Comparison table
Privacy matrix
The matrix compresses the individual reviews into a consistent decision sheet: what is collected, where it flows, and how much control a normal user can exercise.
Composite score
| Platform | Collection | Sharing pressure | User control | Composite |
|---|---|---|---|---|
| Very broad | High | Fragmented | 8/10 | |
| Blind | Moderate | Moderate | Behavior-dependent | 4/10 |
| Moderate | Lower global pressure | Regional/legal leverage | 3/10 | |
| Peerlist | Lean | Low | Profile discipline matters | 2/10 |
Dimension notes
| Dimension | What raises risk | What lowers risk |
|---|---|---|
| Identity density | Real name, full work history, contact import, and social graph in one account. | Minimal profile fields and clear separation between public profile and private search. |
| Behavioral model | Feeds, ad clicks, search intent, messaging metadata, and job-seeking signals. | Low-feed use, disabled personalization, and separate job-tracking workflow. |
| Recipient scope | Parent-company ecosystems, advertising vendors, AI uses, and broad integrations. | Narrower product scope and transparent vendor lists. |
| Control quality | Settings split across many screens or worded as vague toggles. | Exports, deletion workflows, granular visibility, and plain privacy language. |
Recommended stack
For most professionals, the practical answer is not deleting every account. Keep one public discovery profile, publish durable work samples on a domain you control, avoid contact imports, use a separate job-search email, and review privacy controls every quarter.