Amazon: error 8105
About this article
This article explains what Amazon error 8105 means, why it occurs, and how to resolve it on ChannelEngine.
Table of contents
Introduction
Error 8105 occurs when you submit a value for an attribute that does not match any of the valid values defined in Amazon's data definitions for that attribute. Amazon maintains a controlled list of accepted values for many product attributes, and any submission that falls outside this list is rejected.
Cause
This error is typically caused by one of the following:
- A product attribute contains a free-text value where Amazon requires a value from a predefined list (e.g.:
color_name,size_name,material_type). - The submitted value contains a misspelling or uses a synonym that Amazon does not recognize.
- The submitted value is valid in another category but is not accepted in the category being used for the affected SKU.
- The inventory file template being used is not the correct one for the product's category, resulting in a mismatch between the submitted values and the expected attribute definitions.
Resolution
To resolve error 8105, follow these steps:
- Open the affected SKU in Listed products, Validation and feedback.
- Identify the attribute name specified in the error message.
- Find the attribute in Mappings. If the attribute uses option mapping, click Edit option mapping and use Browse to select one of Amazon’s accepted values.
- If the attribute does not use option mapping, download the category-specific inventory file template from the Add Products via Upload section in Amazon Seller Central.
- Open the Data Definitions tab and locate the Accepted Values column for the attribute in question.
- Correct the value in your product data in the Mappings step on ChannelEngine.
- Wait for ChannelExport to re-export your product data.
NB: accepted values vary by product category. If you reference Amazon's templates, refer to the template that matches the exact category of the product you are listing. Using a template from a different category can lead you to invalid values even when the data itself appears correct.
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