Soft Drinks,
according to AI
Every week we ask ChatGPT, Claude and Gemini the questions real UK consumers ask about soft drinks — and record exactly which brands they put forward. Right now, Fanta owns the conversation.
0 AI answers this run · 0 brands named · measured, never estimated
Fanta is the default answer.
Named in 43% of soft drinks answers, typically in position 1.5. Sprite follows at 42%, Coca-Cola at 40%.
Every brand AI names, ranked.
Visibility is the share of answers naming the brand; citation share is its slice of all brand-owned pages cited; read→cited is how often its pages convert a read into a citation.
| # | Brand | Visibility | Avg. position | Citation share | Read→cited |
|---|---|---|---|---|---|
| 1 | Fanta | 43% | 1.5 | 0% | — |
| 2 | Sprite | 42% | 1.4 | 0% | — |
| 3 | Coca-Cola | 40% | 1.5 | 62% | 29% |
| 4 | Pepsi | 35% | 2.2 | 0% | 0% |
| 5 | 7 Up | 10% | 3.7 | 8% | 100% |
| 6 | San Pellegrino | 10% | 3.7 | 8% | 33% |
| 7 | Tango | 8% | 4.2 | 0% | — |
| 8 | Dash Water | 7% | 1.8 | 0% | — |
| 9 | Dr Pepper | 5% | 3.7 | 0% | — |
| 10 | Appletiser | 5% | 7.0 | 0% | — |
| 11 | Cawston Press | 3% | 4.0 | 0% | — |
| 12 | Barr | 3% | 5.5 | 0% | — |
| 13 | Schweppes | 3% | 5.5 | 0% | — |
| 14 | Fentimans | 3% | 6.5 | 8% | 50% |
| 15 | Rubicon | 3% | 7.0 | 0% | — |
Fanta is named most. That is not the same as being wanted.
Being named is visibility. Underneath it, every answer describes a brand in three ways — how much it stands out, how much it belongs, and how much it is returned to. In soft drinks, Coca-Cola leads attraction at 116 against Sprite at 92, indexed on the category at 100.
Each whorl lights one ring per index threshold cleared. See the full soft drinks desire edition →
The referees of soft drinks.
The independent sources AI models cite when answering soft drinks questions — the places a brand needs to be seen, reviewed and ranked.
San Pellegrino converts reads into citations. Pepsi doesn't.
When Claude or ChatGPT opens a brand's own pages while answering, does the page make the cited-sources list? San Pellegrino converts 33% of reads; Pepsi just 0%. That gap is a content problem, not a visibility problem.
Full data table
| # | Brand | Visibility | Avg. position | Citation share | Read→cited |
|---|---|---|---|---|---|
| 1 | Fanta | 43% | 1.5 | 0% | — |
| 2 | Sprite | 42% | 1.4 | 0% | — |
| 3 | Coca-Cola | 40% | 1.5 | 62% | 29% |
| 4 | Pepsi | 35% | 2.2 | 0% | 0% |
| 5 | 7 Up | 10% | 3.7 | 8% | 100% |
| 6 | San Pellegrino | 10% | 3.7 | 8% | 33% |
| 7 | Tango | 8% | 4.2 | 0% | — |
| 8 | Dash Water | 7% | 1.8 | 0% | — |
| 9 | Dr Pepper | 5% | 3.7 | 0% | — |
| 10 | Appletiser | 5% | 7.0 | 0% | — |
| 11 | Cawston Press | 3% | 4.0 | 0% | — |
| 12 | Barr | 3% | 5.5 | 0% | — |
| 13 | Schweppes | 3% | 5.5 | 0% | — |
| 14 | Fentimans | 3% | 6.5 | 8% | 50% |
| 15 | Rubicon | 3% | 7.0 | 0% | — |
The models do not agree on who leads.
Ask about soft drinks and the brand you are shown depends on the assistant: Claude → Fanta, Gemini → Fanta, ChatGPT → Sprite. Their top-five lists share just 57% of names.
Brands whose visibility swings most between models — the bar per model, widest gap on the right.
The data behind this chart
| Brand | Claude | Gemini | ChatGPT | Spread |
|---|---|---|---|---|
| Pepsi | 20% | 50% | 35% | 30pp |
| Coca-Cola | 30% | 55% | 35% | 25pp |
| Fanta | 40% | 55% | 35% | 20pp |
| Sprite | 35% | 55% | 35% | 20pp |
| Tango | 15% | 5% | 5% | 10pp |
| 7 Up | 10% | 5% | 15% | 10pp |
| San Pellegrino | 5% | 15% | 10% | 10pp |
| Dr Pepper | 0% | 10% | 5% | 10pp |
| Shloer | 5% | 0% | 0% | 5pp |
| Dash Water | 5% | 10% | 5% | 5pp |
Editorial carry soft drinks.
Every page AI opened while answering, classified by what kind of page it is. Editorial supply the most citations; Community threads convert best — 95% of the ones models opened were actually cited.
The data behind this chart
| Page type | Cited | Read but not cited | Conversion |
|---|---|---|---|
| Editorial | 27 | 24 | 53% |
| Community threads | 18 | 1 | 95% |
| Product pages | 17 | 8 | 68% |
| Other | 15 | 25 | 38% |
| How-to guides | 15 | 3 | 83% |
| category-page | 15 | 18 | 45% |
| Reviews | 13 | 9 | 59% |
| Listicles | 8 | 3 | 73% |
Structured data is what separates cited from ignored.
Of the soft drinks pages models actually opened, how much more often each feature's pages ended up in the cited sources. Structured data is worth 14 percentage points; hard statistics pages fare 37pp worse. Measured within the read population, so selection can't flatter it.
The data behind this chart
| Feature | Pages with | Cited % | Pages without | Cited % | Difference |
|---|---|---|---|---|---|
| Structured data | 179 | 63% | 91 | 49% | +14pp |
| Specifications | 63 | 68% | 207 | 56% | +13pp |
| Named author | 93 | 67% | 177 | 54% | +12pp |
| Comparison table | 36 | 58% | 234 | 59% | -0pp |
| Answer up front | 96 | 58% | 174 | 59% | -0pp |
| Updated this year | 70 | 56% | 200 | 60% | -4pp |
| Hard statistics | 68 | 31% | 202 | 68% | -37pp |
Coca-Cola builds pages AI can quote.
Readiness scores each brand's own pages on the structure models reward — a direct answer up front, tables, hard numbers, named authors, structured data, recency, specifications. Set against how often those pages are actually cited.
| Brand | Readiness | Pages cited | Pages profiled |
|---|---|---|---|
| Coca-Cola | 35 | 50% | 16 |
| Dalston's | 28 | 20% | 5 |
Readiness is the share of eight measurable structural signals present on a brand's profiled pages. It is a build-quality measure, not a ranking of the brand.
The questions soft drinks pages have to settle.
Read straight off the pages AI cited: the consumer questions cited content answers most often. Content that fails to settle these is content models have no reason to quote.
Nineteen more categories.
Method: 20 unbranded consumer prompts per category, spread across the buying journey, run weekly against ChatGPT, Claude and Gemini. Read→cited uses Claude and ChatGPT only (Gemini does not separate the two). Correlational observations of model behaviour at the time of the run. Data from the run completed Wed, 02 Sep 2026 10:03:07 GMT.