Amazon Flat File Templates Explained: How to Use Them Without Pain

Amazon flat file templates in 2026: what changed and what still works

Amazon flat file templates remain one of the primary ways sellers create and update listings in bulk through Seller Central. But the landscape shifted significantly in mid-2025 when Amazon deprecated legacy flat file and XML listing feeds through the Feeds API, pushing developers toward the JSON-based Listings Items API instead.

What does this mean practically? If your team uploads flat files manually through the Seller Central interface, that workflow still works. If your systems submit flat files programmatically through the SP-API Feeds endpoint, that path closed on July 31, 2025. Understanding which camp you fall into determines how you should approach flat files going forward.

Either way, the underlying challenge remains: Amazon's listing requirements are category-specific, change without warning, and punish sloppy data with rejected uploads, suppressed listings, or poor discoverability. A disciplined approach to template management saves hours of firefighting every upload cycle.

Before diving into Amazon-specific details, it helps to have solid feed fundamentals. Our guide on optimizing ecommerce product feeds covers the cross-channel baseline that makes platform-specific work easier.

Required fields and product type definitions

Required fields in Amazon flat file templates are not a single static list. They vary by product type, marketplace, and sometimes by the specific listing context such as whether you are creating a new ASIN or updating an existing one.

Amazon's current catalog architecture is built around Product Type Definitions. Each product type has its own JSON schema specifying which attributes are required, conditionally required, or recommended. When you download a flat file template from Seller Central, the columns and valid values reflect these definitions for the category you selected.

In practice, fields fall into three tiers:

Must-pass fields block ingestion entirely when missing or invalid. These typically include SKU, product identifiers (UPC, EAN, or GTIN where applicable), title, price, and core category attributes. Since January 2025, titles must stay under 200 characters for most categories and 125 characters for certain apparel subcategories. Special characters like !, $, ?, and { are prohibited unless part of a registered brand name.

Conditionally required fields become mandatory based on other values. For example, selecting a variation theme triggers requirements for parent-child relationship fields. Certain technical categories require material composition or compatibility attributes only when a product falls into a specific subcategory.

Recommended fields do not block upload but directly affect listing quality and search visibility. Missing bullet points, incomplete product descriptions, or absent backend keywords mean you pass ingestion but lose discoverability. Teams that only track blocking fields end up with live listings that underperform.

A solid product data quality checklist helps you govern all three tiers systematically instead of chasing errors after upload.

Anatomy of a flat file template and how to read it

Every Amazon flat file template you download from Seller Central contains seven sheets. Understanding each one prevents the kind of trial-and-error that wastes upload cycles.

• Instructions: Overview of the upload process and basic rules for the category.
• Data Definitions: Column-by-column field descriptions, data types, character limits, and whether each field is required, conditionally required, or optional.
• Valid Values: Enumeration lists for controlled attributes like color, size, material, and other fields that only accept predefined entries.
• Template: The actual data entry sheet where you fill in your product information. This is the only sheet you upload.
• Example: Sample rows showing correctly formatted entries for the category.
• Images: Specifications for product image requirements.
• Browse Data: Category node mappings and browse tree information.

The critical mistake teams make is ignoring the Data Definitions and Valid Values sheets. When you enter a color value that looks right to a human but does not match Amazon's enumeration exactly, the upload fails or the attribute gets silently dropped. Always cross-reference your data against the Valid Values sheet before uploading.

For teams managing product titles across categories, the Data Definitions sheet is where you find the exact character limits and formatting rules that vary between product types.

Building an attribute mapping pipeline

Most flat file errors originate upstream, not in the template itself. The root cause is typically a weak or nonexistent mapping between your source data (supplier feeds, ERP exports, PIM systems) and Amazon's attribute requirements.

Instead of manually copying values into spreadsheet columns, build a mapping pipeline with clear transformation rules:

Source identification: Document every field name from every source system. Suppliers call the same attribute different things. One vendor's Colour is another's Color_Primary, and your internal system might call it product_color.

Canonical normalization: Map all source variants to a single internal field name. This canonical layer is your translation hub. When a new supplier or data source appears, you only need to map it to the canonical model, not to every destination channel independently.

Amazon-specific transformation: From the canonical model, define how each field maps to the exact Amazon attribute name, apply formatting rules (unit conversions, character limits, enumeration matching), and specify fallback logic for missing values.

Validation gates: Before any data reaches the flat file, run checks against Amazon's allowed values, character limits, and cross-field dependencies.

This pipeline approach means your flat file becomes an output format, not a workspace. When Amazon changes a requirement or you expand into a new category, you update the mapping rules once rather than retraining a team on spreadsheet conventions.

Lasso's features are designed exactly for this workflow: import messy source feeds, normalize attributes against standardized rules, and output channel-ready data with validation built in. For teams still receiving inconsistent supplier files, our guide on standardizing supplier product data with AI covers how to clean up the input side.

Common flat file errors and how to prevent them

Certain error patterns appear in almost every Amazon flat file workflow. Knowing them in advance saves significant debugging time.

Error 90041 (Missing Product Information): Triggered when mandatory fields for a product type are empty or contain invalid data. Prevention: always download a fresh template for your specific category and verify every required column in the Data Definitions sheet before uploading.

Error 8541 (Attribute Mismatch): Occurs when your submitted data conflicts with existing catalog information for an ASIN. This commonly happens when updating listings where Amazon has locked certain attributes. Fix: submit a partial update file containing only the attributes you need to change rather than a full listing file.

Variation theme errors: Using an incorrect variation theme for your category causes parent-child relationship failures. Each Amazon category has approved variation themes (Size/Color, Size, Flavor, etc.), and picking one that is not supported for your product type triggers rejection. Prevention: check the Valid Values sheet for approved themes before building variations.

Duplicate SKU conflicts: Uploading a file with SKUs that already exist under a different ASIN or with conflicting product identifiers causes cascading errors. Maintain a clean catalog validation framework to catch these before upload.

Character limit violations: Since the January 2025 title policy update, Amazon enforces the 200-character limit more strictly and will auto-modify titles that exceed it after a 14-day grace period. Check all text fields against limits defined in the Data Definitions sheet.

Enumeration mismatches: Entering "Dark Blue" when Amazon's valid value list only accepts "Navy" causes silent attribute drops or outright rejections. The fix is maintaining a controlled dictionary that maps your internal values to Amazon's exact enumerations.

For teams managing attribute enrichment across sellable listings, pre-upload validation against Amazon's enumerations should be an automated step, not a manual review.

A practical pre-upload validation checklist

Uploading first and debugging later is the most expensive workflow pattern in catalog management. Every rejected file means another round of error parsing, data correction, re-upload, and waiting. Run these validation layers before any file touches Seller Central:

1. Template version check: Confirm you are using the latest template for your product type. Amazon updates templates without notification, and old column headers or missing fields cause immediate rejection.

2. Required field completeness: Verify every must-pass and conditionally required field has a valid value. Cross-reference against the Data Definitions sheet, not memory.

3. Data type and format validation: Numeric fields must follow Amazon's formatting (no currency symbols in price fields, correct decimal separators). Dates must match the expected format. Units must use Amazon's accepted abbreviations.

4. Enumeration matching: Check every controlled attribute against the Valid Values sheet. Flag any value that does not match exactly.

5. Cross-field dependency checks: Validate parent-child relationships, variation theme consistency, and identifier logic. If a parent SKU references child SKUs that are not in the file, the upload will fail.

6. Business rule review: Flag pricing anomalies, missing images, or incomplete descriptions that will pass ingestion but hurt listing performance.

Run a dry upload with a small SKU sample first. Review the processing report, fix any issues, and only then proceed with the full batch. This staged approach is especially important when listing products across multiple channels where a single data error can cascade.

Lasso can automate most of these validation steps, catching errors in your data pipeline before you ever generate the flat file. Combined with a solid product data enrichment workflow, pre-upload validation becomes a routine automated gate rather than a manual bottleneck.

Moving beyond flat files: when to consider API-based listing management

Flat files uploaded through Seller Central remain a valid tool, particularly for teams that manage fewer than a few thousand SKUs or need occasional bulk updates. But there are clear signals that it is time to graduate to a more automated approach:

• Upload frequency: If your team uploads files weekly or more often, manual template management becomes a time sink.
• Error rate: If more than five percent of rows fail on each upload, your data pipeline needs structural improvement, not more spreadsheet debugging.
• Category breadth: Managing templates across ten or more product types means ten or more sets of field requirements to track manually.
• Multi-marketplace presence: Selling on Amazon US, EU, and other regions multiplies template complexity since field requirements and valid values differ by marketplace.

Amazon's push toward the JSON-based Listings Items API and Product Type Definitions API is a clear signal about the platform's direction. While Seller Central flat file uploads still work, the API path gives you programmatic access to real-time product type schemas, synchronous validation feedback, and a workflow that integrates into your existing catalog automation.

For teams not ready for full API integration, the middle path is to automate the data preparation side. Keep your source data in a governed catalog model, use transformation rules to produce Amazon-ready output, validate automatically, and only use the flat file as the final delivery vehicle. This way, the template is just a format, and your investment is in the data pipeline that outlasts any single channel's upload mechanism.

If your team is planning this kind of operational shift, Lasso's pricing page shows how the platform fits into catalog workflows at different scales. For a walkthrough of how it maps to your specific categories, reach out to our team.