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01 The brief
A UK health brand wanted to know whether listings written for the questions shoppers ask Alexa for Shopping would win more of its answers. Before the work it was number 2 in its lead category.
Source: Lexym Rufus Visibility Tracker, Amazon UK, before window. Lmo7 calculation.
02 What we did
Map the questions
We mapped 50 unbranded shopper questions (25 per category, two categories).
Rework six listings
We rewrote six listings: copy, structured attributes and A+ FAQs.
Track from a clean account
We asked the questions several times a day from a clean Amazon account with no purchase history, for 4 weeks before go-live and 4 weeks after.
Log every change
We logged every price, deal, ad and Buy Box change alongside the results.
how we measure Alexa for Shopping answers
why answers get redrawn every night
Lexym Rufus Visibility Tracker, Amazon UK, 50 unbranded questions (25 per category) asked several times a day from a clean account. Before: 4 weeks. After: 4 weeks. Aug to Oct 2026. Lmo7 calculation.
03 What moved in Alexa for Shopping
Across both categories, the brand's products appeared as product cards in more answers. Category A rose from 53% to 61% (+8 points, +15% relative). Category B rose from 58% to 66% (+8 points, +14% relative).
Answers showing the brand's products as product cards
| Category | Before (4 weeks) | After (4 weeks) | Change |
|---|
| Category A | 53% | 61% | +8 pts (+15%) |
|---|
| Category B | 58% | 66% | +8 pts (+14%) |
|---|
Lexym Rufus Visibility Tracker, Amazon UK, 50 unbranded questions (25 per category) asked several times a day from a clean account. Before: 4 weeks. After: 4 weeks. Aug to Oct 2026. Lmo7 calculation.
5 of the 6 reworked products appeared in more answers.
Lexym Rufus Visibility Tracker, Amazon UK, 50 unbranded questions (25 per category) asked several times a day from a clean account. Before: 4 weeks. After: 4 weeks. Aug to Oct 2026. Lmo7 calculation.
The biggest gains came on buying questions with a specific need behind them. The share of answers naming the brand rose by 20 to 28 percentage points.
Share of answers naming the brand on specific-need buying questions, change in percentage points
| Specific-need buying questions | Change in percentage points |
|---|
| for a specific age group | +28 |
|---|
| easy-to-take format | +28 |
|---|
| for a specific health need | +28 |
|---|
| for a specific gender | +27 |
|---|
| taste | +20 |
|---|
Lexym Rufus Visibility Tracker, Amazon UK, 50 unbranded questions (25 per category) asked several times a day from a clean account. Before: 4 weeks. After: 4 weeks. Aug to Oct 2026. Lmo7 calculation.
How-to questions behave differently. These are questions such as how many a day, daily use and take with food. In August, 20% of answers named no brand at all (1 in 5). In September to October that rose to 71% (7 in 10). From early September, answers also got about 14% shorter.
Lexym Rufus Visibility Tracker, Amazon UK, 50 unbranded questions (25 per category) asked several times a day from a clean account. Before: 4 weeks. After: 4 weeks. Aug to Oct 2026. Lmo7 calculation.
78% of how-to answers that named a brand named this one.
Lexym Rufus Visibility Tracker, Amazon UK, 50 unbranded questions (25 per category) asked several times a day from a clean account. Before: 4 weeks. After: 4 weeks. Aug to Oct 2026. Lmo7 calculation.
How-to answers naming no brand at all
| Period | Share of answers |
|---|
| August 2026 | 20% |
|---|
| September to October 2026 | 71% |
|---|
Lexym Rufus Visibility Tracker, Amazon UK, 50 unbranded questions (25 per category) asked several times a day from a clean account. Before: 4 weeks. After: 4 weeks. Aug to Oct 2026. Lmo7 calculation.
04 What moved in sales
We compared the 38 days before go-live with the 38 days after. Price, deals and ad spend also changed in this period, so read the sales figures as a strong direction, not proof.
Product page views on the six reworked listings vs the rest of the catalogue
| Listings | Product page views |
|---|
| Six reworked listings | +9% |
|---|
| Rest of the catalogue | minus 12% |
|---|
Price, deals and ad spend also changed in this period, so read the sales figures as a strong direction, not proof.
Amazon sales and traffic data, client account, Amazon UK, 38 days before vs 38 days after go-live, Aug to Oct 2026. Lmo7 calculation. Price, deals and ad spend also changed in this period.
Glance-view conversion up to 28% higher on the two cleanest listings
| Listing | Before | After | Relative change |
|---|
| Listing 1 | 35.5% | 41.5% | +17% relative |
|---|
| Listing 2 | 20.3% | 25.9% | +28% relative |
|---|
Price, deals and ad spend also changed in this period, so read the sales figures as a strong direction, not proof.
Amazon sales and traffic data, client account, Amazon UK, 38 days before vs 38 days after go-live, Aug to Oct 2026. Lmo7 calculation. Price, deals and ad spend also changed in this period.
One product, two markets
| Market and listing | Units |
|---|
| UK, listing reworked | +21% |
|---|
| EU markets, listing not changed | minus 23% |
|---|
Price, deals and ad spend also changed in this period, so read the sales figures as a strong direction, not proof.
Amazon sales and traffic data, client account, Amazon UK and EU markets, 38 days before vs 38 days after go-live, Aug to Oct 2026. Lmo7 calculation. Price, deals and ad spend also changed in this period.
05 What this means for your brand
As Alexa for Shopping answers get shorter, the product cards that remain go to listings that answer a specific buyer need: who it is for, format and taste. In this case the gains came where the listing answered the question directly.
This is the quick-win track: listing copy, structured attributes and A+ FAQs. It does not replace the long game. On Amazon that means reviews, ratings and sales history. Off Amazon it means citations and authority for ChatGPT and Google. If you are weighing paid AI placements, the same order applies: audit organic AI visibility first.
We track this for brands with Amazon Rufus Radar and report it as product-card share, not just brand mentions.
06 How Lmo7 does it
Map the questions
We list the unbranded questions your shoppers ask and find which answers your products are missing from.
Rework the listings
We rewrite copy, structured attributes and A+ FAQs against those questions.
Go live and log
We log every price, deal, ad and Buy Box change alongside the go-live, so results can be read against what else changed.
Track product cards
We report how often your products appear as product cards, several times a day.
07 Questions
How many questions did you test?
50 unbranded shopper questions, 25 per category, across two categories. We asked each several times a day from a clean Amazon account with no purchase history, for 4 weeks before go-live and 4 weeks after. Source: Lexym Rufus Visibility Tracker, Amazon UK. Lmo7 calculation.
Did conversion go up by 28%?
Glance-view conversion was up to 28% higher on the two cleanest listings: 35.5% to 41.5% (+17% relative) and 20.3% to 25.9% (+28% relative). The 28% applies to that listing, not to all six. Price, deals and ad spend also changed in this period, so read it as a strong direction, not proof. Source: Amazon sales and traffic data, client account, Amazon UK, 38 days before vs 38 days after go-live, Aug to Oct 2026. Lmo7 calculation.
Does better listing content replace reviews and off-Amazon authority?
No. Listing content is the quick-win track. The long game is separate: reviews, ratings and sales history on Amazon, plus off-Amazon citations and authority for ChatGPT and Google.
The Lmo7 Agency - AI Search and Ads for Consumer Brands | UK-based | Serving Global Brands
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