Step 1
Take every option name and value in use with the products carrying each one, the variant SKUs and the image or file names built from those labels, plus any marketplace feed, filter app or saved report that matches on the exact label text.
Option values were entered over years in mixed spellings and orders, and the merchant needs one convention without breaking dependent SKU and image references. In this case, the immediate task is to standardize the names and values of variant options. The workflow should produce a variant matrix and precise change list recording old and new labels.
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.
Act as a Shopify operations specialist.
Help me standardize the names and values of variant options.
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: [every option name and value in use with the products carrying it, the variant SKUs and image or file names built from those labels, and any marketplace feed, filter app or saved report matching the exact label text]. Choose one canonical spelling, letter case and value order per option, classify each current label as unchanged, renamed or merged, and flag any rename whose target label is already taken by another value or whose old text also appears inside a SKU, image reference or external mapping.
Return a variant matrix and precise change list, recording the old and new label for every renamed value 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.Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.
Take every option name and value in use with the products carrying each one, the variant SKUs and the image or file names built from those labels, plus any marketplace feed, filter app or saved report that matches on the exact label text.
Choose one canonical spelling, letter case and value order per option, classify each current label as unchanged, renamed or merged, and flag any rename whose target label is already taken by another value or whose old text also appears inside a SKU, image reference or external mapping.
Deliver a variant matrix and precise change list recording the old label, the new label and the products and variant IDs touched by each rename, then confirm that renamed plus unchanged labels still equal the original value count and re-run every mapping named in the first step against the new labels.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
Only when the supplier record or a shared SKU shows they describe the same purchasable variation, because merging two genuinely different finishes into one label removes a choice shoppers previously had; doubtful pairs stay recorded as rename candidates with the doubt written down rather than collapsed.
Image assignment, marketplace feeds, filter apps and saved reports often match on the raw text rather than an internal ID, so each one has to be listed before the rename and checked after it; assumed matches are what turn a tidy rename into lost variant images and unexplained export failures.
Recount values before and after and require the totals to match unless a deliberate merge is logged, then open one product from each affected group to confirm options, images and filters still resolve; a value count that drops without an entry in the change list means something was removed silently.
Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.
Ciwi Spark builds Shopify-native AI tools and agents around the workflows merchants actually run: research, ads, translation, and customer support. Stop rewriting the same prompts by hand.