Best Practices for Cleaning Amazon Ads Data

Check for duplicates and structural noise

Amazon Ads exports can contain repeated rows when reports overlap or when the same file is pulled more than once. A reliable cleanup starts by identifying a unique key for each record, usually a combination of date, campaign name, ad group, and target or search term. Remove duplicate rows before importing to avoid double-counted spend and inflated performance metrics.

• Sort by date, campaign name, and search term to locate repeated entries.
• Delete blank rows and any summary or total lines that are not part of the raw data set.
• Keep one row per unique key unless the report intentionally splits match types or placements.

Standardize fields before aggregation

Consistent column names and value formats make it easier to refresh a dashboard without rewriting calculations. Rename fields so the same metric uses the same label in every export, and convert text values into proper date or numeric types where needed.

• Use short, stable column names without spaces or special characters where possible.
• Convert date columns to a single date format and time zone convention.
• Turn spend, sales, clicks, and conversion rate into numeric fields so aggregations work correctly.

For teams processing multiple Sponsored Products files, Amazon Ads Report Analyzer automates report imports, which can reduce the manual normalization step before analysis.

When clean data matters most

A clean export is especially valuable when you are blending Amazon Ads data with other sources or comparing trends over time. Missing columns, duplicate records, or inconsistent date formats become more visible as the dashboard grows, and small errors can distort ROAS, ACoS, and wasted spend calculations.

• Before connecting to Power BI or Looker Studio, verify that every metric used in your report is present.
• Confirm that zero values are true zeros and not blank cells that will be read as null.
• Spot-check a few rows against the Amazon Ads console to ensure totals align.

For analyzing spend efficiency after cleaning, Amz Ad Waste Detector - Amazon Ads Analytics Module can help surface underperforming areas in the processed data.