema, and the current value on record for each field]. Match each source value to its product by the identifier both records share, fill only fields a source states outright, record the source and the retrieval reference beside every filled value, and leave an attribute unresolved where the source is silent, ambiguous between two products or contradicted by another supplied source.
Return an enriched product data draft with unresolved fields 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
Match each source value to its product by the identifier both records share, fill only fields a source states outright, record the source and the retrieval reference beside every filled value, and leave an attribute unresolved where the source is silent, ambiguous between two products or contradicted by another supplied source.
03
Step 3
Deliver an enriched product data draft in which every filled value names its source, list each still-unresolved attribute with the reason it stayed open, and reconcile the filled-value count plus the unresolved count against the field total in the target schema before handing the draft to the merchant.
FAQ
Common questions when running this scenario
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
How is a value matched to the right product?
Match on the identifier both the record and the source carry, such as the SKU or the supplier code. Where only a product name links them, record the match as uncertain and leave the value unresolved rather than filling it, because a confident wrong match is harder to detect than a stated gap.
What happens when two supplied sources disagree?
Keep the value from the source the merchant ranks higher and record the conflict beside it. Choosing silently hides a discrepancy the merchant may need to settle with the supplier, and the same disagreement usually points at the source that should be corrected.
How is a completed enrichment pass checked?
Count the filled values and the unresolved attributes and check the sum against the fields in the target schema. A pass that accounts for fewer fields than it started with has dropped data, and every overwrite should still show the value it replaced.
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Next step
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