Profile Explorer

The Profile Explorer is a UI for searching, viewing, and investigating unified customer profiles produced by identity resolution. It lets you look up any customer by their identifiers, inspect the golden record, see all linked source records, and understand how and why records were merged.

Searching for Profiles

Search by Identifier

Enter any identifier value in the search bar to find the matching profile:

The search normalizes your input using the same normalization rules configured for each identifier family. For example, searching for Alice@Company.Com will match alice@company.com if email normalization is enabled.

Search by Cluster ID

If you know the cluster ID (from API results, logs, or downstream systems), enter it directly to navigate to that profile.

Search by Attribute

Search by golden record attribute values:

Search Results

If multiple profiles match your search, results are displayed as a list showing:

• Cluster ID — The unique identifier for the resolved profile
• Primary identifier — The highest-priority identifier value (e.g., the canonical email)
• Record count — How many source records are in the cluster
• Key attributes — A preview of name, email, and other key fields

Click on a result to open the full profile view.

Profile Detail View

The profile detail page has several sections:

Golden Record

The top section shows the golden record — the unified profile with the winning value for each attribute.

For each field, you can see:

• The winning value selected by the survivorship strategy
• Which strategy was used
• Which source record the value came from

Source Records

A table showing all source records in the cluster, with all their original attribute values:

This view lets you see the raw data from each source system and understand how the golden record was derived.

Identifiers

A summary of all identifiers associated with the profile, organized by family:

Merge History

The merge history shows the sequence of edges that linked the source records together:

Step 1: web_001 ←→ app_789
  Reason: Shared email (alice@gmail.com)
  Rule: "Email Match" (Priority 1)

Step 2: web_001 ←→ crm_456
  Reason: Shared identifier mapping
  Rule: "CRM ID Cross-Reference" (Priority 2)

Result: Cluster {web_001, app_789, crm_456}

This is valuable for investigating why records were merged and debugging unexpected merges.

Traits

If traits have been computed for the resolved entity type, the profile page shows the current trait values:

Audience Membership

A list of audiences this profile currently belongs to:

Investigating Merge Quality

The Profile Explorer is the primary tool for validating identity resolution results. Use it to:

Verify Correct Merges

Look up known customers and confirm that the right records are linked:

1. Search for a customer by a known identifier
2. Check that all expected source records appear in the cluster
3. Verify that no unexpected records are included
4. Confirm that the golden record attributes look correct

Investigate Suspicious Merges

If a cluster seems too large or contains unrelated records:

1. Open the profile and review the source records
2. Check the merge history to see which edges linked them
3. Identify the specific identifier and merge rule that caused the suspicious link
4. Decide whether to:
   • Add the identifier to a deny list
   • Tighten the relevant merge rule
   • Lower the cluster size limit

Find Missing Merges

If two records that should be linked are in separate clusters:

1. Search for each record separately
2. Compare their identifiers — do they share any identifier values?
3. If yes, check whether a merge rule covers that identifier family
4. If no shared identifiers exist, the records cannot be merged with the current configuration

Exporting Profiles

You can export profile data from the explorer:

API Access

You can also access profile data programmatically:

# Search for a profile by identifier
GET /api/v1/identity-graphs/{graph_id}/profiles?identifier=alice@gmail.com
 
# Get a profile by cluster ID
GET /api/v1/identity-graphs/{graph_id}/profiles/{cluster_id}
 
# Get source records for a profile
GET /api/v1/identity-graphs/{graph_id}/profiles/{cluster_id}/records
 
# Get merge history for a profile
GET /api/v1/identity-graphs/{graph_id}/profiles/{cluster_id}/history

Best Practices

• Spot-check after every resolution run — Look up 10-20 known customers to verify merge quality
• Investigate clusters at the size limit — These are the most likely to contain false merges
• Use merge history for debugging — When a merge looks wrong, the history tells you exactly which identifier and rule caused it
• Share profiles with stakeholders — Use the export feature to share specific profiles with marketing or data teams for validation
• Monitor singleton count — A high singleton rate (unmerged records) may indicate that merge rules are too restrictive or identifiers are not overlapping enough

Next Steps

• Golden Records — Understand survivorship strategies
• Running Resolution — Run or re-run identity resolution
• Merge Rules — Adjust rules based on explorer findings