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Spark playbook scenarios · Spark: AI Store Assistant

Convert supplier records into Shopify product drafts

A supplier feed has to land in the store, but its identifiers follow another convention and its categories do not line up. In this case, the immediate task is to convert supplier records into Shopify product drafts. The workflow should produce a validated import draft with a row-level exception list, each match verified against the merchant's supplier data.

Topic
Product Creation and Import
Target keyword
import supplier products to shopify
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 convert supplier records into Shopify product drafts.
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 supplier feed, its identifier convention, the agreed crosswalk onto store identifiers, the category-to-collection mapping, the permitted write fields, and each row's supplier status]. Resolve each row to an existing product through the crosswalk or record it as new, place it into its agreed destination collection, carry only the permitted fields into the product schema, and flag rows whose supplier identifier is missing, whose category has no agreed destination, or whose status reads discontinued or unavailable.
Return a validated import draft with a row-level exception list 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.
Use in Spark
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.

01

Step 1

Collect the supplier feed, the identifier convention it follows, the agreed crosswalk onto store identifiers, the mapping between the supplier's categories and the collections in use, and the fields the feed is permitted to write.

02

Step 2

Resolve each row to an existing product through the crosswalk or record it as new, place it into its agreed destination collection, carry only the permitted fields into the product schema, and flag rows whose supplier identifier is missing, whose category has no agreed destination, or whose status reads discontinued or unavailable.

03

Step 3

Deliver the import draft with a row-level exception list stating per row whether it matched, was created or was parked, which collection it landed in and which fields came from the feed, then verify each match against the merchant's supplier data and confirm the counts of new, updated and parked rows add up to the rows supplied.

FAQ

Common questions when running this scenario

Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.

How do supplier identifiers reach store records?

Through the crosswalk the merchant maintains, pairing each supplier key with exactly one store identifier. Without it matching falls back on names and the same product arrives twice under two spellings; rows whose key has no pair yet are created new and reported, so the crosswalk can be extended deliberately rather than guessed.

What happens to categories with no store equivalent?

The row is parked rather than pushed into an approximate collection, because a near-miss category quietly misplaces the product in navigation and filters. Parked rows keep their original supplier category, so the merchant can add the missing collection or agree a proper destination later.

Should discontinued items be removed?

Flag them for review instead of deleting anything, since removal destroys records that may still carry order history. Discontinued rows appear in the exception list with their status; whether to unpublish, archive or leave them is the merchant's call, because availability and supplier discontinuation are separate decisions.

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