Paid traffic

Google Ads audit: questions the data should answer

Conduct a Google Ads audit around questions about demand, messaging, landing pages, conversions, sales follow-up, and the next tests to run.

By Anderson, who leads Natander. Editorial reading, with no promise of results

An audit is not an account score

A useful audit does more than mark settings as right or wrong. It asks whether the account reflects the offer, whether the traffic reached is relevant, and whether the available signals support decisions. A campaign can be technically active yet direct traffic to an unsuitable page, optimize for a conversion that does not represent an opportunity, or leave important search terms unreviewed. The diagnosis must connect each configuration to a concrete operational problem.

Start with the business goal and work backward to the platform. List what should happen after the click, what data is available, and where the business must confirm what each signal means. The report should distinguish observed facts, interpretations, risks, and hypotheses. Without this separation, an elegant recommendation can only rearrange the appearance of the panel. An audit becomes useful when the team knows which decision each finding must inform and what evidence will be sufficient.

  1. State the business goal that guides the analysis.
  2. Separate configuration, evidence and interpretation.
  3. Record the period, changes, and sources reviewed.
  4. List questions that data still cannot answer.

Test the integrity of your measurement

Before comparing costs or rates, verify that events are recorded only once, at the right time, and in the right destination. Test forms, phone links, and chat flows; confirm the parameters; and verify that each inquiry reaches the team. Compare what the platform says with operational records, without expecting systems to agree perfectly on all journeys. The difference between sources is a finding that deserves its own explanation.

A technical conversion may be important without representing a qualified opportunity. Document the attribution window, source, counting method, and limitations. If there is loss of consent, browser blocking, redirection or duplication, the auditor should point out the problem and the likely impact without inventing a numerical correction. The report should preserve uncertainty so that the team does not confuse technical adjustment with commercial result or assign revenue without confirmation when necessary.

  1. Reproduce each priority event in a controlled environment.
  2. Check for duplication, parameters, confirmation, and receipt.
  3. Compare events with service records.
  4. Describe attribution limits and missing data.

Evaluate demand, messaging, and landing pages together

The search terms indicate the language and intent that reached the ads. The ads show how the company responded. The page reveals whether the promise was confirmed. Analyze these three layers in sequence, looking for queries outside the scope, generic texts, slow destinations or calls that require more commitment than the information offered allows. The chain helps to locate the exact point where the expectation shifted.

Then compare the message with the service. A campaign may seem consistent and attract contacts that the operation cannot accept by area, deadline or modality. Do not automatically classify the finding as a media problem: it may call for a negative keyword, a new page, an offer adjustment, or sales alignment. The audit should present alternatives and the evidence needed to choose among them. The person responsible can then correct the most likely cause without erasing the context.

  1. Classify search terms by intent and fit.
  2. Link ad and page to the observed term.
  3. Confirm scope, capacity and response in the service.
  4. Specify whether the solution is media, content, operation or measurement.

Deliver priorities that someone can act on

The audit should produce a prioritized action queue, not a loose collection of suggestions. For each finding, record the evidence, risk, dependencies, owner, and next test. Fix problems that distort the data or break the journey first, such as duplicate conversions, broken landing pages, and ads that conflict with the offer. Then treat message and allocation hypotheses. The queue should state the order and acceptance criteria for every item in the final report.

Avoid promising that a change will produce a certain metric. What can be promised is a verification process: publish the change, observe the defined event, gather feedback from the customer-service team, and review the result in context. A mature audit makes clear what has been completed, what remains under investigation and when the next reading will be possible. This precision prevents the customer from receiving a certainty manufactured in a recommendation or report format.

  1. Order findings by impact, confidence, and dependencies.
  2. Assign an owner and validation criteria.
  3. Correct journey failures before testing scale.
  4. Schedule a review without turning a hypothesis into a promise.

Reference sources

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