Amazon PPC Optimization: Evidence-Led Campaign Review

Automatic and manual Amazon Ads campaigns can serve different purposes. The right structure depends on the seller's product economics, search-term evidence, placement results, inventory, and approved objectives; no campaign type universally produces a better ACoS.

Define each campaign's purpose

Document whether a campaign is for discovery, a validated query, branded coverage, product targeting, or another client-approved purpose. Keep reporting legible enough to explain where spend and attributed sales came from.

Review search terms

Use seller-authorized search-term and bulk reports. A candidate movement from automatic or broad discovery to a manual campaign should state the source period, product margin, match type, current result, proposed bid and budget, and the reason. A cheap click or one attributed order is not universal proof of repeatable demand.

Use negative keywords carefully

Review product intent and campaign purpose before adding a negative. Record the affected campaign, match type, evidence, and approver. Human review is required because an automated candidate can block relevant traffic.

Measure the approved change

Agree a suitable review period based on traffic, attribution, seasonality, and data quality. Compare ACoS, TACoS context, spend, attributed sales, and contribution assumptions without claiming that one structure caused all movement.

BFarm provides written recommendations with reasons and applies advertising changes only after client approval. Results and timing are not guaranteed. See the Advertising Optimization service, negative-keyword framework, and budget-allocation framework.