The spreadsheet that arrives two days before go-live
The contract is signed and the first inbound is booked. Then the client's product list arrives. It is an export from their Shopify admin with 1,200 rows, a third of which are variants of the same T-shirt. The barcode column is half empty, the weight column is in grams for some rows and kilograms for others, dimensions are missing entirely, and there are three SKUs that appear twice with different descriptions.
Your onboarding person spends days on it. They email the client a list of questions, get back a different file, merge the two, and discover on receiving day that the case barcodes on the cartons do not match any of the unit barcodes they were given.
Why product data is always the bottleneck
The client's system only needed enough data to sell. Your warehouse needs enough to receive, store, pick, pack and ship, and that is a longer list. Nobody tells the client that until they are asked, and they rarely know the answers straight away because their own supplier holds the carton specifications.
| Field | Why the warehouse needs it |
|---|---|
| Unit barcode | Scan to confirm the right item is picked |
| Case or inner barcode and quantity | Receiving cartons without opening every one |
| Weight and dimensions | Carrier service selection, box size, volume-based storage |
| Batch or best-before flag | Whether the WMS must capture it at goods in |
| Customs data for cross-border orders | Commodity code and country of origin on declarations |
| Hazard or special handling flags | Keeping restricted items out of the wrong service |
There is also no single form. Every onboarding is done slightly differently depending on who handles it, so the questions asked of one client differ from those asked of the next.
What slow onboarding costs a 3PL
Delayed go-lives delay revenue, and a client who spent their first fortnight answering the same question three times starts the relationship doubtful. Worse is bad data that gets through. A missing weight means the wrong carrier service or a surcharge later. A wrong case quantity means a stock discrepancy on day one that takes weeks to explain.
Your most experienced operations person also ends up as a data cleaner, which is not what you hired them for.
The onboarding checker we build
- An upload page for the client, or an inbox, that accepts their product file in whatever shape it comes: CSV, Excel, or an export from Shopify, WooCommerce or their ERP.
- Column mapping that recognises common export formats and remembers a client's mapping for next time they add products.
- Field checks against your rules: barcode format and check digits, duplicate SKUs and barcodes, units of weight that look wrong, dimensions that are impossible for the product type.
- A gap report written for the client, listing exactly which SKUs lack which fields, in plain language they can pass to their supplier.
- A load into your WMS through its API or import template once the file passes, with a record of who approved it.
- The same check for every later product update, so new ranges follow the same standard as the first load.
Where it helps, a language model such as OpenAI or Anthropic Claude can suggest a mapping for unfamiliar column names or group variants under a parent. It proposes; your team confirms.
What onboarding feels like afterwards
The client gets one clear list of what is missing, early, instead of a trickle of emails. Your team starts receiving with product data that has already been checked, and the WMS stops accumulating half-complete SKUs that cause problems months later.
Every client is onboarded to the same standard, whoever handles it.
Signs your onboarding needs this
- Product files arrive in a different layout from every client.
- Go-live dates slip while product data is fixed.
- Receiving finds case barcodes nobody was told about.
- Your WMS has SKUs with no weight or dimensions.
- One person knows how to clean and import a client's product list.