From 6th to top 3: how Dell won in Alexa, Amazon's AI shopping assistant
In May 2026, Amazon folded Rufus into Alexa for Shopping, putting an AI assistant in the search bar, the app, and every Alexa device. Shoppers stopped typing keywords and started asking what to buy.
There are dozens of ways a product page can shape what Alexa recommends, and no obvious way to know which ones matter. Rather than optimise blind, Dell worked with WPP Media and Shalion to find out exactly where the brand was winning and losing.
9.7%→11.2%
Dell's Alexa share of voice, UK laptops, pre to post PDP update
+1.5 pp
Gained in a period when the overall market barely moved
6th → top 3
In Alexa share of voice for UK laptops
Action:
Shalion audited Dell's visibility across 48 weighted shopper questions spanning 16 consumer intents, identifying exactly which questions Dell was winning, losing, or invisible on.
Working with WPP Media, Dell reworked its product content to answer the high-intent questions it was missing. Titles, bullets, A+ content and backend attributes were rewritten to name use cases and attributes outright.
No new budget and no media spend. The only variable that changed was the content, so the movement could be attributed with confidence.
The 5-step framework applied to Dell
ThThe same loop runs on any brand, category or market.
Query selection
Map the questions and consumer intents shoppers actually use to ask Alexa for a recommendation.
Monitor
Track share of voice by intent, against named competitors, trended over time.
Benchmark
See why a competitor is winning, whether it comes down to title, bullets or A+ content.
Diagnose
Match each intent to the SKUs in your catalogue best positioned to win it.
Act
Turn every content gap into a specific, copywriter-ready instruction, ranked by potential impact.
Result:
What the data reveals
Dell's Alexa share of voice rose from 9.7% to 11.2% between March and April, a gain of 1.5 percentage points in a period when the overall market barely shifted.
Once Dell named attributes outright, the effect was immediate. Share of voice on specific recommendations like "Wi-Fi" moved from 0% to 25%, while generic ones like "long battery life" went from 15.4% to 0%.
That trade proves the mechanism: Alexa matches shopper questions to product content directly. Dell gained where the copy was explicit and lost where it relied on reputation.
“Partnering with Shalion during the beta test of their GEO tool was exciting and seamless. The granularity of the data stood out, enabling constructive, well-grounded recommendations for the test with Dell. Their eagerness to understand our needs made them feel like a true extension of our team.”
Yara El Saadani
Senior Commerce Strategy Director - EMEA
Key takeaways you can apply to your brand
Be specific to win a recommendation.
Whatever gets implied, gets missed.
Specificity has a cost
If it is not managed deliberately and tracked, naming one use case can cost you another.
Reputation alone no longer earns a recommendation
Dell lost ground on the broad queries its old copy used to win by default.
This is diagnosable, not a guessing game
Every gain and every loss traces back to a specific question and a specific line of content.