Import Shopify Rental Products by CSV: A Rentshelf Guide

Understand what the rental import changes

Rentshelf CSV import helps a growing store configure many rental products without opening each rental record individually. It matches spreadsheet rows to Shopify products by product handle and creates or updates their rental configuration. The current feature is available on Growth.

This is a rental configuration workflow. Prepare the underlying products in Shopify first, including the handles you intend to reference. Keep your source catalog and a copy of the import file so you can trace a later setting back to the row that introduced it.

Download the template before editing

Use the template provided on the Rentshelf import page as the starting point. It documents the expected column names and gives you a structure for prices, duration, inventory, buffers, deposits, delivery methods and add-ons. Resist the temptation to rename headers to match an internal spreadsheet: recognizable labels for staff may not be valid import fields.

The product_handle field identifies the Shopify product. Copy the handle carefully rather than using the product title or a complete storefront URL. Check for duplicates in the file; the importer uses the first occurrence of a repeated handle, so a later row should not be treated as an intentional override.

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1. Catalog actions — Link products or begin the CSV workflow from the catalog actions.

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The rental catalog exposes Import CSV beside Link product. Inspect imported rows and then open representative products to verify the saved settings.

Prepare values as configuration data

Use plain numeric values for prices and quantities. Review the supported format before entering compound fields such as duration options, pricing tiers or add-ons. A comma within a field needs proper CSV quoting; a spreadsheet export is safer than manually joining text with commas.

Blank cells are ignored by the importer, helping preserve existing settings during updates. That also means a blank cell is not a reliable way to clear an existing value. If your task includes removing a setting, inspect the product configuration and use an explicit supported value or edit it in the app.

• Check that every product handle exists in Shopify.
• Use supported pricing modes such as DAILY, TIERED or FIXED.
• Review total units and buffer days as carefully as prices.
• Use the template format for dates, weekdays and compound fields.
• Keep one row per product handle.

Pilot three different products

Choose a simple daily rental, a product with an additional rule and a product whose existing settings you need to preserve. This small batch tests more than three nearly identical rows would. Save a copy of each current configuration before uploading changes.

After importing, read the per-row results. Correct the source spreadsheet when a row fails so your file remains the record of what you meant to apply. Do not assume that one successful row means the entire file was accepted.

Verify the storefront, then scale

Open each pilot product in the app and compare its saved values against the file. Next, choose dates on the storefront, inspect the quote and confirm that the available quantity behaves as intended. Include a variant or fixed duration when those settings are part of the import.

Only expand after these checks pass. Group the rest of the catalog into manageable batches and retain the files and results. This makes future updates easier to investigate and gives staff a clear record of which products have completed a storefront check.

Build a file another colleague can audit

Use a working spreadsheet with a notes column for your team, but export only the supported import columns. Beside the working copy, record who checked product handles, which settings should change and which should remain untouched. This prevents a file prepared for one task from quietly becoming a broad catalog reset when someone reuses it a month later.

Imagine you are adjusting buffers on twelve products. Start with the three-product pilot and include only the intended supported values. Compare the saved buffer against the before-state, then also inspect price and duration to confirm they were preserved. An import can be syntactically valid while still expressing the wrong business decision. The success message is the beginning of verification, not the whole acceptance test.

Treat failed rows as a separate queue

If nine rows succeed and three fail, keep those groups separate. Read the specific error for each rejected row, correct the source file and resubmit the affected configuration only after understanding what changed. Avoid repeatedly uploading the entire file without a record of prior results. Otherwise colleagues cannot tell whether a value came from the original batch or a later correction.

Common investigation points include a handle that no longer matches Shopify, an unsupported header, a number formatted as currency text and a compound field exported without quoting. Check the template before guessing a replacement format. Preserve the rejected file with a clear name, and save the corrected version separately so the difference remains visible.

Plan recovery before the larger upload

An import is not a backup system. Keep the configuration you intend to restore before changing a large group of products. If the pilot is wrong, correct the affected settings and verify again before touching the remaining catalog. Do not assume uploading an older spreadsheet will reverse every possible change, particularly where blank cells are ignored.

Schedule the larger batch when someone can inspect row results and sample live product pages immediately. Give staff the list of changed products and the settings involved. A short handover such as “buffers updated; prices unchanged; three exceptions still pending” is more useful than simply saying the import finished.