Altera shows a code such as ABC001 with each error or warning. This article explains the codes for this area of the app and how to resolve them. For codes from other areas, see Error and warning codes.

These codes will appear when you upload a spreadsheet to be imported with the app.

There was an error opening the file you uploaded. Please try again and contact us if the problem persists.

You can upload a ZIP file with multiple CSV files to have them processed at once. However in this case the app did not detect any CSV files in the zip file you uploaded.

If you want to process multiple Excel sheets at the same time you can combine them into a single Excel workbook and upload that.

We couldn't determine if your file was CSV, Excel, or a valid ZIP. Please upload either a CSV file, an Excel workbook with the .xlsx extension, or a ZIP file containing CSV files so our system can process it.

Our system tried to read your file but did not detect any sheets with the required structure. Ensure your file includes sheets that match one of our supported object types (for example, a valid Products or Orders sheet) and try again.

Your spreadsheet contains columns that Altera does not recognize and these columns will be ignored when you import data through the app.

The most common cause of this is trying to import data that does not match the Altera/Matrixify format. To fix this, make sure your spreadsheet matches the format in our documentation ( Product Fields for example).

The file you uploaded appears to be a product export from Shopify's admin in Shopify's native format. Altera requires product files to be in the Altera/Matrixify format instead. See our Product Fields documentation for the correct format.

You can convert your file to the Altera format by going to Tools > Data transformations in the left menu. Note that even if you convert a Shopify product export to the Altera/Matrixify format, some data may not come through.

If you're trying to copy products from one Shopify store to another, the best approach is to:

This ensures all product data is captured and transferred correctly.

Some columns can appear multiple times in a spreadsheet but others cannot. Make sure that you don't have any columns with duplicate names besides Tags and Image Src.

The same applies to a column and its old name. For example, Transaction: Shop Currency Amount is the old name of Transaction: Amount (Shop Currency), and Risk: Score is the old name of Risk: Level. Both columns set the same value, so keep only one of them.

The ID column contains a value that doesn't look like a valid Shopify ID. Shopify IDs are numeric and at least 9 digits long (e.g., 16224095404377). The ID column should either be empty, contain a Shopify numeric ID, or contain a GraphQL identifier like gid://shopify/Product/16224095404377.

Common causes:

If you are intentionally using your own identifiers in the ID column for row grouping, you can ignore this warning.

Excel has a character limit of 32,767 characters per cell. When metafields with exactly this character count are detected, they will be ignored during import to prevent data corruption in Shopify. This typically happens when Excel has truncated a longer value.

Note that the limit applies any time Excel reads or writes a cell, including when it opens a .csv file. Saving as CSV after opening in Excel does not restore the original value because Excel has already cut it. To preserve long metafield values, export the file directly from your source as CSV and edit it in a tool without this limit (such as Google Sheets, which allows up to 50,000 characters per cell, or a plain text editor). See IMP007 for more detail.

It looks like you are trying to upload an export of your WooCommerce products to Altera. Please try uploading the file again in the Altera/Matrixify format instead.

You are using the DELETE command in your import. Please note that deleting items is permanent and cannot be undone. The deletion will also process any hidden rows in your spreadsheet, so make sure to review your data carefully before proceeding.

You are using the REPLACE command in your import. When replacing items, the existing item will be completely deleted and recreated with the new data. This means all existing data not included in your import will be lost. The replacement will also process any hidden rows in your spreadsheet, so make sure to review your data carefully before proceeding.

ZIP files uploaded for import should not contain subdirectories. All CSV files should be placed at the root level of the ZIP file. Please restructure your ZIP file to place all CSV files in the root directory without any subdirectories.

The ZIP file you uploaded contains files that are not CSV files. ZIP files for import should only contain CSV files (plus any system files like .DS_Store which are automatically ignored). Please remove any non-CSV files from your ZIP file and try again.

The value provided cannot be converted to true/false. Boolean columns in your spreadsheet must contain recognized true or false values.

Accepted true values:

Accepted false values:

Values are case-insensitive, so TRUE, True, FALSE, and False are also valid. Make sure all values in boolean columns match one of these accepted formats.

The file you uploaded appears to be an order export from Shopify's admin in Shopify's native format. Altera requires order files to be in the Altera/Matrixify format instead, which contains more data than Shopify's native export.

You can convert the file under Tools > Data transformations in the app. Note that even if you convert a Shopify order export to the Altera/Matrixify format, not all order data will come through. Shopify's native order export is missing many fields that are required for a complete order import. For example:

If you're trying to copy orders from one Shopify store to another, the best approach is to:

This ensures all order data is captured and transferred correctly.

The system could not find a file analysis for the uploaded file. This typically occurs when trying to process a file that hasn't been analyzed yet. The file analysis should be triggered automatically when a file is uploaded.

If you continue to see this error, please contact support.

The file analysis completed successfully, but no analysis data was found. This is an unexpected error that indicates a problem with the analysis process.

Please try re-uploading your file. If the problem persists, contact support.

The system was unable to analyze your file due to an error. This could be caused by:

Try re-uploading your file. If the error persists, verify that your file is a valid CSV, Excel (.xlsx), or ZIP file. Contact support if you need further assistance.

The file analysis took too long to complete and timed out. This can happen with very large files or during periods of high system load.

Please try again in a few moments. If the problem persists with the same file, consider:

The Command column contains a value we don't recognize. Valid commands are:

Check your Command column for typos (e.g., "CREATE" instead of "NEW") and update them to one of the supported commands above. You can also leave the Command column blank to use the default MERGE behavior.

The file you uploaded appears to be an Etsy product listings export. This file needs to be converted to the Shopify format before importing.

Use the Etsy Products transformation under Tools > Data transformations to convert this file. See How to Migrate Etsy Products to Shopify for step-by-step instructions.

The file you uploaded appears to be an Etsy Order CSV export. This format gives a summary of each order but does not include the individual line items, which are required for importing into Shopify.

To import your Etsy orders, you need to export the Order Item CSV from Etsy instead. See How to Migrate Etsy Orders to Shopify for step-by-step instructions.

The file you uploaded appears to be an Etsy Order Item CSV export. This file needs to be converted to the Shopify format before importing.

Use the Etsy Orders transformation under Tools > Data transformations to convert this file. See How to Migrate Etsy Orders to Shopify for step-by-step instructions.

Your spreadsheet has an ID column where the first row is blank, but subsequent rows contain ID values. This pattern often indicates a data formatting problem in your spreadsheet.

Why this matters: If there are any valies in the ID column it will be used to group related rows together. For example, a product with multiple variants will have the product ID in the first row, and the variant rows below it share that same ID. When the importer sees a blank ID, it assumes those rows belong to the same item as the previous row.

Common causes:

How to fix:

The file you uploaded appears to be a Shopify theme ZIP file. Altera is designed for importing and exporting data like products, orders, and customers-not for managing themes.

How to upload themes to Shopify:

Theme ZIP files typically contain folders like assets, config, layout, locales, sections, and snippets, along with .liquid template files. If you intended to upload a data file (like products or orders), make sure you're uploading a CSV, Excel, or ZIP file containing CSV files instead.

The ID column in your spreadsheet contains values in scientific notation (e.g., 1.48E+13). This is typically caused by Excel automatically converting large numeric IDs into scientific notation format. This is a critical issue because the ID column is used to group rows together during import - when IDs are in scientific notation, many different rows can appear to have the same ID, causing them to be incorrectly grouped as a single record.

How to fix:

Tip: When working with large numeric IDs, always format the column as Text before pasting values to prevent Excel from converting them.

Your spreadsheet was matched to a Shopify data type, but all detected sheets contain errors that prevent the import from starting. Review the error messages shown for each sheet and correct the issues in your spreadsheet before re-uploading.

The CSV file could not be parsed because it contains formatting errors such as mismatched quotes, inconsistent column counts, or other structural issues. This typically happens when:

How to fix:

The easiest fix is to open the CSV file in Google Sheets or Excel and then save it as a new CSV file. This will automatically re-format the file with proper quoting and consistent columns.

If that doesn't work, you can manually inspect and fix the file:

Your file has more than one column that assigns a product to custom (manual) collections, such as both a Collection column and a Custom Collections column. Both map to the same underlying field.

This is informational, not an error. The import does not discard either column: it merges their values additively, so the product is added to the collections listed in every colliding column (duplicates are removed).

How to fix:

No action is required. If you prefer to keep things simple, use a single Custom Collections column with a comma-separated list of collection handles or titles, and remove the extra column.

Tip: If you originally exported the file from another application, try re-exporting it. Many applications have options for CSV export that handle quoting automatically.

The uploaded spreadsheet is password protected or encrypted, so Altera cannot read its contents. This applies to both .xls and .xlsx files that have been secured with a password.

How to fix:

The uploaded .xlsx file is a valid ZIP archive, but the spreadsheet data inside it doesn't follow the Excel format. The most common cause is cell references that are missing their column, which happens when a file is generated by a third-party tool or script rather than saved by a spreadsheet application. Altera can't tell which column each value belongs to, so it can't read the file.

How to fix:

Saving the file through a spreadsheet application rewrites the underlying structure and repairs the damaged references. If the tool that produced the file can also export CSV, uploading the CSV instead works too.

The uploaded file is larger than the 250 MB import size limit, so Altera can't analyze or import it.

How to fix:

For CSV files, splitting by rows works well because each row (or group of rows sharing an ID) is independent. Compressing a CSV into a ZIP file also reduces the upload size significantly.

The file is within the upload size limit, but analyzing it used more memory than allowed. This usually happens with ZIP files that expand to many gigabytes of data, or spreadsheets with an extremely large number of rows or columns.

How to fix:

The uploaded spreadsheet file is damaged. This usually affects older .xls files, which store their data in numbered blocks with an index that says which blocks belong to the spreadsheet. When that index is wrong, parts of the file overlap or point past the end of the file, so the spreadsheet can't be pieced back together. Common causes are an upload or download that stopped partway through, a file recovered from a failing disk or a corrupted email attachment, and older accounting or ERP systems that write incorrect .xls files.

How to fix:

If Excel can't open the file either, the original is unrecoverable. Export the data again from wherever it came from, and choose CSV or .xlsx if that option is available.

The uploaded .xlsx file isn't a complete archive. An .xlsx file is a compressed archive of smaller files, with an index of its contents stored at the very end. When that index is missing or a part of the archive is damaged, there's no way to unpack the spreadsheet. The usual cause is a transfer that stopped partway through, such as an interrupted upload, a download that was cancelled, or a file copied from a disconnected drive or a syncing cloud folder.

How to fix:

Checking the file size against the original is a quick way to spot a truncated copy.

The uploaded spreadsheet opened, but the data inside it is scrambled, so it can't be read. Unlike ALYS032, where the spreadsheet is structured in a way Altera can't interpret, here the underlying content is damaged and no application can parse it reliably. This usually follows file damage, such as a copy that was interrupted, a recovery from a failing disk, or an editing tool that crashed while saving.

How to fix:

If Excel can't open the file either, use an earlier version of the file, or export the data again from the system that produced it.

A customer notification column in your orders file contains TRUE. Shopify sends an email to the customer for every row where the column is TRUE:

This is usually not intended when you import historical orders, for example during a store migration. Customers would get emails about orders they placed months or years ago. The warning tells you which column is affected and how many rows have the value TRUE.

How to fix:

Files exported from Altera always contain FALSE in these columns. Customers who use the Shop app can still get a notification in the app when you import orders. See Customer notifications in the order fields reference for details. For notifications sent to your staff, see ORD004.

The Collections sheet mixes two sets of column names: the Matrixify columns (Source: Type, Source: Title, Inclusion: Type, Condition: Field, Condition: Value, Sort: Position, ...) and the Altera columns used before September 2026 (Source, Source Target, Must Match, Rule: Product Column, Rule: Condition, Product: Handle, ...). Both sets describe the same source data, so a file that carries both cannot be read unambiguously.

How to fix:

A few bytes in the CSV file are not valid in the file's text encoding. This usually happens when text with curly quotes or dashes is pasted from another program into a file that is saved as UTF-8, or when a file was saved with one encoding and edited with another. Altera replaced only those bytes with the replacement character (�) and imported the rest of the file unchanged.

How to fix:

Error codes related to data formatting and validation that can occur across different object types (orders, customers, products, etc.).

The phone number provided in your import is not in a valid format that Shopify accepts. Shopify is fairly strict about phone numbers and may reject numbers that are accepted in other platforms.

To ensure the phone number is accepted we recommend the following:

For US phone numbers specifically, Shopify rejects the area code 555 and all area codes starting with 1 as those are not real phone numbers.

Excel formatting tip: When entering phone numbers that start with a plus sign (like +16308545555), Excel may interpret them incorrectly or apply unwanted formatting. To prevent this, prefix the phone number with a single quote character (e.g., '+16308545555). The quote tells Excel to treat the value as text, and it won't be visible when the file is processed.

The province/state code provided in your import is not valid for the specified country. Shopify uses ISO 3166 standard province codes, and each country has its own set of valid province codes.

How to fix this:

Common examples:

If you're importing addresses for a country that doesn't require province codes, simply leave the province column empty rather than trying to provide a value.

The country value provided in your import could not be recognized. Shopify stores countries as ISO 3166-1 alpha-2 codes (two-letter codes). Altera accepts either the two-letter code or a full country name and converts recognized names to the matching code, but the value you provided matched neither.

How to fix this:

Common examples:

Common mistakes:

The email address provided in your import is not in a valid format. Email validation is performed by Shopify, not Altera, so any email that Shopify rejects will produce this error.

How to verify: You can confirm whether an email is valid by trying to manually create a customer with it in the Shopify admin. If Shopify rejects it there, it will also be rejected on import.

How to fix this:

Common examples of valid emails:

Common examples of invalid emails:

The value provided is not a valid number or cannot be converted to a number. This error occurs when numeric fields contain text, special characters, or formatting that cannot be interpreted as a valid numeric value.

This error applies to various numeric fields across different import types including:

Accepted number formats:

Numbers may be written with comma and period grouping, and are interpreted as follows:

See DAT019 for a warning about values whose grouping is interpreted in a way you may not expect.

How to fix this:

Common examples:

Invalid values:

Valid values:

The first name or last name provided in your import is not valid. Shopify has certain requirements for name fields that must be met for the import to succeed.

Common causes:

How to fix this:

Note: The support for emoji in name fields varies depending on what type of data you're importing. Some Shopify resources accept emoji in names while others do not. If you're seeing this error, the specific data type you're importing does not support emoji characters in the name field.

A required field in your import is empty or blank. Shopify requires certain fields to have a value and will reject records where these fields are missing.

Common required fields include:

How to fix:

Review the field mentioned in the error and provide a valid value. If you're updating existing records and don't want to change a field, you can leave it empty only if it's not required for the operation.

The value provided is too long and exceeds Shopify's maximum character limit for this field.

Common character limits:

How to fix:

Shorten the value to fit within the allowed character limit. If you're working with long text content, consider using a metafield with a larger capacity instead.

The value provided is too short and does not meet Shopify's minimum length requirement for this field.

How to fix:

Provide a longer value that meets the minimum length requirement. Check the specific field's requirements in Shopify's documentation.

The value you're trying to use is already taken by another record. Shopify requires certain fields to be unique across your store.

Fields that must be unique:

How to fix:

The ID or reference you provided does not match any existing record in your Shopify store. This typically happens when trying to link to another resource that doesn't exist.

Common causes:

How to fix:

The value provided is not valid for this field. This is a general validation error that occurs when the input doesn't meet Shopify's requirements.

Common causes:

How to fix:

Review the field's expected format in the documentation and ensure your value matches. Check for any special characters, encoding issues, or formatting problems.

You've reached a Shopify limit for this type of resource. Shopify imposes limits on various resources based on your plan.

Common limits:

How to fix:

The value provided doesn't match the expected format or constraints for this specific field type. This is common with metafields and fields that have specific validation rules.

Common causes:

How to fix:

The data type provided doesn't match what's expected for this field. This occurs when the wrong type of data is provided (e.g., text instead of a number).

Common causes:

How to fix:

The Shopify resource GID contains a non-numeric identifier where a numeric ID was expected. Some Shopify resource types (such as Online Store theme JSON templates) use string-based identifiers like article, blog, or cart instead of numeric IDs.

Common causes:

How to fix:

The date or time value in your import file is not valid. This usually means the timezone offset is outside the allowed range (±24 hours), or the value is otherwise malformed.

Common causes:

How to fix:

A date or date/time value in your import file falls before the year 0001 (1 AD) once it is converted to UTC. Neither Shopify nor the underlying date library can represent a year earlier than 0001, so the value was rejected.

Common causes:

How to fix:

This is a warning, not an error. The import is not blocked. A numeric value uses comma or period grouping that was read in a way you may not have intended, so it is worth double-checking the result.

This happens because a comma can mean two different things. When a value has no period, a comma is treated as the decimal separator, so 1,000 is read as 1 (one), not 1000 (one thousand). Mixed formats such as 1.000,00 are read the same way (the period is the decimal separator and the comma is removed), giving 1.

When you will see this:

How to fix this:

A Line: Properties value has a line with more than one colon (:). Each line item property is written as key: value on its own line, separated by real line breaks, and the colon separates the key from the value. A line with two or more colons is ambiguous, so the row is rejected.

The most common cause is a file that contains a literal \n (a backslash followed by the letter n) instead of a real line break, which leaves two key: value pairs on the same line.

Example that fails:

How to fix this:

The Tags Command column contains a value we don't recognize. This column controls how the tags in the row are applied to the object and must be one of MERGE, REPLACE or DELETE (case insensitive). The row was rejected so its tags are not applied incorrectly.

This commonly happens when a row-level command such as NEW or UPDATE is mistakenly entered in the Tags Command column instead of one of the values above.

How to fix this:

A metafield reference value didn't start with gid://shopify/, so it couldn't be processed. Check that all reference handles match the expected gid://shopify/ format.

Previous code: OBJ004.

These codes indicate that a row was skipped during import based on the command used and whether the item exists in Shopify. Skipped rows are not errors - they are expected behavior when using NEW, UPDATE, or DELETE commands with items that don't match the command's requirements.

You used the NEW command to create an item, but an item with the same identifier already exists in your Shopify store. The row was skipped to prevent creating duplicates.

Why this happens: The NEW command is designed to only create items that don't already exist. When it finds a matching item, it skips the row rather than failing.

The same applies to a Variant Command of NEW on a product import: a variant row that matches an existing variant is left unchanged, and the product row reports which variants were skipped.

How to resolve:

You used the UPDATE command to update an item, but no matching item was found in your Shopify store. The row was skipped because there's nothing to update.

Why this happens: The UPDATE command is designed to only update items that already exist. When it can't find a matching item, it skips the row rather than failing.

How to resolve:

You used the DELETE command to delete an item, but no matching item was found in your Shopify store. The row was skipped because there's nothing to delete.

Why this happens: The DELETE command is designed to only delete items that exist. When it can't find a matching item (perhaps because it was already deleted), it skips the row rather than failing.

How to resolve:

When importing a ZIP file containing multiple CSV files, the system could not find a CSV file matching the expected sheet name. This typically occurs when the ZIP file structure doesn't match what was detected during file analysis.

How to resolve:

The file format is not supported for this operation. Altera supports Excel (.xlsx), CSV, and ZIP files containing CSV files.

How to resolve:

The import row matched more than one existing item in your Shopify store, so the app could not safely determine which one to update, replace, or delete. The row was failed to avoid modifying the wrong item.

Why this happens: Some lookup columns (like Title for products or Name for orders) are not unique in Shopify. When the import file only includes a non-unique identifier and multiple items match it, the app cannot know which one you meant.

How to resolve:

A cell value is exactly 32,767 characters long, which is the maximum cell length in Excel. This strongly suggests the value was truncated by Excel, so Altera skips the row or field to avoid overwriting your Shopify data with incomplete content.

This affects Body HTML for products, pages, and blog posts as well as metafield values. When Body HTML is truncated the entire row is skipped. When a metafield value is truncated only that metafield is skipped.

Why a CSV file can still trigger this warning:

The 32,767 character limit applies whenever Excel reads or writes a cell, not just to .xlsx files. If you open a CSV in Excel, Excel truncates any long cells when it loads the file. Saving back to CSV from that point on preserves the truncated value, so the file extension is CSV but the content has already been cut. Altera detects the truncated length and warns even though the file is a CSV.

How to resolve:

A cell value is exactly 50,000 characters long, which is the maximum cell length in Google Sheets. This strongly suggests the value was truncated when the file was saved, so Altera skips the row or field to avoid corrupting data in Shopify.

This affects Body HTML for products, pages, and blog posts as well as metafield values. When Body HTML is truncated the entire row is skipped. When a metafield value is truncated only that metafield is skipped.

How to resolve:

Download your data as a CSV file directly from your source rather than copying it through Google Sheets.

Shopify accepted the request for this row but returned no object and no error, so Altera had nothing to record as the result. This is usually a transient condition that happens when the item is changed or removed in Shopify while the import is running (for example, an article that is updated by another process at the same moment).

Only the affected row is skipped. The rest of the import continues normally.

How to resolve:

Altera processes rows in parallel and uses a short-lived lock so that an image reused across many products is only uploaded once. This row waited too long for that shared upload (or another shared resource) to finish and gave up. This typically happens during large migrations where the same image appears on hundreds of products and is slow to process in Shopify.

Only the affected row is skipped. The rest of the import, including later steps, continues normally.

How to resolve:

Altera could not finish reading this import file because the process ran out of memory or stopped unexpectedly. This can happen with very large files (multiple gigabytes) when the server is busy with other large imports at the same time.

No rows from the file were imported. Your store data was not changed.

How to resolve:

Reading and preparing this import file took longer than the allowed time limit, so the import was stopped before any rows were processed.

No rows from the file were imported. Your store data was not changed.

How to resolve:

Rows that belong to the same item have different values in the Command column, for example MERGE on one row and DELETE on another. Rows belong to the same item when they repeat the identifier of the row above them (ID, Handle, Email, Name, and so on) or leave it blank, or when a variant [ID] column on a product import matches them to the same product. Only one command can be applied to an item, so the item is not imported and no changes are made to it. The message lists the conflicting commands and the first row that uses each one.

This applies to every data type with multiple rows per item, such as products with variants, customers with addresses, orders with line items, and companies with locations. Translations are the exception: each translation row can carry its own command.

How to resolve:

The Command cell is blank on the first row of an item, but another row of the same item has a command such as DELETE. The command for an item is read from its first row, and a blank cell means MERGE, so the later row's command would be ignored. Instead of silently merging the item, the item is not imported and no changes are made to it. The message names the row that has the command.

This applies to every data type with multiple rows per item, such as products with variants, customers with addresses, and orders with line items. Translations are the exception: each translation row can carry its own command.

How to resolve:

Codes related to creating and managing import or export jobs.

In order to provide a reliable service to all users you may have a limit to the number of jobs you can run at the same time. You can either cancel another job or wait for it to finish before starting a new job.

You have reached the maximum number of scheduled jobs allowed by your plan. To create a new scheduled job, you'll need to either disable an existing scheduled job or upgrade your plan for a higher scheduled job limit.

Your export has reached the maximum number of rows allowed by your current plan. The export was completed up to this limit, but additional data could not be included in the file.

To export more data, you can:

The exported file will contain a message indicating where the row limit was reached.

The single CSV export format only supports exporting one object type at a time. To export multiple object types, use the ZIP format (matrixify_zip) instead, which creates separate CSV files for each object type in a single archive.

You cannot enable scheduling for a job that does not have a schedule configured. Please configure the schedule settings (start time and repeat interval) before enabling scheduling.

A step in the data transformation recipe could not be applied to your export. The export completed using the original data without the transformations applied, and the file was not delivered to a remote connection.

The message on the job names the step that failed by its position and type in the recipe, for example Transformation step 2 (Copy column) failed. When the step can tell why, the message says so. The most common reason is a column the recipe refers to that is not in the export, for example because the export's field selection does not include it, or because the column has a different name in this data type.

To resolve this:

If the message gives no reason, the step failed unexpectedly. Please contact support with your job ID so we can look at the details.

The export configuration sent to the API is missing or contains invalid values, such as an unsupported filter relation or field name. The error message lists which part of the configuration failed validation and the accepted values.

To resolve this:

An export was created with a filter column that the selected data type does not have, for example a typo such as Bogus or a wrong-case key such as Handle instead of handle. Altera rejects the export instead of running it, because a filter it does not recognize cannot be applied and the export would otherwise contain the whole store.

The error message lists the valid filter columns for the data type.

To resolve this:

The export finished writing its data, but no output file path was recorded, so the job could not deliver the file or run the steps that follow it, such as data transformations and remote uploads. This is an internal error.

Run the export again. If it keeps happening, contact support with your job ID.

Previous code: TSK001.

The export job has no object types selected, so there is nothing to export. Edit the job and select at least one object type, such as Products or Orders, then run it again.

Previous code: TSK002.

The job stopped because of an unexpected error before it could finish. This can happen during a temporary service disruption, such as a Shopify outage, while the job is starting up or counting your data.

To resolve this:

Previous code: TSK003.

The import stopped at its last step, where the results file (a copy of your spreadsheet with the Import Result and Import Comment columns) is written. Every row that was imported before that step is already in your store, so do not import those rows again. This can happen when the spreadsheet carries a workbook setting that the file library rejects, even though Excel opens the file without complaint.

If the run was cancelled or reached your plan's row limit before this step, the sheets after that point were not imported.

To get a results file:

Previous code: TSK004.

A background task was started for a job run that no longer exists. This usually means the job or run was deleted while the task was waiting to start. No data was changed.

If you did not delete the job, run it again. If it keeps happening, contact support with your job ID.

Previous code: TASK001.

When trying to export objects, the provided object type wasn't recognized. Ensure you're using a valid object type (e.g., products or orders).

Previous code: OBJ001.

Sheet analysis didn't find a matching type for the label. Double-check your sheet configurations or labels before importing.

Previous code: OBJ002.

You tried to import using an object slug that isn't supported. Confirm it's a valid import type (e.g., products, customers).

Previous code: OBJ003.

You attempted to export using a data type the system doesn't recognize. Please try to reconfigure the job and run it again.

Previous code: WRT001.

The export format is not recognized. Currently Altera only supports CSV and Excel files in the Altera/Matrixify format.

Previous code: WRT002.

The export uses the Google Shopping Feed format, but includes an object type other than products. The Google Shopping Feed format can only be produced from product data.

Edit the export so that Products is the only selected object type, or choose the CSV or Excel format for the other object types.

Previous code: WRT003.