Contact Clean Up Mode for Finding & Resolving Edge-Case Duplicates

Details:

Reconciling duplicate contacts is one of the most labor-intensive parts of using Dex. Duplicates commonly arise from name changes (e.g., marriage), nicknames, automatic email imports, or inconsistent formatting.

Currently, Merge Contacts only surfaces very high-confidence matches and does not help users identify or resolve edge cases. As a result, users are forced to manually search common names (e.g., “Claire”) and visually scan for duplicates.

Proposed solution:

Introduce a “Contact Clean Up” mode (similar in spirit to Quick Actions) focused specifically on identifying and resolving potential duplicates that require human judgment.

Possible capabilities:

Surface lower-confidence duplicate candidates for user review (not auto-merge)

Detect patterns such as:

First/last name + email domain similarities

Nickname vs. legal name (e.g., Liz / Elizabeth)

Same company + similar names

Allow users to:

Review uncertain matches one by one

Approve, skip, or dismiss merge suggestions

Provide search and filtering tools specifically optimized for cleanup workflows

Value:

Dramatically reduces manual effort in maintaining clean contact data

Gives users control over ambiguous merge decisions

Improves long-term data quality without risking incorrect automatic merges