Case study at a glance
About this case study: this is an Infinite360 Tech Academy project case study delivered on a simulation environment with synthetic data. It shows the scope, architecture and approach our consultants and learners practise. It is not a client engagement and implies no affiliation with, or endorsement by, any company or brand.
| Industry | Insurance |
|---|---|
| Platforms | AEP, Journey Optimizer, Real-Time CDP, CJA |
| Type | Academy project case study (simulated environment, synthetic data) |
| Roles practised | Data engineer, AJO developer, governance specialist |
| Environment | insurance.infiante360techacademy.com |
The business challenge
An insurer's policy administration, claims and digital systems are disconnected. New policyholders receive generic welcome packs, claimants chase updates by phone and renewal reminders go out on a fixed calendar regardless of risk or engagement.
Target architecture
Implementation approach
- Policy lifecycle map — quote → renew
- Schemas & labels — sensitive data first
- Ingest — policy + claims
- Audiences — renewal windows
- Journeys — onboard, claim, renew
- Retention reporting — CJA cohorts
Use cases implemented
- Policy onboarding series with document reminders
- Claim-status update journey triggered by claim events
- Renewal reminders at 60, 30 and 7 days
- Retention offer for at-risk policyholders
- Cross-sell for single-policy households
- Retention cohort analysis in CJA
Validation and governance checks
- Health and claims data labelled and excluded from marketing destinations
- Renewal windows computed outside AEP and ingested as clean attributes
- Claims journeys tested for missing or delayed events
- Suppression rules prevent offers to customers with open complaints
- Every journey has an owner, purpose and version in its name
What Infinite360 brings
Architecture first
A documented target architecture, identity strategy and data model before a single journey is built.
Reusable accelerators
Schema patterns, naming conventions, backlog templates, QA checklists and runbooks reused across projects.
Validation discipline
Every stage is validated - payloads, identity graphs, profile fragments, audience counts and journey test runs.
Governance built in
Consent, data usage labels and least-privilege access are designed in, not bolted on at go-live.
Knowledge transfer
Walkthrough recordings, documentation and pairing so your team can run and extend the solution.
Day-one-ready people
Consultants and contract engineers who have practised the same pattern end to end before joining your team.
From case study to contract delivery
The roles that practise this case study — Data engineer, AJO developer, governance specialist — are the same profiles we place through contract hiring and staff augmentation. Because they have already built this pattern end to end, onboarding focuses on your systems and standards rather than on learning the platform.
Frequently asked questions
Should sensitive claims data be used for marketing?
Only where policy and consent allow. In the project, sensitive fields are labelled at ingestion so governance blocks their use in marketing activation.
Is this based on a real insurer?
No. It is a simulation built with synthetic data.
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