Every week we ask ChatGPT, Claude and Gemini the questions real UK consumers ask about solar & heat pumps — 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
Named in 10% of solar & heat pumps answers, typically in position 1.0. Tesla follows at 7%, GivEnergy at 5%.
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 | 10% | 1.0 | 13% | 29% |
| 2 | Tesla | 7% | 1.5 | 0% | — |
| 3 | GivEnergy | 5% | 4.0 | 6% | — |
| 4 | Fox ESS | 5% | 4.3 | 0% | — |
| 5 | SolarEdge | 5% | 6.0 | 0% | — |
| 6 | Enphase | 3% | 2.5 | 6% | 50% |
| 7 | Solis | 3% | 3.5 | 0% | — |
| 8 | British Gas | 2% | 1.0 | 6% | 50% |
| 9 | Green Energy | 2% | 1.0 | 0% | — |
| 10 | AlphaESS | 2% | 2.0 | 0% | — |
| 11 | LG Chem | 2% | 2.0 | 0% | — |
| 12 | OVO Energy | 2% | 2.0 | 0% | — |
| 13 | EcoFlow | 2% | 3.0 | 13% | 25% |
| 14 | E.ON Next | 2% | 7.0 | 13% | — |
| 15 | Huawei | 2% | 7.0 | 0% | — |
The independent sources AI models cite when answering solar & heat pumps questions — the places a brand needs to be seen, reviewed and ranked.
When Claude or ChatGPT opens a brand's own pages while answering, does the page make the cited-sources list? Octopus Energy converts 29% of reads; EcoFlow just 25%. That gap is a content problem, not a visibility problem.
| # | Brand | Visibility | Avg. position | Citation share | Read→cited |
|---|---|---|---|---|---|
| 1 | Octopus Energy | 10% | 1.0 | 13% | 29% |
| 2 | Tesla | 7% | 1.5 | 0% | — |
| 3 | GivEnergy | 5% | 4.0 | 6% | — |
| 4 | Fox ESS | 5% | 4.3 | 0% | — |
| 5 | SolarEdge | 5% | 6.0 | 0% | — |
| 6 | Enphase | 3% | 2.5 | 6% | 50% |
| 7 | Solis | 3% | 3.5 | 0% | — |
| 8 | British Gas | 2% | 1.0 | 6% | 50% |
| 9 | Green Energy | 2% | 1.0 | 0% | — |
| 10 | AlphaESS | 2% | 2.0 | 0% | — |
| 11 | LG Chem | 2% | 2.0 | 0% | — |
| 12 | OVO Energy | 2% | 2.0 | 0% | — |
| 13 | EcoFlow | 2% | 3.0 | 13% | 25% |
| 14 | E.ON Next | 2% | 7.0 | 13% | — |
| 15 | Huawei | 2% | 7.0 | 0% | — |
Ask about solar & heat pumps and the brand you are shown depends on the assistant: Claude → Tesla, Gemini → Octopus Energy, ChatGPT → SolarEdge. Their top-five lists share just 10% of names.
Brands whose visibility swings most between models — the bar per model, widest gap on the right.
| Brand | Claude | Gemini | ChatGPT | Spread |
|---|---|---|---|---|
| Tesla | 5% | 15% | 0% | 15pp |
| Octopus Energy | 5% | 20% | 5% | 15pp |
| Fox ESS | 0% | 10% | 5% | 10pp |
| SolarEdge | 0% | 10% | 5% | 10pp |
| GivEnergy | 0% | 10% | 5% | 10pp |
| Solis | 0% | 10% | 0% | 10pp |
| Green Energy | 5% | 0% | 0% | 5pp |
| LG Chem | 5% | 0% | 0% | 5pp |
| British Gas | 5% | 0% | 0% | 5pp |
| OVO Energy | 0% | 5% | 0% | 5pp |
Every page AI opened while answering, classified by what kind of page it is. Editorial supply the most citations; Comparisons convert best — 100% of the ones models opened were actually cited.
| Page type | Cited | Read but not cited | Conversion |
|---|---|---|---|
| Editorial | 77 | 12 | 87% |
| How-to guides | 74 | 5 | 94% |
| Comparisons | 15 | 0 | 100% |
| Documentation | 13 | 10 | 57% |
| pricing | 12 | 1 | 92% |
| Other | 9 | 6 | 60% |
| Product pages | 8 | 1 | 89% |
Of the solar & heat pumps pages models actually opened, how much more often each feature's pages ended up in the cited sources. Structured data is worth 29 percentage points; hard statistics pages fare 10pp worse. Measured within the read population, so selection can't flatter it.
| Feature | Pages with | Cited % | Pages without | Cited % | Difference |
|---|---|---|---|---|---|
| Structured data | 232 | 90% | 59 | 61% | +29pp |
| Answer up front | 153 | 90% | 138 | 78% | +12pp |
| Specifications | 78 | 91% | 213 | 81% | +10pp |
| Named author | 181 | 87% | 110 | 79% | +8pp |
| Comparison table | 88 | 85% | 203 | 83% | +2pp |
| Cites its sources | 29 | 83% | 262 | 84% | -1pp |
| Updated this year | 111 | 79% | 180 | 87% | -7pp |
| Hard statistics | 112 | 78% | 179 | 88% | -10pp |
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. GivEnergy is the widest gap: well-built pages that still aren't converting into citations.
| Brand | Readiness | Pages cited | Pages profiled |
|---|---|---|---|
| Sunsave | 73 | 71% | 7 |
| GivEnergy | 57 | 0% | 40 |
| Spirit Energy | 56 | 0% | 4 |
| Good Energy | 53 | 0% | 9 |
| Fox ESS | 51 | 0% | 56 |
| Project Solar | 50 | 0% | 6 |
| Hive | 45 | 40% | 5 |
| EDF Energy | 44 | 0% | 4 |
| E.ON Next | 32 | 6% | 17 |
| British Gas | 30 | 14% | 7 |
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.
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.
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 08:02:33 GMT.