Automation does not fix a broken account. It makes the account run faster. If the campaigns are built on a weak structure, the targeting is scattered, and the spend is going to irrelevant search terms, adding rules and scheduling on top of that accelerates the problem rather than solving it. The 10-point audit below is what should happen before any automation tool gets connected.
This is not a data analysis checklist. It is a structural audit, the kind of review that answers the question: is this account built correctly enough to trust rules running against it unsupervised? Most of the items take less than 15 minutes each. Running through all 10 in a single session gives you a clear picture of what to fix before you build anything automated on top.
1. Campaign naming conventions
Open your campaigns list and ask one question: can you understand what each campaign is targeting just from its name, without clicking into it? A campaign called "Auto Campaign 3" tells you nothing. A campaign called "SP | Exact | Insulated Bottles | Top Sellers" tells you the ad type, match strategy, product category, and intent tier at a glance.
Automation rules need to reference the right campaigns. Poorly named campaigns make it impossible to build rules with confidence and increase the risk of targeting the wrong set. Fix the naming before you add any rules. A consistent structure like [Ad Type] | [Match Type] | [Product/Category] | [Goal] works for most accounts.
2. Match type separation
Exact, phrase, and broad match keywords should live in separate campaigns, not mixed together in the same ad group. When match types are mixed, you cannot set bids by intent, you cannot analyze performance by match type cleanly, and you cannot build budget or dayparting rules that apply to one match tier without affecting the others.
Pull your campaign list and check: are match types separated at the campaign level? If not, this is the most impactful structural fix in the audit. The guide on what to automate covers why match type structure is the foundation everything else rests on.
3. Duplicate keywords
The same keyword appearing in multiple campaigns means you are bidding against yourself in the same auction. It inflates your average CPC, makes it impossible to read keyword-level performance cleanly, and fragments the conversion history that Amazon uses to rank your ads.
Download your keyword targeting report across all campaigns and run a duplicate check. Any keyword that appears in more than one campaign at the same match type needs to be resolved, either by consolidating into the intended campaign or by adding the keyword as a negative in the campaigns that should not be targeting it.
4. Budget utilization and pacing
Check your last 30 days of daily budget data. Which campaigns are consistently hitting their daily budget before the end of the day? A campaign that exhausts its budget at 11am every day has a pacing problem that no amount of scheduling will fix. The budget cap is stopping it from running during your best afternoon hours.
This is one of the most common signs that an account needs budget rule attention before dayparting attention. Wasted spend and early budget exhaustion are often two sides of the same problem: budget going to low-converting early hours, leaving the high-converting afternoon window underfunded. Budget rules can address the timing, but only after you know which campaigns have a utilization problem versus a spend efficiency problem.
5. Search term report review
Download your search term report for the last 60 days. Sort by spend, descending. Look at the top 20 search terms by spend and ask: how many of these have zero conversions? Any search term spending more than two to three times your target cost-per-acquisition without a conversion is wasted spend. If your target ACoS implies a cost-per-order of $8, a search term with $25 in spend and no sales needs a negative keyword.
This is the fastest way to find recoverable budget. Most accounts that have never done a search term audit are sending 15 to 30% of their spend to irrelevant queries. Cleaning this up before adding automation rules means the rules are working with clean signal rather than polluted data.
6. ACoS by campaign
Pull your 30-day ACoS at the campaign level. For each campaign, compare the ACoS to your target. Flag every campaign that is running more than 20% above target and has more than $50 in spend. These are the campaigns where something structural is wrong: wrong match type, too many irrelevant keywords, bids set too high relative to conversion rate.
Understanding what a good ACoS looks like for your margin structure matters here. A 40% ACoS on a product with 70% gross margin is fine. A 40% ACoS on a product with 30% gross margin is a money-losing campaign. The flag is not absolute ACoS, it is ACoS relative to your target. Performance rules built on ACoS thresholds need this target clearly defined before they can be set correctly.
7. Hourly performance data
Pull at least 30 days of hourly data from the Amazon Ads console (Portfolios report with hourly breakdown, or the Campaign Report with hour segmentation). Look for the hours where spend is consistently above your account average spend-per-hour but conversions are zero or near-zero.
This is the data that drives dayparting decisions. If you do not have 30 days of hourly data, wait until you do before building a dayparting schedule. A schedule built on two weeks of data can be skewed by a promotional period or a weekend-heavy sample. Thirty days captures enough variation to see a stable pattern.
8. Placement performance
In your campaign reports, check the placement breakdown: top of search, product detail pages, and rest of search. Compare conversion rates and ACoS across placements for your highest-spend campaigns. You may find that your top-of-search placement converts at half the rate of product detail page clicks, or vice versa.
Amazon's placement bid adjustments let you raise or lower bids by placement. If product detail pages consistently convert better for your account and you are not adjusting for that, you are treating placements as if they are equivalent when they are not. This is especially important before adding budget or performance rules, because placement efficiency affects the account-level ACoS signal those rules will be reacting to.
9. Negative keyword coverage
A well-maintained account has negatives at both the campaign and ad group level. Common gaps: no negatives at the campaign level (relying entirely on match type to exclude irrelevant traffic), branded terms not negated in competitor-targeted campaigns, and category terms negated too broadly, cutting off relevant traffic along with the irrelevant.
Pull your negative keyword list and compare it against the irrelevant search terms you found in step five. Any search term spending money without converting that is not already negated should be added to the list before you finalize this audit.
10. Automation readiness
The final check is a summary question: given what you found in the first nine items, is this account ready to have rules running against it without daily supervision?
The test is straightforward. If a dayparting rule pauses your campaigns during the dead overnight window, will it be pausing campaigns that are targeting the right things during the active window? If a performance rule pauses a campaign that exceeds an ACoS threshold, is the ACoS signal clean enough to trust, or is it inflated by irrelevant search terms that should have been negated?
The eight automation rules worth building for most accounts become genuinely useful only when the structural issues in items one through nine are resolved. An account that clears all 10 checks is ready for automation to extend the team's capacity. An account that fails several of them will have automation amplify its existing problems.
Parkway Home, a home goods brand managing 22 active campaigns, ran through this audit before connecting Off Hours and found that four campaigns had duplicate keywords consuming about 12% of the account's budget, and that the overnight window (midnight to 5am) was responsible for 9% of spend with zero attributed orders in the prior 30 days. Resolving the duplicates and building the dayparting schedule together recovered more budget than either fix alone would have, because the spend freed from duplicates stayed in the account rather than being reallocated to the same bad hours.
Frequently asked questions
How often should you audit your Amazon PPC account? A full structural audit is worth doing quarterly, or any time you are about to make a significant change like adding automation, restructuring campaigns, or onboarding a new tool. Lighter weekly reviews of performance metrics, search term reports, and budget utilization are separate from a structural audit and should be part of normal account maintenance.
What does an Amazon PPC audit cover? A thorough audit looks at campaign structure and naming conventions, match type separation, duplicate keywords, budget utilization and pacing, search term analysis for wasted spend, ACoS by campaign, hourly performance data, placement performance, negative keyword coverage, and overall automation readiness. Some audits also check keyword bid competitiveness and whether the account structure supports clean reporting.
How long does an Amazon PPC audit take? For a mid-size account with 10 to 30 active campaigns, a thorough structural audit takes two to four hours the first time. Subsequent audits on the same account are faster because you are checking for drift from a known baseline. Agencies auditing a new client account typically spend a full day on the initial review before touching any settings.
Once your account passes this audit, Off Hours builds the dayparting and budget rules that run the scheduling side automatically. 14-day free trial, no credit card required. Start here.