AI Commerce Intelligence
See your category through the AI shopper’s eyes.
Shoppers increasingly ask AI what to buy. Share of Conversation measures which brands Direct AI puts forward when they do. The wider AI Commerce Benchmark shows how the competitive field changes across other AI environments, where measured.
AI Commerce
AI is becoming the new front door to commerce.
More shoppers now start with a question, not a search results page — and receive a short, curated answer in return.
Those answers increasingly shape which brands make the shortlist. There is no traditional shelf, no ranking page and no transparent attribution model to show brands where they stand.
Share of Conversation brings that picture into view for Direct AI: which brands are being put forward, where your brand appears, and where competitive differences emerge.
The measurement gap
Your digital shelf metrics can’t see inside AI.
Brands have spent years measuring what they can see and control — search rankings, product pages, ratings and reviews, availability. Those signals still matter.
But when a shopper asks AI for a recommendation, the answer arrives without a shelf, a ranking page or clear attribution. You can do everything right on the digital shelf and still have no view of how — or whether — your brand is being put forward.
Traditional digital shelf
Observable signals — and they still matter.
Search visibility
Product page optimisation
Ratings & reviews
Availability
“What should I choose for…?”
The measurement gap
The shopper moves into AI — outside the shelf’s view.
AI Commerce — inside the answer
01
Shopper question
“What should I choose for…?”
02
Curated AI answer
A short answer, not a ranked shelf.
03
Brands put forward
Specific brands appear within the answer.
04
Direct AI KPI
Each recognised eligible brand’s share of references across a certified universe of shopper questions.
Separate evidence environments
Direct AI
Gemini · OpenAI · Perplexity
AI Search
Where measured
Retailer AI
Where measured
Each environment is reported separately — the competitive field can differ between them.
The AI Commerce journey
AI doesn’t have one shelf.
One shopper need. Multiple AI decision environments.
A shopper’s question can travel through several kinds of AI before it becomes a purchase. Each one can put forward a different set of brands. The competitive shelf changes as the shopper moves through AI.
01
Shopper demand
Originating need
What shoppers are looking for, and how they ask.
02
Direct AI
Share of Conversation
Assistants such as Gemini, OpenAI and Perplexity answering shopper questions directly.
03
AI Search
Where measured
AI-generated answers inside search, such as Google AI Mode.
04
Retailer AI
Where measured
Retailers’ own shopping assistants, such as Amazon Rufus or Boots AI Assistant.
05
Product / digital shelf
Where measured
The product page and digital shelf the shopper finally lands on.
The core measure
Who owns the AI conversation in your category?
Share of Conversation measures a brand’s share of recognised eligible brand references across a certified universe of shopper questions.
In plain terms: when real shopper questions for your category are put to Direct AI — Gemini, OpenAI and Perplexity — which brands are put forward, and how your share compares with each competitor’s. Every brand is measured against the same category evidence base.
Competitive, not isolated. Every brand’s share is read against the whole category.
Built on real shopper questions. A certified set of questions shoppers actually ask.
One clear measure. Not a composite, index or blended AI score.
Share of Conversation
Direct AI
10.74%
Cadbury
Chocolate & Confectionery UK · UK benchmark
Cadbury’s share of the counted brand references in one UK category benchmark, measured across Direct AI.
Provider variation
Different AI. Different competitive field.
Put the same shopper question to Gemini, OpenAI and Perplexity and you may not see the same brands put forward — or in the same order.
That is why asking one chatbot a handful of questions isn’t an AI Commerce measurement strategy. Share of Conversation measures a certified set of shopper questions consistently across each Direct AI provider, so you can see how the competitive field shifts from one to the next.
Not which AI is best — how the field changes.
Shopper need
Gemini
OpenAI
Perplexity
The same shopper need can produce a different competitive field depending on the AI environment.
Illustrative representation. Provider-level evidence is reported separately within measured benchmarks.
The AI Commerce Benchmark
Inside an AI Commerce Benchmark.
Each benchmark combines the evidence lenses relevant to your category.
Core measure
Direct AI competitive share
Gemini
OpenAI
Perplexity
Competitive context
Provider competitive field
See how the competitive field differs across Gemini, OpenAI and Perplexity.
Shopper needs
See how the competitive field changes across different shopper missions within the category.
Wider AI Commerce evidence
Where measured
AI Search
Evidence from AI-generated search answers.
Where measured
Retailer AI
Evidence from retailers’ own AI shopping assistants.
Where measured
Product / digital shelf
Diagnostic evidence from product pages.
Lenses vary by study. Each is reported separately — never blended into a single score.
A real benchmark
Sun Protection & SPF UK — one benchmark, in numbers
160
certified shopper questions
480
Direct AI answers
2,087
counted brand references
172
brands in the measured field
La Roche-Posay — 15.24% Share of Conversation
See it in action
Explore real benchmark evidence.
See how Share of Conversation reads in a real category — the brands Direct AI puts forward, the competitive field, and how it shifts between Gemini, OpenAI and Perplexity.
How a benchmark is built
From shopper question to competitive evidence.
We analyse how brands appear across real shopper questions — revealing the competitive field, how Share of Conversation changes across AI environments, and where further investigation is warranted.
Illustrative shopper intent
BEST FOR
What should I choose for…
COMPARE
Which option is better for…
NEED STATE
What works best when…
ATTRIBUTE
What should I look for in…
AUDIENCE
Which option is better for…
OCCASION
What works best when…
VALUE
What should I choose for…
INFORMATION
What should I look for in…
We build a certified set of the questions shoppers actually ask in your category.
Share of Conversation is measured across Direct AI — Gemini, OpenAI and Perplexity. Where a benchmark includes them, AI Search and Retailer AI are reported as separate lenses.
We recognise every brand put forward and measure each brand’s share of references against its competitors.
We show where your brand appears, how the field changes by provider and shopper need, and where competitive differences emerge.
Methodology
Rigorous by design. Clear by default.
Every Share of Conversation benchmark follows the same disciplines, so the evidence holds up in a boardroom — without needing a data science degree to read it.
What should I choose…
Which is better for…
What works best when…
CERTIFIED SET
Real shopper questions
A certified universe of questions that reflect how shoppers actually ask about your category.
Gemini
OpenAI
Perplexity
Consistent measurement
Every question is put to each Direct AI provider in the same way, so results are comparable across the category.
RECOGNISED
UNRESOLVED
held separately
Recognised brand evidence
Only brands we can clearly recognise are counted. Where evidence is uncertain, we treat it conservatively rather than guess.
REFERENCES
EVIDENCE BASE
SHARE
A transparent denominator
Every brand is measured against the same category evidence base, so figures can be compared within a category. Missing evidence is never treated as zero.
DIRECT AI
Share of Conversation
AI SEARCH
Separate lens
RETAILER AI
Separate lens
PRODUCT / DIGITAL SHELF
Separate lens
Environments kept separate
Share of Conversation is the Direct AI measure. AI Search, Retailer AI and product-page evidence are separate lenses within the wider AI Commerce Benchmark, measured where evidence is available — never blended into a single AI score.