Filtering and Segmenting Amazon Campaign Data for Fair Conversion Rate Comparisons

Why Blended Metrics Hide Amazon Ads Problems

Most Amazon Ads accounts contain different campaign types, products, and search terms. A single conversion rate across the whole account may look acceptable while specific ad groups or match types are quietly wasting budget. Amazon Ads Dashboard by Todoza is designed to help by consolidating data into one view and allowing reports to be filtered from account level down to search terms.

Without those filters, a high-performing campaign can offset a struggling one. That makes it difficult to tell whether a conversion rate difference is meaningful or just the result of comparing unlike data groups.

Practical Filters and Segments to Use

Before comparing campaign conversion rates, divide the data into segments that reduce noise. Useful ways to filter include:

• Time period: compare the same calendar window across campaigns to avoid seasonal distortions.
• Marketplace and account: separate regions or accounts when pricing, competition, and demand differ.
• Campaign and ad group: isolate branded search, generic search, and product targeting.
• Match type and search term: review close match, loose match, and individual search terms for wasted spend signals.

Amazon Negative Keyword Tool by Todoza imports Search Terms reports and evaluates queries using conversion rate and ROAS signals. Using those segments first makes the comparison far more actionable.

When This Matters Most

Filtering and segmenting is especially useful when deciding which search terms to negate, where to reallocate budget, or how to read a metric over time. A segment can show that one campaign has a low conversion rate only in a specific marketplace or for a specific match type. That changes the next step from pausing the entire campaign to making a narrower adjustment.