The most overlooked lever in Alexa for Shopping, and how brands can use it to get recommended

To get recommended by Alexa for Shopping, your product page needs to answer the questions shoppers ask, because the assistant answers from listing details, customer reviews and community Q&A. Premium A+ Q&A is the part of the page built for those answers, and many brands leave it blank.

Azoma is an agentic commerce optimization platform, and across the Amazon catalogs we review for brands, we often see the Premium A+ Q&A module left blank, even where the brand already has access to Premium A+. It is the one part of an Amazon detail page written in the same shape as a shopper’s question. Since Amazon renamed Rufus as Alexa for Shopping on May 13, 2026, the assistant answers those questions on the page itself, which makes a blank Q&A module one of the clearest gaps a brand can close.

What is the Premium A+ Q&A module?

The Premium A+ Q&A module is a section of the Amazon product detail page where a brand publishes questions and its own answers. Amazon’s A+ Content design guide lists Q&A sections among the modules Premium A+ adds, alongside video, interactive hotspots, carousels and enhanced comparison charts. Premium allows up to seven modules per ASIN, against five for Basic A+.

Amazon advises building the section from repeating themes in reviews, covering features, usage and compatibility. It also tells brands to keep text out of images, for mobile readability. The answers therefore belong in the module’s text fields, where people and machines can both read them.

Premium A+ is open to registered brands that meet Amazon’s eligibility criteria, which Seller Central shows per account. Amazon’s internal data puts the sales lift from well-implemented Premium A+ at up to 20%.

Why do brands leave the Premium A+ Q&A module blank?

Brands most often leave the Q&A module blank because A+ is briefed as visual brand storytelling, while Q&A needs factual answers from several teams. A useful answer to “does this fit a 2019 model?” or “is this safe for sensitive skin?” usually needs sign-off from product, regulatory and customer care. That makes the Q&A the module most likely to be postponed when a brand builds its A+ content.

The cost of that gap has grown in 2026. Shoppers still get an answer to a question the page leaves open, and it comes from reviewers or rival listings.

Why does the Premium A+ Q&A module matter for Alexa for Shopping?

The Premium A+ Q&A module matters because Alexa for Shopping answers shoppers’ questions from what Amazon holds about each product. On May 13, 2026, Amazon renamed its Rufus shopping assistant Alexa for Shopping, combining it with Alexa+. Alexa for Shopping now takes questions in the main Amazon search bar and writes AI overviews on product detail pages.

The reach is large. Rufus was used by more than 300 million customers in 2025, according to Amazon’s Q4 2025 results. Amazon’s Rufus launch announcement, now updated with the rename, says product answers draw on listing details, customer reviews and community Q&As, plus information from across the web.

A brand that writes the answer on its own page supplies the wording Alexa works from. Answer the question before the shopper asks it, and Alexa has your words to work with.

What Alexa for Shopping draws on, stated by Amazon and measured by Azoma. Amazon announcement February 2024, updated May 2026; citation shares September 2026. Sources: Amazon; Azoma platform.

➡️ Book a call with our team to see what Alexa for Shopping says about your products today.

Which questions belong in your A+ Q&A? 

The questions that belong in your A+ Q&A are the high-volume questions in your category that your page does not yet answer. Each answer should agree with everything else Alexa reads about the product.

1. Start from demand 

Build the question list from what shoppers already ask, before anyone writes an answer. Three sources do most of the work:

• Alexa’s suggested questions. On many product pages, Alexa for Shopping shows prompts shoppers can tap, such as “Does it have a strong scent?” or “Is this shampoo good for curly hair?”. Record them for your ASINs and your top competitors’ ASINs, because they show what Alexa expects shoppers to ask in your category.

• Review summaries and recurring objections. Amazon’s AI-generated “Customers say” summaries flag topics where feedback is mixed, such as frizz control or how heavy a product feels. A mixed topic is a question shoppers are still asking, so it belongs in your Q&A.

• Search terms and community Q&A. Amazon Brand Analytics shows the phrases shoppers type, and existing community questions show what buyers needed to know before they bought.

Then group the questions by the need behind them. COSMO, the commonsense knowledge graph behind Amazon’s product understanding, links each product to relations such as who it is for (used_by), what it pairs with (used_with) and what it contains (has_part). Grouping your questions by these relations shows which parts of that graph your Q&A fills.

Mapping shopper questions to COSMO relation types, examples illustrative.

2. Find the gaps 

Check every question against your title, bullets, description, backend attributes and A+ content, and mark each one as answered clearly, answered vaguely or unanswered. The unanswered questions and the mixed review topics go into the Q&A first. Start with five strong questions per ASIN, and expand once you can see which ones change what Alexa says.

A weak and a strong A+ Q&A pair. Example illustrative.

Cover limits as well as benefits. Questions about fit, edge cases and who a product suits least are the ones shoppers most need answered before they buy. They are also the ones brand copy most often skips.

3. Check that Alexa gets it right 

Ensure Alexa for Shopping surfaces the right answer, and the right products, when shoppers ask. Ask Alexa each question from your Q&A on your product page and in the search bar, then compare what it says with the answer you approved. Note anything it gets wrong, such as a missing claim, an outdated ingredient, the wrong hair type or a competitor recommended for a need your product meets.

Then trace each error to its source and fix it there. The cause is usually a conflicting backend attribute, an old bullet, a recurring review complaint or an outside article with outdated details. Make the same fact read identically across your title, bullets, attribute dropdowns, A+ content and brand.com, so every source Alexa reads points to the same right answer.

How do you measure the impact of A+ Q&A optimisations?

Record a baseline before the module goes live: for each question, note whether your product is named, where it ranks, what reason Alexa gives and how it describes the product. Re-run the same questions once Amazon approves the A+ content, and compare the results against ASINs you left unchanged. 

Use Amazon’s Manage Your Experiments tool to A/B test the A+ content itself, so you can see conversion alongside visibility.

If you’d like to do this at scale, Azoma can help.

Screenshot from the Azoma dashboard with optimisations for the Premium A+ Q&A

The platform shows your share of voice in Alexa for Shopping, re-running your category’s questions daily so you can see exactly when your products start being named. Our team also helps you produce optimized A+ Q&A, built from the questions shoppers ask and checked against what Alexa says. 

In Azoma’s work with a premium haircare brand, Alexa for Shopping visibility across 10 SKUs rose 217% after PDP optimization that included A+ FAQs. 

Book a call with our team to see where your products stand today. 

Summing Up

The Premium A+ Q&A module is the easiest gap on an Amazon detail page to see and one of the quickest to close. Alexa for Shopping explains its recommendations from what Amazon holds about each product, and the Q&A module is where a brand answers shoppers’ questions in its own words.

The method is short. Find the questions your category asks, answer the ones your page leaves open, keep every answer consistent with the rest of the listing, and check what Alexa says afterwards.

FAQs

How do I get recommended by Alexa for Shopping?

Alexa for Shopping recommends products using listing details, customer reviews and community Q&A, so the first step is to make sure your product page answers the questions shoppers ask. Fill the Premium A+ Q&A module with direct answers to your category’s highest-volume questions, and keep those answers consistent with your bullets and attributes. Earned and affiliate publishers supplied 87.6% of Alexa for Shopping citations from July to September 2026 (Azoma platform), so coverage on those sites matters too.

How can I see what Alexa for Shopping says about my products?

Alexa for Shopping shows you its view of a product when you ask it questions on the product page and in the Amazon search bar. Ask the same questions on your page and on your top competitors’ pages, note the suggested questions Alexa offers, and repeat on a schedule. Across a large catalog, a tracking tool that re-runs the same prompts daily and stores the full answers makes this manageable.

How do I optimize a large Amazon catalog for Alexa for Shopping?

A large Amazon catalog is best handled by prioritizing the ASINs where Alexa for Shopping already recommends another product on your highest-volume questions. Build one question set per product family, then write answers specific to each ASIN where the model, size or formulation changes the answer. Azoma helps catalog teams spot those ASINs quickly and produce optimized A+ Q&A across whole product families, so the work starts where it will make the biggest difference.

What should I look for in an Alexa for Shopping optimization tool?

An Alexa for Shopping optimization tool should show you what the assistant says about your products, measured repeatedly. Look for daily re-runs of the same prompts, answers captured in the regions you sell in, and mentions, rank, sentiment and citations recorded for every answer. Azoma, an agentic commerce optimization platform, does this at scale across Alexa for Shopping, Walmart Sparky and ChatGPT, so you can track your share of voice and see where your products stand.