Prepare a Plumbing Pricebook Import Spreadsheet Safely

Treat the original file as evidence

Save an untouched copy of the source export. Make changes in a working copy and retain a mapping note explaining how each source field is handled. That gives you a way to investigate problems without reconstructing the original data from memory.

This is a vendor-neutral preparation guide. It does not assert that GoPlumber or another platform accepts every column shown below. Check the destination's actual supported import fields and validation messages before uploading business data.

Build an explicit mapping table

Keep unmapped fields in an accompanying archive or documented metadata process. Do not silently discard specifications, supplier references, or scope notes simply because the first import screen does not show a matching field.

Use a staging spreadsheet

source_system,source_item_id,service_code,name,description,unit,cost,selling_price,active,review_status
SOURCE,ID-EXAMPLE,CODE-EXAMPLE,Example service,Replace with reviewed scope,each,,,false,needs_price_review

The example intentionally leaves unknown numeric values blank. A blank cost is not the same as zero cost, and a blank selling price is not an offer to perform the work free of charge.

Keep identifiers as text so leading zeros survive. Check decimal separators, currency symbols, and whether amounts are stored in major units such as dollars or smaller units such as cents.

Check duplicates by identity and meaning

Two rows with the same service name may be different items with different scope or units. Conversely, two differently named rows may describe the same service. Review both the identifier and the meaning before merging.

For an illustrative example, “Service visit” priced per visit and “Service labor” priced per hour should not be merged merely because their names look similar. The unit changes how an estimate calculates the charge.

Do not reuse a retired item's code for a new unrelated service. Historical estimates may still depend on that reference.

Test a representative sample

Include a normal item, a long description, an inactive item, a leading-zero code, and a row with missing information. Check how the destination handles each case before importing the full list.

Create a test estimate from the imported item and inspect the customer-facing output. A successful upload message does not prove that descriptions, units, or prices were mapped correctly.

Confirm whether an import creates new items, updates matching items, or can do both. Do not rerun a full file until you understand the matching rule; otherwise, a retry may create duplicates.

Reconcile the result

Compare record counts, active-item counts, identifiers, and a sample of prices and descriptions. Keep an exception list for rejected, ambiguous, or unsupported rows.

Only make the imported catalog available to the team after those checks are resolved. The goal is a reviewed working pricebook, not merely an upload that finished without an error message.