Surface Duplicate Entries Quickly for Targeted Action

Sort and group the export before cleanup

Start by normalizing the columns that matter for your account, such as date range, campaign name, ad group, keyword or search term, and match type. Then sort or filter on the text fields where duplicate values most often appear. This makes repeated rows visible before you spend time on individual line items.

For larger reports, a module that processes campaign, ad group, target keyword, search term, and advertised product level data can do this grouping across many accounts. The key is to separate true duplicates from legitimate repeat performance across different dates or placements.

Build a targeted action queue from flagged entries

Grouped duplicates become useful when they are connected to an action. For search term cleanup, the Amazon Negative Keyword Tool by Todoza ranks search terms from Amazon Ads reports and evaluates them with campaign-specific signals rather than one fixed threshold. That helps you prioritize which repeated or low-value terms to review first.

• Route duplicate search terms into a single cleanup queue.
• Compare performance by campaign, not just a global account average.
• Keep the process read-only until a team member approves negative keywords or bid adjustments.

When this matters

This matters most when you are comparing ROAS or wasted spend across multiple accounts or marketplaces. Duplicate rows can inflate totals, create false trend lines, or make a campaign look more efficient than it is. A unified dashboard view that consolidates report types can highlight those inconsistencies before they affect budget decisions.

It is also valuable for teams that manage ad spend across several Amazon marketplaces. Marketplace-specific signals are more useful than a single account-wide rule when deciding which entries to act on.