Budgeting & Bookkeeping Apps,
according to AI
Every week we ask ChatGPT, Claude and Gemini the questions real UK consumers ask about budgeting & bookkeeping apps — and record exactly which brands they put forward. Right now, Emma owns the conversation.
0 AI answers this run · 0 brands named · measured, never estimated
Emma is the default answer.
Named in 38% of budgeting & bookkeeping apps answers, typically in position 2.6. Snoop follows at 30%, YNAB at 27%.
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 | Emma | 38% | 2.6 | 12% | 18% |
| 2 | Snoop | 30% | 3.6 | 1% | 20% |
| 3 | YNAB | 27% | 2.8 | 12% | 37% |
| 4 | Monzo | 18% | 2.4 | 6% | 18% |
| 5 | QuickBooks | 18% | 2.5 | 5% | 20% |
| 6 | Xero | 18% | 2.6 | 3% | 33% |
| 7 | Actual Budget | 18% | 3.6 | 0% | — |
| 8 | FreeAgent | 15% | 3.0 | 3% | 50% |
| 9 | Sage | 13% | 3.3 | 4% | 67% |
| 10 | Starling Bank | 13% | 3.4 | 3% | 13% |
| 11 | TrySnowball | 7% | 1.8 | 0% | — |
| 12 | Moneyhub | 7% | 2.8 | 0% | 0% |
| 13 | Empower | 7% | 3.0 | 0% | — |
| 14 | Sharesight | 7% | 4.5 | 5% | 30% |
| 15 | Splitwise | 7% | 5.0 | 1% | 50% |
Emma 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 budgeting & bookkeeping apps, Monarch Money leads affinity at 128 against Hammock at 99, indexed on the category at 100.
Each whorl lights one ring per index threshold cleared. See the full budgeting & bookkeeping apps desire edition →
The referees of budgeting & bookkeeping apps.
The independent sources AI models cite when answering budgeting & bookkeeping apps questions — the places a brand needs to be seen, reviewed and ranked.
Sage converts reads into citations. Starling Bank doesn't.
When Claude or ChatGPT opens a brand's own pages while answering, does the page make the cited-sources list? Sage converts 67% of reads; Starling Bank just 13%. That gap is a content problem, not a visibility problem.
Full data table
| # | Brand | Visibility | Avg. position | Citation share | Read→cited |
|---|---|---|---|---|---|
| 1 | Emma | 38% | 2.6 | 12% | 18% |
| 2 | Snoop | 30% | 3.6 | 1% | 20% |
| 3 | YNAB | 27% | 2.8 | 12% | 37% |
| 4 | Monzo | 18% | 2.4 | 6% | 18% |
| 5 | QuickBooks | 18% | 2.5 | 5% | 20% |
| 6 | Xero | 18% | 2.6 | 3% | 33% |
| 7 | Actual Budget | 18% | 3.6 | 0% | — |
| 8 | FreeAgent | 15% | 3.0 | 3% | 50% |
| 9 | Sage | 13% | 3.3 | 4% | 67% |
| 10 | Starling Bank | 13% | 3.4 | 3% | 13% |
| 11 | TrySnowball | 7% | 1.8 | 0% | — |
| 12 | Moneyhub | 7% | 2.8 | 0% | 0% |
| 13 | Empower | 7% | 3.0 | 0% | — |
| 14 | Sharesight | 7% | 4.5 | 5% | 30% |
| 15 | Splitwise | 7% | 5.0 | 1% | 50% |
The models do not agree on who leads.
Ask about budgeting & bookkeeping apps and the brand you are shown depends on the assistant: Claude → Snoop, Gemini → Emma, ChatGPT → Emma. Their top-five lists share just 20% 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 |
|---|---|---|---|---|
| Emma | 20% | 55% | 40% | 35pp |
| Snoop | 20% | 50% | 20% | 30pp |
| Xero | 5% | 35% | 15% | 30pp |
| QuickBooks | 10% | 35% | 10% | 25pp |
| Actual Budget | 5% | 30% | 20% | 25pp |
| Sage | 5% | 30% | 5% | 25pp |
| Monzo | 5% | 30% | 20% | 25pp |
| Starling Bank | 5% | 25% | 10% | 20pp |
| YNAB | 20% | 25% | 35% | 15pp |
| Empower | 15% | 5% | 0% | 15pp |
Comparisons carry budgeting & bookkeeping apps.
Every page AI opened while answering, classified by what kind of page it is. Comparisons supply the most citations; pricing convert best — 100% of the ones models opened were actually cited.
The data behind this chart
| Page type | Cited | Read but not cited | Conversion |
|---|---|---|---|
| Comparisons | 59 | 4 | 94% |
| How-to guides | 52 | 1 | 98% |
| Product pages | 36 | 1 | 97% |
| Editorial | 29 | 2 | 94% |
| Listicles | 17 | 3 | 85% |
| pricing | 14 | 0 | 100% |
| Documentation | 9 | 5 | 64% |
| Reviews | 9 | 2 | 82% |
Structured data is what separates cited from ignored.
Of the budgeting & bookkeeping apps pages models actually opened, how much more often each feature's pages ended up in the cited sources. Structured data is worth 19 percentage points; hard statistics pages fare 14pp 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 | 208 | 92% | 78 | 73% | +19pp |
| Named author | 158 | 93% | 128 | 80% | +13pp |
| Updated this year | 131 | 92% | 155 | 83% | +8pp |
| Comparison table | 91 | 92% | 195 | 85% | +8pp |
| Answer up front | 162 | 90% | 124 | 83% | +7pp |
| Hard statistics | 73 | 77% | 213 | 91% | -14pp |
RentalBux 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. Moneyhub is the widest gap: well-built pages that still aren't converting into citations.
| Brand | Readiness | Pages cited | Pages profiled |
|---|---|---|---|
| RentalBux | 58 | 20% | 5 |
| Richify | 54 | 33% | 3 |
| Landlord Studio | 53 | 80% | 5 |
| Moneyhub | 51 | 3% | 39 |
| Latch | 48 | 14% | 7 |
| WealthR | 48 | 60% | 5 |
| Crunch | 46 | 0% | 3 |
| Pandle | 44 | 0% | 4 |
| Aureli | 42 | 67% | 3 |
| PocketSmith | 42 | 33% | 3 |
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 budgeting & bookkeeping apps 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 Fri, 04 Sep 2026 07:03:34 GMT.