Get a demo

SKU standardization & mapping

Pull SKUs from vendor files, sales channels, and your ERP master list. Reconcile every variant into one clean mapping table the rest of your stack can trust.

Get a demo

The prompt

I want to standardize SKUs across our vendor files and sales channels into a single internal format. Can you build me a flow that ingests CSVs and Excel files, pulls the master SKU list from our ERP, matches and reconciles inconsistent SKU variations, and outputs a clean mapping table?

Just copy and paste the prompt into a new Parabola flow to get started.

What Parabola builds

A workflow with six steps you can edit:

1. Ingest the source files. Vendor CSVs, channel exports, retailer remittance sheets, anything that carries SKUs in a foreign format.

2. Pull the master list. The internal SKU table from NetSuite, Fulfil, or whichever ERP holds the canonical version.

3. Normalize the variant codes. Trim whitespace, fix casing, strip retailer prefixes, expand abbreviated codes. Apply your house format.

4. Match against the master. Exact match first, then fuzzy match on description and UPC for the ones that need help.

5. Flag the unmatched. SKUs that did not resolve land in a review queue with the candidate matches the flow considered.

6. Output the mapping table. Vendor SKU, channel SKU, retailer SKU, internal SKU, all in one place. Plus a clean exception list for the master data team.

Why teams stop doing this manually

The same product has six SKUs depending on who is writing it down. The vendor uses one code. The 3PL adds a prefix. Amazon stores it under an ASIN. The retailer ships back a remittance with their proprietary item number. The ERP master is the version that matters, but nothing upstream uses it.

The manual version is a spreadsheet that the ops team patches every time a new SKU shows up. The patch is a VLOOKUP against a tab the team built three years ago. New SKUs miss the table for a week. Old SKUs sit on the table after they have been retired. The downstream reports that depend on the mapping start showing duplicates and gaps that nobody can explain.

The work is not glamorous, but every other report rides on it. A clean SKU mapping is the difference between a sell-through report that ties out and a sell-through report that the planner has to explain. Build it once in a flow, keep it fresh on every run, and stop maintaining a shadow lookup table.

How it works

Step 1. Paste the prompt.

Open Parabola, paste the prompt in section 2, and let it ask follow-up questions about your file formats, where the master SKU list lives, and how strict the match needs to be.

Step 2. Connect your data.

Vendor inbox or shared folder for incoming files, your ERP for the master list, and a destination for the mapping output.

Step 3. Run it on every new file.

A new vendor CSV lands, the flow ingests it, matches each row against the master, and updates the mapping table. The exceptions land in the review queue.

Related prompts

FAQ

What if my vendors send the file in a different format every month?

The flow handles variable file shapes. It reads the headers, locates the SKU column, and applies the normalization rules. If the layout changes drastically, the exception queue catches the rows that did not parse.

How does fuzzy matching work for SKUs without a clean exact match?

The flow uses description and UPC as secondary keys. You set the confidence threshold. Below threshold, the row lands in the review queue with the candidate matches surfaced.

Can the flow write the mapping back to NetSuite as an item alias?

Yes. The output can push approved aliases into the ERP. Most teams keep the human approval step before any write-back.

What about discontinued SKUs?

Tag the master list with status. The flow ignores retired SKUs from matching but keeps them in the lookup table so historical reports still tie out.

How is this different from doing the mapping in Excel?

Excel works for a static lookup. It breaks when new SKUs hit weekly, when codes change format, and when six channels need to feed the same mapping. The flow runs every cycle, handles inconsistent inputs, and shows the matching logic so master data can audit each decision.
One SKU table the rest of the stack can trust.
Paste the prompt, point it at your vendor files and your master list, and let the mapping refresh on its own.
Start for free