Case Study
Restoring Trust in Lifecycle Marketing Metrics for a Telehealth Startup
Client Overview
A high-growth U.S. based telehealth startup offering virtual care services. The company relied heavily on lifecycle marketing to drive patient activation, adherence, and retention — but faced growing concerns around the reliability of its engagement metrics.
The Challenge
As the company scaled, the lifecycle marketing team began to notice discrepancies between internal product events and downstream engagement data in Iterable. Campaign performance reports varied depending on the source, key metrics such as message delivery, opens, and conversions were difficult to reconcile, and leadership lacked confidence in dashboards used to guide spend and strategy.
The core issue was not tooling — it was event integrity.
Marketing events were being emitted from multiple systems, often without consistent naming conventions, payload structures, or validation rules. As a result:
- Events in the data warehouse did not always align with Iterable marketing events
- Campaign attribution varied by report and stakeholder
- Core funnel metrics (activation, adherence, re-engagement) were increasingly questioned
- Decision-makers hesitated to act on lifecycle insights
The organization needed a healthcare analytics consultant who could operate across data engineering, marketing analytics, and HIPAA-conscious environments — without slowing execution.
The Approach
Our healthcare data analytics consulting team partnered directly with Lifecycle Marketing, Data Engineering, and Product Analytics to conduct a full audit of marketing events across the stack.
The engagement focused on three parallel workstreams:
1. End-to-End Event Audit
We mapped the complete lifecycle of marketing events—from product instrumentation through ingestion, transformation, and activation in Iterable. This included a detailed comparison of:
- Product-generated events vs. Iterable-recorded events
- Event naming conventions and semantic meaning
- Payload completeness, timestamps, and user identifiers
2. Event Reconciliation Framework
We designed a standardized reconciliation process to validate parity between warehouse events and Iterable events. This allowed teams to:
- Quantify event drift and duplication
- Identify dropped or malformed events
- Detect timing mismatches impacting attribution windows
3. Metric Governance & Trust Layer
Working with stakeholders, we formalized definitions for lifecycle KPIs and tied each metric to a validated source of truth. This included documentation, data quality checks, and ownership models aligned with HIPAA and internal compliance requirements — critical for any healthcare analytics engagement.
Throughout the process, all analysis and remediation were conducted by U.S.-based resources experienced in handling PII and PHI, ensuring compliance and minimizing operational risk.
The Results
Within weeks, the lifecycle marketing team regained confidence in its data — and its decisions.
Key outcomes included:
- Full alignment between Iterable marketing events and warehouse data
- Clear, auditable definitions for lifecycle engagement metrics
- Improved campaign reporting consistency across teams
- Faster experimentation cycles driven by trusted insights
- Executive dashboards that leadership could act on without caveats
Most importantly, lifecycle marketing shifted from debating numbers to optimizing outcomes.
The Impact
By treating marketing events as governed data assets — not just tracking artifacts — the company transformed its analytics foundation. Lifecycle performance reviews became sharper, investment decisions more defensible, and cross-functional trust markedly improved.