Signal
Brand familiarity versus a small rating edge
In controlled tests a familiar brand is recommended almost without exception when specifications are identical, and a competitor rating advantage of less than a tenth of a star is enough to break that dominance.
One research group, one product category (skincare, an experience good), with generalisation tested only as the authors' own robustness check, so the finding sits below the reported default.
Per-platform status
Where a platform documents relevant behavior, its status and source are shown. Undocumented platforms show "unknown" - honest unknowns, never invented.
| Platform | Status | Notes | Source |
|---|---|---|---|
| ChatGPT | Unknown | Not documented by this platform. | - |
| Gemini / Google AI Mode | Unknown | Not documented by this platform. | - |
| Perplexity | Unknown | Not documented by this platform. | - |
| Copilot | Unknown | Not documented by this platform. | - |
| Claude | Unknown | Not documented by this platform. | - |
Evidence and sources
This signal is typed reported (Medium confidence).
How to act on this
For a challenger brand this makes rating accuracy and review quality a higher-leverage investment than brand-name spend, because the gap that has to be closed is small. Earn the rating honestly: the same study shows the surface responds to authority-style language including fabricated evidence, which is fabrication, not a tactic, and it is a risk to plan for rather than a lever to pull.
Handbook chapters
Notes
The same paper reports a collective trap: when every brand adopts the same optimisation strategy the individual payoff proxy collapses, and brands that do not participate receive no recommendations at all in its tests.