Shopify Product Upload Services and Catalogue Setup

Send a real sample before asking for a price. Twenty rows from your actual supplier sheet, with the images as you have them, tell a specialist more than any description. Messy source data is what makes uploads slow, and a quote given without seeing it is a guess.

Ask how they'll get products in, not just how fast. Anything beyond a few dozen products should go in through a spreadsheet import, not one by one in the admin. Ask to see the import file before it's loaded, and what happens to rows that fail.

Test their judgement on variants. Ask how they'd set up a shirt sold in four colours and six sizes, and when they'd split a range into separate products instead. General ecommerce data entry services type fast but rarely make these calls well. Someone who can't explain the trade-off will make a different choice every week.

Agree naming conventions up front. Option names, vendor and product type values, tags and SKU format should follow one written convention. "Colour" on one product and "Color" on the next splits your filters, and inconsistent tags or product types quietly drop products out of automated collections.

Ask for quality checks after every batch. A good specialist spot-checks prices, stock, weights and images against the source, then sends you a list of gaps: missing barcodes, low-resolution images, products with no type. Weights matter because shipping rates can depend on them.

Be wary of a flat per-product price with no questions. A specialist who quotes without asking about variants, images or metafields hasn't looked at the work. The same goes for anyone who folds descriptions into the data entry rate: writing is a different skill and should be priced as one.

Most catalogue problems are decided in the first week and paid for long after. Settle these before the first import.

Product or variant. Variants suit versions of one item that share a description and differ by size, colour or material. Separate products suit items that need their own description, images, reviews or search presence. Shopify also limits how many options and variants a single product can carry, so very large ranges may need splitting anyway.

Option naming. Pick one name per option ("Size", "Colour") and one format for values ("Small" or "S", never both). Storefront filters group by these values, so inconsistency is visible to customers.

Manual or automated collections. Manual collections suit small curated edits. Automated collections pull products in by rules such as product type, tag, vendor or price, so new uploads land in the right place without anyone editing the collection. Most catalogues want mostly automated collections, with a few manual ones for campaigns.

Metafields for specs. Materials, dimensions, care instructions and compatibility belong in metafield definitions, not in tags or buried in descriptions. From there they can feed product-page blocks and storefront filters.

SKU and barcode conventions. A SKU format that encodes range, colour and size, such as TEE-BLK-M, speeds up stock counts and picking. Barcodes matter if you sell on marketplaces or advertise on Google Shopping.

An import template. The last deliverable should be a spreadsheet template with your columns, your conventions and one example row — so the next 500 products don't need a specialist.

Specialists price per product, per project or per hour, and the state of your source data decides which is fairest. Typical ranges:

From the first upload to keeping a live catalogue tidy, the work breaks down like this: