Shopify bulk editor, CSV or a browser assistant: which fits your update?
You have a list of product changes to make in Shopify: new prices, corrected SKUs, updated weights, a few new metafield values. Shopify gives you two native ways to apply them: the bulk editor and CSV import. Most of the time, one of those is the right choice, and you don’t need anything else.
Sometimes, though, the hard part isn’t applying the update. It’s that half the values don’t exist yet. They’re spread across supplier portals, PDFs and product pages. This guide helps you choose the right native method for the update and recognise when you have a preparation problem instead.
The decision table
Use this to place your update. The first two columns are about applying changes. The third is about preparing them.
| Dimension | Shopify bulk editor | CSV import | Browser assistant (e.g. Dassi) |
|---|---|---|---|
| Input readiness | Values are known and you can type or fill them in directly | Values already sit in a spreadsheet keyed by product handle | Values are missing, scattered across supplier sites, or need reconciling |
| Update size | Items you can select in the admin and review on screen | Larger catalog changes; file must be under 15 MB | Small batches of unresolved fields, reviewed before any update |
| Cross-site lookup | None. You edit what’s in Shopify | None. You prepare the file elsewhere | Reads pages on sites you’re already logged into |
| Review effort | See each cell before saving; Shopify validates values on save | Check every included column, because blanks can overwrite data | Check each gathered value against its source link |
| Rollback preparation | Shopify’s help pages don’t describe an undo, so record current values first | Shopify tells you to back up product data first; imports can’t be cancelled once started | Not applicable. It prepares data; you still apply it with a native method |
If your values are ready, choose between the first two columns. If they’re not, the third column is about getting them ready, not about replacing Shopify’s tools.
When the bulk editor fits
The bulk editor works with products and variants, collections, customers and inventory (variants only). You select items with checkboxes in the admin, click Bulk edit, then use Columns to add the properties you want to change, such as price, SKU or compare-at price.
It suits updates where you can see the work:
- You can copy a value to neighbouring cells by dragging the cell’s fill handle.
- Shopify checks values when you click Save. If something is invalid, such as a missing required SKU or a metafield that fails validation, you fix it and save again.
- For products with multiple variants, inventory can only be bulk edited from the Inventory section.
Two practical notes from Shopify’s documentation: the more you change at once, the longer saving takes, and Microsoft Edge can cause errors because of its URL length limit. Shopify’s product bulk editing page points to CSV import for larger operations.
Before you save: the help pages don’t describe an undo. Copy the current values of the columns you’re changing, or export the affected products, so you can restore them if needed.
When CSV import fits
CSV import suits larger structured changes, especially when your data already lives in a spreadsheet. It’s also where you’d handle product metafields (once they’re defined) and image URLs (publicly accessible HTTPS links, up to 250 per product).
CSV is powerful, and its overwrite rules deserve a checklist. When you choose Overwrite products with matching handles:
- Every row has Title and Handle. The handle is the unique identifier Shopify uses to match existing products.
- No accidental blanks. A blank cell in an included column overwrites the existing value with a blank.
- Only the columns you mean to change. Columns left out of the file keep their current values, so a narrow file is safer than a full export.
- Option columns kept for variant products. If you leave out the Option1 name and value columns, Shopify creates a new default variant and deletes existing variants.
- Dependent columns present. Including a non-required column without the columns it depends on can remove existing data.
- No variant metafields. Product CSV doesn’t support them.
- A backup exists. Shopify’s import instructions say to back up product data before importing. Once an import starts, it can’t be cancelled.
CSV also can’t delete products in bulk, so it isn’t the tool for clearing out discontinued lines.
When preparation is the bottleneck
Both native methods assume you already have correct values. Here is an illustrative example of a case where you don’t:
A store stocks 40 products from three suppliers. The supplier spreadsheet covers price and SKU, but not carton weight, country of origin or the updated material composition. Those details sit on each supplier’s product pages, one of which needs a trade login. Five products show different SKUs on the supplier site than in the store.
Choosing between bulk editor and CSV doesn’t help yet. The slow part is opening each supplier page, finding the field, checking it matches the right variant and noting where it came from.
This is where a browser assistant can help. Dassi runs in your browser on sites you’re already logged into. You describe or demonstrate a task, set rules for which sites it uses and when it pauses, then run it and review the run history. Your configured AI provider processes the instructions and relevant page content, so check your provider’s data terms before using it on sensitive supplier pages.
A read-only preparation prompt keeps the scope tight:
For each row in the table below, open the supplier product page in the
"Source URL" column. Find the field named in "Missing field".
Return a table with: Handle, SKU, Missing field, Value found,
Exact text on the page, Source URL.
If the page shows a different SKU from the one in the table, or the value
is ambiguous or absent, write UNRESOLVED and explain why.
Do not edit anything in Shopify. Do not guess values.Then verify before any update:
- Open each source link and confirm the value matches the page text.
- Confirm units (grams vs kilograms, centimetres vs inches) match your store’s convention.
- Resolve every UNRESOLVED row by hand or with the supplier.
- Apply the confirmed values with the bulk editor or CSV, using the checks above.
For the preparation steps themselves, these guides go deeper: turning a supplier catalog into a checked SKU spreadsheet, comparing supplier price lists by SKU and matching supplier photos to Shopify variants.
Where human review stays
No method removes review. The bulk editor validates format, not whether a price is right. CSV applies exactly what’s in the file, blanks included. A browser assistant can misread a page or pick the wrong variant, which is why every gathered value needs a source link you check. You decide what goes into Shopify.
Your next step
Start with the native method. If your values are ready and you can review them on screen, use the bulk editor. If they’re in a spreadsheet keyed by handle, use CSV, back up first and import only the columns you’re changing.
If gathering supplier data is what’s holding you up, pick five unresolved supplier fields and try the prompt above with Dassi for Chrome. Check each value against its source, then apply the confirmed ones through Shopify.