Alumni relationship data quality
Engagement teams struggle to maintain accurate contact and preference data across alumni systems.
The challenge behind the workflow.
Engagement teams struggle to maintain accurate contact and preference data across alumni systems.
Connect student, course, finance, research, and service information while respecting purpose and access. Help educators and administrators understand participation and operations without reducing a learner to an automated score.
Data to bring together
- Alumni profiles
- Engagement histories
- Contact preferences
Source systems are examples of the data required. Confirm connector availability, permitted access, refresh timing, and the authoritative owner before implementation.
How Genedata supports the work.
Configure one connected workflow, then reuse its mappings, definitions, and review process as the business grows.
- 01
Connect and prepare
Reconcile approved identifiers and preserve the origin of preference changes.
Build the preparation as a reusable visual workflow or reviewed code, with explicit source mappings and validation checks. - 02
Investigate and validate
Identify duplicate candidates, stale records, and conflicting contact permissions.
Keep shared definitions and source versions with the analysis so another team can reproduce the result. - 03
Publish and review
Deliver an owned relationship quality queue and reusable permitted audience views.
Make the output available to the right people with appropriate access, ownership, and review evidence.
An alumni data quality workspace
Make the next run easier.
Shared preference checks reduce bespoke filtering for each alumni initiative.
Start from one approved example. Save the agreed mappings and definitions, publish the reviewed output, and let the next team follow the same evidence instead of rebuilding the preparation.
Measure your own improvement
Unresolved contact and preference discrepancies
Record a baseline before the pilot and compare like-for-like work afterward. Results depend on source quality, configuration, and adoption.Review and responsibility
Relationship owners approve merges and outreach purpose before activation.
AI with professional judgment.
Use AI to summarize institutional data and explain patterns. Educators and authorized staff review interventions, admissions, funding, and sensitive student decisions.
Try the workflow with your team.
Use representative, approved sample data. Agree the expected output and a review owner before extending the workflow to a live process.