Amazon's Rufus Prompt Report is not a replacement for the search-term report yet. It is earlier than that. It shows the natural-language questions Amazon is willing to connect to your advertised products inside Rufus and prompt-based shopping surfaces.
That matters because search-term reports tell you what shoppers typed after they already knew roughly what to search. Prompt reporting starts to show how shoppers describe the problem, feature, comparison, or use case before the keyword is obvious.
For Amazon sellers, the move is simple: do not wait for Rufus volume to become large before studying the report. Small prompt data can expose listing gaps, FAQ gaps, A+ Content gaps, and PPC keyword ideas while competitors still think AI shopping is a side feature.
Key Takeaways
- The Amazon Rufus Prompt Report shows prompts that received clicks, tied to the associated ad and performance metrics.
- Amazon says sellers can find prompts in Ads Console under Campaign, Ad Group, Ads, then the Prompts tab.
- Prompt data is not the same as keyword data. It is closer to shopper language before it gets compressed into a search term.
- Low click volume does not make the report useless. Early prompts can show what Amazon's AI thinks your product answers.
- Sellers should map prompt language into listing copy, A+ modules, Q&A, PPC keywords, and negative keyword reviews.
What does the Amazon Rufus Prompt Report actually show?
The report shows prompt text, the related ad, and performance metrics for prompts that have received clicks.
Amazon's own update says Sponsored Products and Sponsored Brands campaigns are automatically enrolled in prompts and use existing campaign parameters such as targeting. Amazon also says sellers and vendors can review and manage prompts in Ads Console or by API, and that the Prompts tab lists prompts that received a click with metrics such as impressions, clicks, and orders (Amazon Ads).
That is the receipt. This is not a rumor buried in a forum thread. Amazon has turned prompt-based ads into a managed surface inside its advertising system.
The economic point is that prompt reporting gives you a new read on paid discovery. If a shopper clicks a prompt like "which protein powder is best for sensitive stomachs," that is not just a phrase. It is a use case, an objection, a feature filter, and maybe a conversion blocker sitting in one line.
Decision: treat the report as a diagnostic layer, not a dashboard trophy. Pull the prompts monthly, group them by buyer question, and ask what each one says about your detail page.
Where do sellers find Rufus prompts in Advertising Console?
Amazon says the path is Campaign, Ad Group, Ads, then Prompts.
That detail matters because many sellers will not see a big new report sitting on the home screen. The data is campaign-level and prompt-level, which means a lazy account review can miss it entirely.
Intentwise reported that advertisers started seeing a Sponsored Prompts tab in Ad Console and that Amazon was beginning to show which prompts led to clicks, with impressions, clicks, and purchases attached to the prompt data (Intentwise). Amazon's official rollout later confirmed the Prompts tab location and the same basic metric set.
If you manage a large catalog, the first mistake is checking one hero campaign and assuming the account has no data. Prompts may appear only where Amazon has generated and served eligible prompt units, and Amazon's own wording says prompts are listed if they have received a click.
Decision: check by campaign cluster. Start with Sponsored Products and Sponsored Brands campaigns for your top ASINs, then compare prompt coverage against your highest-margin SKUs. If the report exists for low-margin products but not for your profit drivers, that is a planning problem.
Why is prompt data different from a search-term report?
A search-term report shows the query that triggered ad activity. Prompt data shows the question Amazon placed in front of a shopper, or the question format Amazon believes connects a shopper's need to a product or brand.
That is a different type of intent.
Traditional Amazon PPC forces messy human needs into short phrases: "kids lunch box," "stainless bento," "leak proof lunch container." Rufus-style prompts can preserve more of the real buying context: "is this lunch box easy for a five-year-old to open" or "which bento box does not leak in a backpack."
Amazon describes prompts as a 24/7 virtual product expert that can surface relevant details before shoppers need to ask questions, with prompts appearing in shopping results and product detail pages. When clicked, prompts may open a Rufus dialog or answer directly on the page (Amazon Ads).
The economic point is ugly but useful: if Rufus is surfacing prompts around questions your listing does not answer, your ad may pay to expose uncertainty instead of resolve it. That can depress click-through, conversion, or both.
Decision: do not dump prompt text straight into exact-match campaigns. First classify each prompt as feature intent, comparison intent, objection intent, compatibility intent, or audience intent. Then decide whether the fix belongs in PPC, listing copy, A+ Content, or Q&A.
How should sellers turn prompts into listing changes?
Start by treating every prompt as a question your product page either answers, half-answers, or dodges.
If the prompt asks about a feature, the detail page should name the feature in plain language. If it asks about a use case, the images and A+ Content should show that use case. If it asks about compatibility, size, fit, safety, ingredients, materials, or setup, the answer should not be buried in a lifestyle paragraph.
PPC Ninja shared early beta examples where Amazon generated comparison and feature-specific prompts from listing data, reviews, and product attributes. That third-party example is useful, but the safer operating assumption is still Amazon's official description: prompts draw from your existing campaigns and show product information to shoppers at decision moments (PPC Ninja, Amazon Ads).
Here is the workflow ALFI would use on a client account:
- Export prompts by campaign and ASIN cluster.
- Tag each prompt by intent type.
- Mark whether the answer appears in the title, bullets, images, A+ Content, Q&A, or reviews.
- Rewrite the missing answer in the most visible location first.
- Recheck prompt performance the next month.
Do not over-edit the listing because one prompt appeared once. That is how sellers turn a clean page into keyword soup. Use prompt data as a pattern detector, not as a command.
Decision: if a prompt maps to a high-margin ASIN and a repeated buyer concern, fix the listing before increasing bids. Better information often beats louder advertising.
How should prompts affect PPC keywords and negatives?
Prompts should feed PPC, but not blindly.
A prompt can expose a new keyword theme, especially when shoppers describe an outcome instead of a product name. For example, "best magnesium for sleep without grogginess" might point to search terms around sleep support, non-melatonin alternatives, or morning side effects.
But prompts can also reveal bad-fit traffic. If a prompt asks for a feature your product does not have, that is not a content gap. It is a negative keyword or campaign exclusion candidate.
This is where the search-term report and prompt report need to sit beside each other. The search-term report tells you what already spent. The prompt report tells you what Amazon's AI is trying to connect to the shopper conversation. The overlap is where you harvest. The mismatch is where you protect margin.
Decision: build a monthly prompt review with four columns: keep, test as keyword, answer in content, block or down-rank. If the same prompt theme appears beside poor conversion, do not celebrate the traffic. Fix the relevance leak.
What should brands track before AI shopping volume becomes obvious?
Track prompt coverage, prompt quality, prompt economics, and content fixes.
The wrong move is waiting for prompt spend to become material. By then, the expensive part has started. Amazon says Sponsored Products prompts and Sponsored Brands prompts moved from open beta to general availability in the U.S. and will be charged as part of CPC bidding and billing parameters (Amazon Ads).
That means the free-learning window is narrowing or already gone for many sellers. The brands that build the review habit now will know which prompts deserve budget, which prompts need content support, and which prompts should be paused.
Track these monthly:
- Prompts with impressions but low clicks.
- Prompts with clicks but weak order rate.
- Prompts tied to high-margin products.
- Prompts that reveal missing content.
- Prompts that attract shoppers your product should not serve.
- Prompts that overlap with converting search terms.
At ALFI, this belongs beside contribution margin by SKU. A prompt that drives revenue but sends traffic into a thin-margin product is not automatically good. A prompt that helps a premium SKU answer the right pre-purchase question may be worth defending even at a higher CPC.
Decision: score prompt themes by profit potential, not curiosity. If the prompt does not help a product you want to grow, it does not deserve much operator time.
How should agencies and operators review this every month?
The review should be short, senior, and connected to margin.
This is exactly where large-agency reporting can get lazy. A junior account manager can paste a screenshot of the Prompts tab and call it innovation. That does not help the brand. The useful work is deciding what to change and what not to chase.
A real monthly review should answer five questions:
- Which prompt themes appeared for our top ASINs?
- Which themes are commercially valuable?
- Which themes expose missing listing content?
- Which themes should become keyword tests or negatives?
- Which themes are not worth touching because the unit economics are weak?
That is the ALFI angle on Rufus reporting. AI-shopping data only matters when it changes a decision. If you want someone to review prompt data through listing quality, PPC structure, and contribution margin together, book a call at /contact/.
What is the Amazon Rufus prompt report?
The Amazon Rufus Prompt Report is the prompt-level reporting view for Sponsored Products prompts and Sponsored Brands prompts. Amazon says it shows prompt text, the associated ad, and metrics such as impressions, clicks, and orders when prompts have received clicks.
Is the Rufus Prompt Report the same as the search-term report?
No. A search-term report shows shopper queries that triggered ads. Rufus prompt reporting shows prompt language connected to AI-shopping surfaces. Use both, but do not treat them as the same signal.
Should I add every prompt as a PPC keyword?
No. Some prompts are useful keyword ideas. Others are content gaps or bad-fit traffic. Classify the prompt first, then decide whether it belongs in keywords, listing copy, A+ Content, Q&A, negatives, or no action.
What if my account has very little prompt data?
That is normal at this stage for many accounts. Check campaign by campaign, especially across Sponsored Products and Sponsored Brands. If volume is still low, use the data you do have as directional input and review it monthly.
Can sellers turn off specific prompts?
Amazon says sellers can review, manage, and pause prompts in Ads Console. Intentwise also reported that advertisers can enable or disable specific prompts from the Prompts tab.
When should I ignore prompt data?
Ignore it when the prompt is a one-off, tied to a low-margin product, or clearly mismatched to what the product does. Acting on every prompt creates bloated listings and messy campaigns.
What to do this week
- Open Ads Console and check the Prompts tab inside your top Sponsored Products and Sponsored Brands campaigns.
- Export or record every prompt that has clicks, impressions, or orders.
- Group prompts by feature questions, comparison questions, buyer doubts, fit questions, and audience use cases.
- Pick the top three prompt themes tied to high-margin ASINs.
- Fix missing answers in bullets, images, A+ Content, or Q&A before raising bids.
- Add only the best prompt themes to PPC tests, and mark bad-fit themes for negatives or prompt pausing.
- Review the same report next month beside search terms and SKU-level contribution margin.
