Overview

Error 90223 is a common feed processing error that Amazon sellers encounter when submitting product listing data through flat files or feed uploads. This error fires when a value provided for a specific attribute doesn't match the expected data type — for example, entering text where Amazon requires a number. Understanding how to diagnose and resolve this error quickly can prevent delays in getting your listings live.

Key Points / What Sellers Need to Know

• Data type mismatch is the root cause — Error 90223 means the value you submitted for a product attribute doesn't conform to Amazon's expected format, whether that's a number, date, boolean, or specific text pattern.
• Multiple formatting issues can trigger it — Incorrect units, special characters, wrong date formats, or text entered in a numeric field will all produce this error.
• The error message identifies the problem field — Amazon's error output specifies the exact attribute name and the expected data type, giving you a clear starting point for troubleshooting.
• Feed processing reports are essential — Your feed processing summary report will pinpoint which rows and attributes triggered the error, so always review it before making corrections.
• Resubmission is required after fixing — Once you've corrected the offending values, you must resubmit your entire feed file for the changes to take effect.

Common Causes

Several formatting mistakes can trigger Error 90223 during feed processing. The most frequent cause is entering text characters in a field that requires a purely numeric value — for instance, including a dollar sign or currency code in a price field, or adding "lbs" after a weight value. Amazon also enforces strict date formatting standards, so entering dates as "01/15/2025" instead of the required "2025-01-15" (YYYY-MM-DD) format will produce this error. Boolean fields are another common stumbling point, as they only accept specific values like "true" or "false" (or "1" and "0"), and any variation will be rejected. Sellers who copy data from spreadsheets may inadvertently carry over hidden formatting, extra spaces, or special characters that violate Amazon's data type requirements.