How AI wants smartphones
Smartphones is decided on attraction: Samsung indexes 112 there against Ulefone at 86, a 26-point spread. Attachment separates almost nobody (11 points across the whole category), so being described that way is table stakes here rather than an advantage. Samsung holds the strongest overall profile at 107 — magnetic but unbought. But the brand assistants name most often is Samsung, not the category's market leader: being desired and being named are not the same measurement. Across these 8 brands, affinity tracks being named most closely (rank correlation 0.92).
8 brands · 60 AI answers · 102 dimension scores · measured, never estimated
Smartphonesupset
| # | Brand | Attraction | Affinity | Attachment | Desire shape | Named in |
|---|---|---|---|---|---|---|
| 1 | Samsung | 112 | 110 | 100 | Magnetic but unbought | 65% |
| 2 | Apple | 107 | 111 | 97 | Quietly trusted | 53% |
| 3 | 108 | 107 | 102 | Magnetic but unbought | 52% | |
| 4 | Oppo | 107 | 100 | 96 | Magnetic but unbought | 10% |
| 5 | Motorola | 98 | 106 | 93 | Quietly trusted | 17% |
| 6 | Crosscall | 96 | 93 | 104 | Habit, not love | 2% |
| 7 | Oukitel | 86 | 86 | 104 | Habit, not love | 2% |
| 8 | Ulefone | 86 | 86 | 104 | Habit, not love | 5% |
Indexed against the smartphones average of 8 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 |
|---|---|---|---|---|
| Style & Aesthetic | Attraction | 7.2 | Apple 9.0 | 4.0 |
| Innovation & Technology | Attraction | 7.8 | Google 9.0 | 3.0 |
| Value & Pricing | Attachment | 6.9 | Oukitel 8.0 | 3.0 |
| Lifestyle Fit & Identity | Affinity | 7.4 | Apple 8.7 | 2.7 |
| Heritage & Authority | Affinity | 8.4 | Apple 9.0 | 2.0 |
Where everyone reads alike
| Dimension | Driver | Category avg | Strongest | Spread |
|---|---|---|---|---|
| Sustainability & Ethics | Affinity | 7.1 | Google 7.7 | 0.7 |
| Reliability & Consistency | Attachment | 8.5 | Apple 9.0 | 1.0 |
| Quality & Performance | Attraction | 8.6 | Apple 9.0 | 1.0 |
| Ease of Use & Onboarding | Attachment | 8.3 | Apple 9.0 | 1.0 |
| Differentiation vs Sameness | Attraction | 8.3 | Crosscall 9.0 | 1.0 |
Does desire track being recommended?
Rank correlation between a brand's driver index and the share of answers naming it, across the 8 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.