Discount Stores,
according to AI
Every week we ask ChatGPT, Claude and Gemini the questions real UK consumers ask about discount stores — and record exactly which brands they put forward. Right now, B&M owns the conversation.
0 AI answers this run · 0 brands named · measured, never estimated
B&M is the default answer.
Named in 35% of discount stores answers, typically in position 1.8. The Range follows at 33%, Home Bargains at 30%.
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 | B&M | 35% | 1.8 | 25% | 43% |
| 2 | The Range | 33% | 2.3 | 17% | 25% |
| 3 | Home Bargains | 30% | 1.9 | 17% | 50% |
| 4 | Aldi | 27% | 2.9 | 13% | 50% |
| 5 | Poundland | 27% | 2.9 | 4% | 100% |
| 6 | Lidl | 25% | 3.8 | 0% | 0% |
| 7 | TK Maxx | 10% | 4.7 | 13% | — |
| 8 | Savers | 5% | 2.0 | 0% | — |
| 9 | Wilko | 5% | 2.0 | 0% | — |
| 10 | Food Warehouse | 3% | 3.5 | 0% | — |
| 11 | Iceland | 3% | 3.5 | 0% | — |
| 12 | Low Price Foods | 3% | 4.0 | 8% | 100% |
| 13 | HomeSense | 3% | 6.0 | 0% | — |
| 14 | Farmfoods | 2% | 3.0 | 0% | — |
| 15 | HomeSavers | 2% | 4.0 | 0% | — |
Discount Stores is decided on attraction.
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 discount stores, Aldi leads attraction at 129 against Poundstretcher at 62, indexed on the category at 100.
Each whorl lights one ring per index threshold cleared. See the full discount stores desire edition →
The referees of discount stores.
The independent sources AI models cite when answering discount stores questions — the places a brand needs to be seen, reviewed and ranked.
Aldi converts reads into citations. Lidl doesn't.
When Claude or ChatGPT opens a brand's own pages while answering, does the page make the cited-sources list? Aldi converts 50% of reads; Lidl just 0%. That gap is a content problem, not a visibility problem.
Full data table
| # | Brand | Visibility | Avg. position | Citation share | Read→cited |
|---|---|---|---|---|---|
| 1 | B&M | 35% | 1.8 | 25% | 43% |
| 2 | The Range | 33% | 2.3 | 17% | 25% |
| 3 | Home Bargains | 30% | 1.9 | 17% | 50% |
| 4 | Aldi | 27% | 2.9 | 13% | 50% |
| 5 | Poundland | 27% | 2.9 | 4% | 100% |
| 6 | Lidl | 25% | 3.8 | 0% | 0% |
| 7 | TK Maxx | 10% | 4.7 | 13% | — |
| 8 | Savers | 5% | 2.0 | 0% | — |
| 9 | Wilko | 5% | 2.0 | 0% | — |
| 10 | Food Warehouse | 3% | 3.5 | 0% | — |
| 11 | Iceland | 3% | 3.5 | 0% | — |
| 12 | Low Price Foods | 3% | 4.0 | 8% | 100% |
| 13 | HomeSense | 3% | 6.0 | 0% | — |
| 14 | Farmfoods | 2% | 3.0 | 0% | — |
| 15 | HomeSavers | 2% | 4.0 | 0% | — |
The models do not agree on who leads.
Ask about discount stores and the brand you are shown depends on the assistant: Claude → The Range, Gemini → B&M, ChatGPT → B&M. Their top-five lists share just 67% 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 |
|---|---|---|---|---|
| Poundland | 10% | 45% | 25% | 35pp |
| B&M | 20% | 45% | 40% | 25pp |
| Home Bargains | 20% | 40% | 30% | 20pp |
| The Range | 40% | 25% | 35% | 15pp |
| TK Maxx | 5% | 20% | 5% | 15pp |
| Lidl | 20% | 30% | 25% | 10pp |
| Aldi | 25% | 30% | 25% | 5pp |
| Farmfoods | 5% | 0% | 0% | 5pp |
| Low Price Foods | 5% | 5% | 0% | 5pp |
| HomeSense | 5% | 0% | 5% | 5pp |
How-to guides carry discount stores.
Every page AI opened while answering, classified by what kind of page it is. How-to guides supply the most citations; category-page convert best — 78% of the ones models opened were actually cited.
The data behind this chart
| Page type | Cited | Read but not cited | Conversion |
|---|---|---|---|
| How-to guides | 35 | 11 | 76% |
| category-page | 25 | 7 | 78% |
| Editorial | 24 | 18 | 57% |
| Listicles | 17 | 9 | 65% |
| Product pages | 15 | 7 | 68% |
| Comparisons | 11 | 14 | 44% |
| Community threads | 10 | 4 | 71% |
| News | 8 | 6 | 57% |
Structured data is what separates cited from ignored.
Of the discount stores pages models actually opened, how much more often each feature's pages ended up in the cited sources. Structured data is worth 20 percentage points; hard statistics pages fare 31pp 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 | 209 | 65% | 68 | 44% | +20pp |
| Specifications | 27 | 74% | 250 | 58% | +16pp |
| Named author | 137 | 59% | 140 | 60% | -1pp |
| Answer up front | 107 | 55% | 170 | 62% | -7pp |
| Updated this year | 77 | 47% | 200 | 65% | -18pp |
| Comparison table | 61 | 44% | 216 | 64% | -20pp |
| Hard statistics | 88 | 39% | 189 | 69% | -31pp |
TK Maxx 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 |
|---|---|---|---|
| TK Maxx | 21 | 100% | 3 |
| Aldi | 20 | 60% | 5 |
| The Range | 19 | 100% | 4 |
| B&M | 16 | 75% | 8 |
| Home Bargains | 13 | 80% | 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 discount stores 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 10:00:16 GMT.