An Amazon PPC audit checklist that leads to action

An Amazon PPC audit should explain where money goes, what each campaign is meant to achieve, and which changes deserve attention first. A list of high-ACOS targets is only one part of that work. Some campaigns protect existing demand. Others test new demand. Their results need context.

This checklist combines Alfredo's account-audit walkthrough with the repeatable checks in his automated-audit breakdown. The work starts before bids change and ends with an action log that a person can inspect.

Collect the reports and cost inputs

Start with a bulk campaign export, search-term data, product-level business reports, and current product economics. Include campaigns, ad groups, advertised ASINs, targets, bids, match types, statuses, negatives, and budgets. Use identifiers to join records; campaign names alone are often inconsistent.

Compare a recent period with a longer one to distinguish new changes from recurring patterns. The transcript uses 30- and 90-day views as a practical starting point. Adjust for the account's volume, seasonality, and major events rather than treating either window as a universal rule.

Record which costs are included in the margin calculation. Fees, cost of goods, refunds, and promotions can change what a sale can support. Use product-level ACOS targets instead of assigning one round-number threshold to the catalog.

1. Map products and campaign purposes

For each important ASIN, identify the campaigns that advertise it and the purpose of each: branded defense, non-branded acquisition, discovery, competitor targeting, or another defined role. Then compare that structure with stock availability, margin, and the product's business priority.

Flag unexplained overlap, unsupported products, and campaigns whose purpose nobody can describe. Repeated targets can fragment reporting or make ownership unclear. Their presence alone is not proof that you are increasing your own auction price. Review intent and performance before consolidating.

Complexity is not evidence of quality. A small account may need fewer campaigns than a large catalog. Our campaign structure guide explains when separate control earns its place.

2. Follow spend into actual search terms

Split branded and non-branded search terms, then inspect the spend distribution inside each campaign. A campaign labeled “growth” may spend most of its money on people already searching for the brand. Its blended ROAS will not show whether category acquisition is working.

The source audit illustrates that mismatch. Use it as a question to ask in your account, not a benchmark for how much branded spend every business should have. Brand defense can serve a valid purpose, but it should have a visible budget and a clear reason.

Check whether a small number of terms absorbs the budget intended for a wider test. Record which products and queries receive little evidence because other targets consume the available spend.

3. Check relevance and control

Read the actual query and inspect the advertised product. Does the size, material, use case, or compatibility match what the shopper wants? A click can be technically relevant to the category and still lead to the wrong variation.

Compare performance across automatic and manual targeting without declaring one type inherently wasteful. Amazon's Sponsored Products targeting guide describes automatic targeting as both a delivery and discovery option, with control through targeting-group bids. Manual targeting adds explicit keyword or product selection.

Consider giving repeat converting terms more direct control when that would improve budgeting or decision-making. Preserve the discovery role where it still produces useful information. The audit should explain why a structural change helps, not simply move everything into exact match.

4. Review wasted spend and expensive orders

Separate irrelevant terms from relevant terms that have not yet converted. Irrelevance can justify exclusion quickly. A relevant term needs a judgment based on clicks, spend, expected conversion, attribution maturity, and campaign purpose. Avoid applying a fixed click cutoff to every product.

For converting targets above the product's allowance, investigate click cost, conversion, and the offer before deciding whether to reduce bids or stop delivery. A target with orders is not automatically profitable; a discovery target with early losses is not automatically useless.

Review existing negatives too. Check their scope and whether they block useful demand. Record the intended effect of a negative so the next operator can understand the decision.

5. Find constrained opportunities

Check campaigns that perform within their targets but lose delivery to budget constraints. Verify the constraint through available budget and delivery information; spending near a daily limit alone is not enough to estimate missed sales.

Also inspect products with strong overall conversion and little advertising support. That may justify a controlled test. It does not prove that adding spend will produce the same conversion rate as existing traffic. Confirm inventory, economics, and the source of current demand first.

Turn findings into a reviewable action log

For every finding, record the evidence, affected ASIN or target, proposed change, owner, priority, and review date. Separate measured waste from estimated opportunity. Forecast revenue and savings remain estimates until changes run and results can be assessed.

Automated checks can help identify missing coverage or unusual spend. Keep their output traceable to the source data and review recommendations before applying them. The useful deliverable is a short sequence of justified changes, not an unexplained letter grade.

Start with clear relevance problems and business constraints, then test structural and budget changes. Read how to optimize Amazon ads for the ongoing process after the audit.