Global Healthcare Technology Client — Use Cases

The client had grown across multiple business units and regions, leaving a fragmented MarTech landscape: disconnected platforms, separate data environments, inconsistent integration standards, and no centralized view of the customer. As Senior Business Relationship Manager embedded in IT, the role was to own the relationship between IT and the marketing business units — translating strategic needs into technical plans and holding both sides accountable.

A Customer Data & Insights initiative was established as the formal program framework — articulating why centralized customer data was critical to the business, how a connected platform ecosystem would be built, and what the operating model between line-of-business teams, IT/data engineering, and reporting/analytics teams would look like. The program also developed best-practice guidelines for onboarding new platforms and datasets as the organization continued to evolve its global technology environment.

The audit surfaced a complex, fragmented stack spanning multiple marketing automation, messaging, social, CRM, analytics, and regional platforms — all with varied integration processes, separate data environments by business unit, and no unified reporting layer. Critically, the audit uncovered that foundational identity architecture required for full CRM integration had never been fully established, leaving the enterprise marketing automation platform only partially operational for several years.

The problem statement was formalized for leadership: business units were operating independently, with inconsistent integration patterns, fragmented reporting tools, and no central customer data environment across the enterprise. This became the anchor for the platform consolidation proposal — presenting both the opportunity cost of inaction and a concrete path to unification.

Rather than immediately committing to a full marketing automation migration, a structured pilot was proposed: leverage an existing product campaign to validate the target platform's end-to-end capabilities — lead nurturing, MQL generation, CRM integration, optimization, A/B testing, and reporting — while keeping scope lean to minimize resourcing cost and validate assumptions before full commitment.

The pilot proposal was presented to executive stakeholders across Marketing, IT, and business unit leadership, outlining the problem statement, opportunity, executive summary, and specific asks of each leadership group. A separate IT POV was developed documenting the discovery findings, surfacing longstanding implementation roadblocks, and presenting two concrete decision paths forward — with tradeoffs, dependencies, and recommended next steps for leadership to decide between.

To execute the migration at the required scale and pace, a dedicated team of 14 contractors was hired and managed under A. Bui Consulting — spanning marketing automation architects, platform developers, CRM engineers, analytics developers, and data engineers — all embedded specifically for this engagement.

The migration scope was extensive: establishing the foundational CRM identity layer that had blocked full integration for several years; migrating 100+ assets and system automations from the legacy platform to the target marketing automation platform across multiple product and lifecycle campaigns; building new journey architectures; enabling platform-native optimization capabilities; activating web analytics tracking; establishing a new cloud data environment for unified marketing, CRM, and third-party data; creating new marketing dashboards; and building and delivering a full digital training program enabling the internal marketing team to operate the platform independently.

The roadmap was structured across four stages: foundational implementation — identity architecture, data sanitation, controlled deployment design, and optimization readiness; early-stage adoption — pilot buildout, legacy-platform migration, CRM synchronization, initial personalization, and A/B testing; mid-stage adoption — omnichannel journey orchestration, audience-based marketing, paid-media activation, and behavioral analysis; and late-stage adoption — fully connected AI-enabled campaigns, advanced personalization, next-best-action decisioning, advanced measurement, and customer data platform readiness assessment.

Each stage was mapped across planned data outcomes, marketing program priorities, campaign development, platform enhancements, CRM integrations, and analytics buildout. A representative product-level roadmap was also developed alongside the enterprise roadmap — providing a concrete campaign-level illustration of how each platform stage would translate into real marketing programs.

The CRM identity layer was the single most critical technical dependency blocking full utilization of the marketing automation platform. Without it, the marketing platform and CRM could not reliably share contact identity, campaign activity data could not flow into CRM for sales visibility, lead scoring and MQL workflows could not be fully activated, and the enterprise customer-data vision was effectively on hold. A formal proposal was developed for this workstream covering platform audit, technical feasibility analysis, controlled implementation design, resourcing, and execution.

Parallel data architecture work mapped the conceptual data flow across the full environment — including the cloud integration layer, enterprise data warehouse, ERP environment, data transformation pipelines, marketing staging environment, and data engineering views — identifying integration gaps and defining what a centralized customer data fabric would require to support omnichannel marketing at scale. The goal was to move from business-unit-specific pipelines and custom APIs to a unified data layer that marketing platforms could consume, reducing dependency on data engineering for routine campaign segmentation.