How AI wants budgeting & bookkeeping apps
Budgeting & Bookkeeping Apps is decided on attraction: Monzo indexes 133 there against Clear Books at 75, a 58-point spread. Monzo holds the strongest overall profile at 126 — complete desire. But the brand assistants name most often is Emma, not the category's market leader: being desired and being named are not the same measurement. Across these 25 brands, attachment tracks being named most closely (rank correlation 0.65).
25 brands · 60 AI answers · 375 dimension scores · measured, never estimated
Budgeting & Bookkeeping Appsupset
| # | Brand | Attraction | Affinity | Attachment | Desire shape | Named in |
|---|---|---|---|---|---|---|
| 1 | Monzo | 133 | 122 | 121 | Complete desire | 18% |
| 2 | Starling Bank | 124 | 124 | 123 | Complete desire | 15% |
| 3 | Revolut | 131 | 110 | 114 | Complete desire | 3% |
| 4 | YNAB | 121 | 122 | 108 | Complete desire | 22% |
| 5 | Monarch Money | 121 | 107 | 110 | Complete desire | 7% |
| 6 | Snoop | 116 | 108 | 113 | Complete desire | 22% |
| 7 | Emma | 116 | 108 | 107 | Complete desire | 27% |
| 8 | Xero | 110 | 110 | 105 | Complete desire | 23% |
| 9 | QuickBooks | 106 | 110 | 105 | Complete desire | 22% |
| 10 | FreeAgent | 103 | 103 | 107 | Habit, not love | 18% |
| 11 | Sage | 101 | 113 | 105 | Quietly trusted | 13% |
| 12 | FreshBooks | 101 | 100 | 102 | Category default | 2% |
| 13 | Coconut | 104 | 97 | 99 | Magnetic but unbought | 2% |
| 14 | Zoho Books | 95 | 94 | 102 | Habit, not love | 2% |
| 15 | QuickBooks Self-Employed | 92 | 100 | 97 | Quietly trusted | 0% |
| 16 | Crunch | 92 | 97 | 94 | Loved, not chosen | 2% |
| 17 | TaxCalc | 87 | 93 | 91 | Fading | 0% |
| 18 | Money Dashboard | 85 | 90 | 91 | Fading | 5% |
| 19 | Pandle | 82 | 85 | 97 | Habit, not love | 3% |
| 20 | Wave | 79 | 85 | 94 | Fading | 2% |
| 21 | Booqable | 85 | 82 | 82 | Fading | 0% |
| 22 | GoSimpleTax | 82 | 82 | 85 | Fading | 5% |
| 23 | KashFlow | 75 | 90 | 85 | Fading | 0% |
| 24 | Receipt Bank | 82 | 85 | 82 | Fading | 7% |
| 25 | Clear Books | 75 | 85 | 82 | Fading | 2% |
Indexed against the budgeting & bookkeeping apps average of 25 brands (100 = the category), measured across 60 AI answers in the latest weekly run.
Driver by driver
Where the category actually separates. A wide spread means assistants describe these brands very differently on that driver; a narrow one means it is table stakes.
Attraction
The widest field of the three: this is where the category separates.
Affinity
Real separation, but not the category’s defining contest.
Attachment
The tightest of the three: most brands land close together here.
The shapes AI leaves these brands in
Three indices make a profile, and profiles fall into recognisable shapes. A brand that is magnetic but unbought has a different problem from a habit nobody loves — and a different thing to build next.
What assistants actually talk about
The sixteen dimensions underneath the drivers, scored 0–10 on how the answers describe each brand. Spread is the distance between the strongest and weakest brand: the widest are where a brand can still separate itself, the narrowest are the price of entry.
Where brands separate
| Dimension | Driver | Category avg | Strongest | Spread |
|---|---|---|---|---|
| Boldness & Creativity | Attraction | 6.1 | Monzo 9.0 | 5.0 |
| Differentiation vs Sameness | Attraction | 6.9 | Monzo 9.0 | 4.0 |
| Heritage & Authority | Affinity | 6.5 | QuickBooks 9.0 | 4.0 |
| Innovation & Technology | Attraction | 6.8 | Monzo 9.0 | 4.0 |
| Leadership & Momentum | Attraction | 6.7 | Monzo 9.0 | 4.0 |
Where everyone reads alike
| Dimension | Driver | Category avg | Strongest | Spread |
|---|---|---|---|---|
| Value & Pricing | Attachment | 6.9 | Snoop 8.5 | 2.5 |
| Trust & Credibility | Affinity | 7.2 | Starling Bank 9.0 | 3.0 |
| Sustainability & Ethics | Affinity | 5.9 | Starling Bank 8.0 | 3.0 |
| Customer Service & Support | Attachment | 6.2 | Starling Bank 8.0 | 3.0 |
| Reliability & Consistency | Attachment | 7.1 | Starling Bank 9.0 | 3.0 |
Does desire track being recommended?
Rank correlation between a brand's driver index and the share of answers naming it, across the 25 indexed brands in this category. A relationship inside one run's answers — descriptive, never causal, and easily moved by a single brand at this sample size.
Method & limitations
Every week, each category runs a fixed set of unbranded consumer prompts against ChatGPT, Claude and Gemini. A separate model reads the answers and scores every brand named in them across 16 perception dimensions, 0–10. Those dimensions are grouped into the three Drivers of Desire from the Havas Science of Desire framework, and each brand's driver score is indexed against the average of every scored brand in its category — 100 is the category, 115 is fifteen per cent above it.
This measures how AI assistants describe brands in their answers. It is not a survey of people, and it is not an endorsement: the scores are a reading of machine-generated text at the time of the run, and relationships between drivers and how often a brand is named are correlational. A brand needs at least six scored dimensions in a run to be indexed, and a category needs at least four such brands to get a board. See the full methodology.
Other categories
Where next
This edition measures what AI wants from these brands. These answer what comes next — which brands AI names, which websites feed those answers, and how any of it is counted.