Signal
Personalization context you cannot see
Part of what an agent weighs belongs to the shopper, not to your catalog: remembered preferences, custom instructions and prior activity, which means two people asking the same question can get different answers for reasons no merchant controls.
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 | Supported | OpenAI documents that ChatGPT considers the query and context such as Memory or Custom instructions, and expects to personalize merchant rankings further over time. | Source (opens in new tab) · verified 2026-08-28 |
| 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 spec-fact (Very high confidence).
- Shopping with ChatGPT Search (OpenAI Help Center) (opens in new tab) · updated approximately 2026-08-28
How to act on this
You cannot set this, so treat it as measurement hygiene instead. Test from clean sessions with memory off where the engine allows it, run enough repetitions that personal context averages out, and stop reading a single session as evidence that anything changed.
Handbook chapters
Notes
This signal is here because it explains variance a merchant would otherwise misread. Someone who sees their product recommended on Monday and absent on Tuesday will look for a ranking change, and the cause may be that the two sessions carried different shopper context. Amazon documents a similar dependence on individual shopping activity for its own assistant. Neither is a lever; both are reasons to distrust a sample of one.