How to Identify Missing Rows or Columns in Amazon Ads Exports

Compare row counts and date coverage first

Start with the most obvious signals: total row count and the date range covered by the export. If a current file has significantly fewer rows than the same period last week, something may have been cut off during export or filtering. Similarly, check that all expected marketplace days are present and that scheduled reports did not overlap or skip a day.

• Row count: compare with the previous report for the same period.
• Date coverage: verify every active campaign date is represented.
• Segment coverage: confirm placement, ad group, or keyword rows still appear where expected.

Run a null and missing-column check

Missing columns are often easier to detect than missing rows because the header structure changes. A quick review can confirm whether key fields like orders, sales, impressions, clicks, and spend are still present. Null checks help with partially populated files where some rows contain values but critical metric columns are blank.

Not every blank field is an error; for example, a keyword with no clicks may legitimately show no conversion values. The issue to watch for is a pattern of empty values across rows that should have data, especially in spend or impression columns while other metrics are populated.

When this matters

These checks have the most practical impact when ad decisions depend on clean exports. Missing rows can make a campaign look better or worse than it really is, which affects budget shifts, bid changes, and client reporting. Catching incomplete exports before analysis reduces the chance of acting on a distorted performance picture.