How AI wants mortgages
Mortgages is decided on affinity: HSBC indexes 104 there against First Direct at 94, a 10-point spread. Attachment separates almost nobody (0 points across the whole category), so being described that way is table stakes here rather than an advantage. HSBC holds the strongest overall profile at 102 — quietly trusted.
4 brands · 60 AI answers · 60 dimension scores · measured, never estimated
Mortgages
| # | Brand | Attraction | Affinity | Attachment | Desire shape | Named in |
|---|---|---|---|---|---|---|
| 1 | HSBC | 103 | 104 | 100 | Quietly trusted | 7% |
| 2 | First Direct | 104 | 94 | 100 | Magnetic but unbought | 5% |
| 3 | Halifax | 97 | 99 | 100 | Category default | 12% |
| 4 | Nationwide | 97 | 104 | 100 | Quietly trusted | 13% |
Indexed against the mortgages average of 4 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.
Affinity
The widest field of the three: this is where the category separates.
Attraction
Real separation, but not the category’s defining contest.
Attachment
Tightly bunched: assistants describe every brand here in much the same terms, so it is the price of entry rather than an edge.
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 |
|---|---|---|---|---|
| Heritage & Authority | Affinity | 8.0 | HSBC 9.0 | 2.0 |
| Range & Availability | Attachment | 7.6 | Halifax 8.0 | 1.5 |
| Boldness & Creativity | Attraction | 6.3 | First Direct 7.0 | 1.0 |
| Differentiation vs Sameness | Attraction | 6.3 | First Direct 7.0 | 1.0 |
| Innovation & Technology | Attraction | 6.4 | HSBC 7.0 | 1.0 |
Where everyone reads alike
| Dimension | Driver | Category avg | Strongest | Spread |
|---|---|---|---|---|
| Style & Aesthetic | Attraction | 6.0 | First Direct 6.0 | 0.0 |
| Lifestyle Fit & Identity | Affinity | 6.0 | First Direct 6.0 | 0.0 |
| Value & Pricing | Attachment | 7.1 | First Direct 7.5 | 0.5 |
| Trust & Credibility | Affinity | 7.9 | Halifax 8.0 | 0.5 |
| Reliability & Consistency | Attachment | 7.9 | Halifax 8.0 | 0.5 |
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.