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By AI Marketing Entrepreneurship · Published September 29, 2026
Prepared with AI assistance using linked primary sources. Product information reviewed September 29, 2026.
Amazon Ads conversational analytics lets advertisers investigate campaign results through natural-language questions and an interactive visual workspace. Its most useful role is to shorten the path from a performance question to evidence you can check.
Amazon's 28 September announcement describes the experience as a closed beta accessed through Amazon Ads Agent. Eligible advertisers can request access through their representative or the linked waitlist. The announcement lists markets including the Netherlands, but a listed market does not mean every account already has access.
Start with the choice you need to make. “What happened last month?” can produce an interesting summary without helping you decide anything. “Which campaign needs investigation before next week's budget review?” gives the analysis a purpose.
Then set the boundaries. Name the account, marketplace, campaign group, reporting period, and business objective. When comparing periods, use complete periods of similar length and account for unusual trading days.
Write down the metric you intend to use. Return on ad spend, or ROAS, compares attributed advertising revenue with advertising spend. It does not, by itself, show the profit remaining after product costs, returns, or fulfilment.
Our suggested investigation starts with a broad comparison and then tests possible explanations.
An original example prompt is: “Compare these campaigns over the last two complete four-week periods. Show spend, attributed sales, and ROAS using consistent definitions. Identify the largest changes and separate observations from explanations that still need checking.”
Treat an explanation as a hypothesis until the supporting evidence is available. A promotion, a stock problem, or a change in product mix may affect results even when the advertising setup stays the same.
Choose one familiar campaign and reproduce a calculation from a standard report. Check the dates, currency, included campaigns, and attribution settings. If the conversational answer differs, resolve that difference before applying the same method to a larger decision.
Ask which parts of the answer use observed data and which use a benchmark or interpretation. Amazon says the experience combines advertising data with retail signals and benchmarks. Those sources can add context, but they answer different questions.
Keep a record of the prompt and the report settings. A comparison is much easier to repeat when the next reviewer can see exactly what was included.
Suppose the analysis identifies a campaign whose efficiency has declined. The next step could be a focused review of its products and landing experience. It need not be an immediate budget cut.
Write an action note with four fields: the finding, the proposed explanation, the change to test, and the condition for reversing it. This is our recommended decision record, rather than a built-in Amazon feature.
If you do adjust a campaign, avoid making several unrelated changes at once. Record the date and allow enough evidence to accumulate before drawing a conclusion. A conversational interface makes analysis faster to request; it does not make small samples more reliable.
No. The announcement describes closed beta enrolment for eligible advertisers. Check account access through Amazon before relying on the feature.
Use it to guide investigation. For material budget decisions, check the figures and definitions against the relevant reporting records.
Ask a question tied to one decision, with explicit dates, campaigns, and metrics. A narrow question is easier to verify and repeat.
Prepare a reusable list of five questions before joining the beta. You will have a clearer test of its usefulness than an unstructured conversation about the account.
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