How AI wants budget hotels
Budget Hotels is decided on attraction: citizenM indexes 144 there against Campanile at 70, a 74-point spread. citizenM holds the strongest overall profile at 123 — magnetic but unbought. Across these 24 brands, attachment tracks being named most closely (rank correlation 0.58).
24 brands · 60 AI answers · 360 dimension scores · measured, never estimated
Budget Hotels
| # | Brand | Attraction | Affinity | Attachment | Desire shape | Named in |
|---|---|---|---|---|---|---|
| 1 | citizenM | 144 | 116 | 103 | Magnetic but unbought | 2% |
| 2 | Treehouse Hotels | 136 | 113 | 89 | Magnetic but unbought | 0% |
| 3 | Premier Inn | 101 | 111 | 123 | Habit, not love | 38% |
| 4 | Alofts | 121 | 105 | 100 | Magnetic but unbought | 0% |
| 5 | Moxy Hotels | 124 | 103 | 100 | Magnetic but unbought | 2% |
| 6 | Radisson RED | 124 | 105 | 97 | Magnetic but unbought | 0% |
| 7 | Room2 | 123 | 115 | 92 | Magnetic but unbought | 0% |
| 8 | Holiday Inn Express | 95 | 111 | 121 | Habit, not love | 8% |
| 9 | Hampton by Hilton | 101 | 108 | 111 | Habit, not love | 5% |
| 10 | Novotel | 101 | 115 | 108 | Quietly trusted | 0% |
| 11 | YOTEL | 128 | 95 | 91 | Magnetic but unbought | 0% |
| 12 | Holiday Inn | 91 | 115 | 112 | Habit, not love | 8% |
| 13 | Mercure | 100 | 108 | 105 | Quietly trusted | 0% |
| 14 | ibis | 90 | 103 | 105 | Habit, not love | 22% |
| 15 | Best Western | 86 | 103 | 100 | Quietly trusted | 0% |
| 16 | ibis Styles | 96 | 90 | 94 | Fading | 0% |
| 17 | Travelodge | 81 | 95 | 105 | Habit, not love | 37% |
| 18 | Z Hotels | 105 | 87 | 89 | Magnetic but unbought | 3% |
| 19 | jury's Inn | 83 | 95 | 92 | Fading | 0% |
| 20 | Travelodge International | 76 | 88 | 97 | Habit, not love | 0% |
| 21 | easyHotel | 80 | 75 | 94 | Fading | 7% |
| 22 | ibis budget | 71 | 83 | 98 | Habit, not love | 0% |
| 23 | Days Inn | 71 | 87 | 94 | Fading | 0% |
| 24 | Campanile | 70 | 74 | 81 | Fading | 0% |
Indexed against the budget hotels average of 24 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 |
|---|---|---|---|---|
| Range & Availability | Attachment | 6.3 | Holiday Inn 9.0 | 6.0 |
| Style & Aesthetic | Attraction | 6.0 | citizenM 9.0 | 6.0 |
| Boldness & Creativity | Attraction | 5.6 | citizenM 9.0 | 5.5 |
| Differentiation vs Sameness | Attraction | 6.0 | citizenM 9.0 | 5.0 |
| Heritage & Authority | Affinity | 6.1 | Holiday Inn 9.0 | 5.0 |
Where everyone reads alike
| Dimension | Driver | Category avg | Strongest | Spread |
|---|---|---|---|---|
| Customer Service & Support | Attachment | 6.3 | Alofts 7.0 | 2.5 |
| Ease of Use & Onboarding | Attachment | 6.6 | citizenM 8.0 | 2.5 |
| Trust & Credibility | Affinity | 6.8 | citizenM 8.0 | 3.0 |
| Reliability & Consistency | Attachment | 6.7 | Premier Inn 8.3 | 3.3 |
| Value & Pricing | Attachment | 6.6 | easyHotel 8.5 | 3.5 |
Does desire track being recommended?
Rank correlation between a brand's driver index and the share of answers naming it, across the 24 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.