Energy Suppliers,
according to AI
Every week we ask ChatGPT, Claude and Gemini the questions real UK consumers ask about energy suppliers — and record exactly which brands they put forward. Right now, Octopus Energy owns the conversation.
0 AI answers this run · 0 brands named · measured, never estimated
Octopus Energy is the default answer.
Named in 20% of energy suppliers answers, typically in position 2.1. British Gas follows at 13%, EDF Energy at 10%.
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 | Octopus Energy | 20% | 2.1 | 15% | 67% |
| 2 | British Gas | 13% | 1.1 | 15% | 60% |
| 3 | EDF Energy | 10% | 2.5 | 13% | 33% |
| 4 | E.ON Next | 10% | 3.7 | 11% | 0% |
| 5 | OVO Energy | 10% | 4.0 | 19% | 50% |
| 6 | ScottishPower | 10% | 5.3 | 4% | 0% |
| 7 | Green Energy | 5% | 1.0 | 0% | — |
| 8 | Boost | 5% | 3.0 | 0% | — |
| 9 | Good Energy | 3% | 1.5 | 2% | — |
| 10 | Utility Warehouse | 3% | 7.5 | 2% | 0% |
| 11 | Ecotricity | 2% | 3.0 | 0% | 0% |
| 12 | Fuse Energy | 0% | — | 9% | 100% |
| 13 | Outfox the Market | 0% | — | 2% | — |
| 14 | So Energy | 0% | — | 6% | 50% |
| 15 | Utilita | 0% | — | 2% | — |
Before it answers, it goes looking for Green Energy.
An assistant does not answer from memory alone. It runs its own web searches first, and whoever it searches for is the shortlist it then chooses from. Across 78 searches in energy suppliers, Green Energy is named in 50% of the ones that name a brand at all. ChatGPT Web, Copilot do not report their searches, so these shares are measured against the ones that do.
These are the assistants' own searches, read from their answers — not what anyone typed into a search engine.
The referees of energy suppliers.
The independent sources AI models cite when answering energy suppliers questions — the places a brand needs to be seen, reviewed and ranked.
Octopus Energy converts reads into citations. ScottishPower doesn't.
When Claude or ChatGPT opens a brand's own pages while answering, does the page make the cited-sources list? Octopus Energy converts 67% of reads; ScottishPower just 0%. That gap is a content problem, not a visibility problem.
Full data table
| # | Brand | Visibility | Avg. position | Citation share | Read→cited |
|---|---|---|---|---|---|
| 1 | Octopus Energy | 20% | 2.1 | 15% | 67% |
| 2 | British Gas | 13% | 1.1 | 15% | 60% |
| 3 | EDF Energy | 10% | 2.5 | 13% | 33% |
| 4 | E.ON Next | 10% | 3.7 | 11% | 0% |
| 5 | OVO Energy | 10% | 4.0 | 19% | 50% |
| 6 | ScottishPower | 10% | 5.3 | 4% | 0% |
| 7 | Green Energy | 5% | 1.0 | 0% | — |
| 8 | Boost | 5% | 3.0 | 0% | — |
| 9 | Good Energy | 3% | 1.5 | 2% | — |
| 10 | Utility Warehouse | 3% | 7.5 | 2% | 0% |
| 11 | Ecotricity | 2% | 3.0 | 0% | 0% |
| 12 | Fuse Energy | 0% | — | 9% | 100% |
| 13 | Outfox the Market | 0% | — | 2% | — |
| 14 | So Energy | 0% | — | 6% | 50% |
| 15 | Utilita | 0% | — | 2% | — |
The models do not agree on who leads.
Ask about energy suppliers and the brand you are shown depends on the assistant: Claude → British Gas, Gemini → Octopus Energy, ChatGPT → Octopus Energy. Their top-five lists share just 25% 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 |
|---|---|---|---|---|
| Octopus Energy | 10% | 30% | 20% | 20pp |
| E.ON Next | 0% | 20% | 10% | 20pp |
| OVO Energy | 0% | 20% | 10% | 20pp |
| Green Energy | 0% | 15% | 0% | 15pp |
| British Gas | 10% | 20% | 10% | 10pp |
| EDF Energy | 5% | 15% | 10% | 10pp |
| ScottishPower | 5% | 15% | 10% | 10pp |
| Boost | 0% | 10% | 5% | 10pp |
| Good Energy | 5% | 5% | 0% | 5pp |
| Ecotricity | 5% | 0% | 0% | 5pp |
Editorial carry energy suppliers.
Every page AI opened while answering, classified by what kind of page it is. Editorial supply the most citations; Product pages convert best — 91% of the ones models opened were actually cited.
The data behind this chart
| Page type | Cited | Read but not cited | Conversion |
|---|---|---|---|
| Editorial | 150 | 37 | 80% |
| How-to guides | 149 | 17 | 90% |
| Comparisons | 38 | 9 | 81% |
| Other | 20 | 16 | 56% |
| faq | 18 | 2 | 90% |
| Documentation | 16 | 22 | 42% |
| News | 10 | 5 | 67% |
| Product pages | 10 | 1 | 91% |
Answer up front is what separates cited from ignored.
Of the energy suppliers pages models actually opened, how much more often each feature's pages ended up in the cited sources. Answer up front is worth 10 percentage points; cites its sources pages fare 46pp 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 |
|---|---|---|---|---|---|
| Answer up front | 339 | 82% | 245 | 72% | +10pp |
| Structured data | 174 | 81% | 410 | 77% | +4pp |
| Named author | 269 | 79% | 315 | 77% | +2pp |
| Comparison table | 136 | 73% | 448 | 79% | -7pp |
| Updated this year | 254 | 70% | 330 | 84% | -15pp |
| Hard statistics | 215 | 65% | 369 | 86% | -21pp |
| Cites its sources | 40 | 35% | 544 | 81% | -46pp |
EDF Energy 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. Ecotricity is the widest gap: well-built pages that still aren't converting into citations.
| Brand | Readiness | Pages cited | Pages profiled |
|---|---|---|---|
| EDF Energy | 31 | 15% | 59 |
| Fuse Energy | 29 | 47% | 17 |
| Octopus Energy | 24 | 18% | 68 |
| Good Energy | 24 | 40% | 15 |
| OVO Energy | 24 | 20% | 35 |
| So Energy | 24 | 20% | 10 |
| Ecotricity | 20 | 0% | 5 |
| Outfox the Market | 20 | 0% | 5 |
| British Gas | 19 | 20% | 60 |
| Utility Warehouse | 18 | 22% | 9 |
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 energy suppliers 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 Tue, 13 Oct 2026 06:43:55 GMT.