Problem
During a rapid growth phase in healthcare DX, the company's customer data was fragmented across more than ten locations: internal databases, kintone, Excel files, and other sources. No single system held a reliable view of any given account or contact.
The marketing team was spending more than 30% of its working time on data management: compiling contact lists, cleaning records, and preparing campaign inputs manually. The complex many-to-many relationships between healthcare facilities, physicians, and agencies added another layer: that logic lived in the heads of specific individuals, not in any system.
The result was a team with limited capacity for strategy or campaign execution, operating on data they couldn't fully trust.
Work
We designed this as a data integration and operating model project, not a tool setup. The goal was to give the team a foundation they could use daily without ongoing manual overhead.
- Data integration architecture: consolidated all customer data sources into HubSpot as a single source of truth
- Relationship modeling: recreated the complex many-to-many structure between facilities, physicians, and agencies in HubSpot's object model
- Automation setup: built integrations with kintone and other source systems to eliminate manual sync and update tasks
- Operational enablement: provided role-specific training and adoption support so the team could actively use the new foundation from day one
Result
- Data management and extraction work reduced by approximately 65%, freeing about 100 hours per month across the marketing team
- Marketing team shifted from operational to strategic execution: campaign planning, LTV strategy, and initiative design
- More personalized campaign execution: customer attributes and relationships now queryable in real time
- Real-time ROI visibility: initiative-level tracking without manual aggregation
Why it matters
The constraint wasn't capacity. It was that the team's capacity was entirely consumed by infrastructure work that should have been automated. When 30% of your time goes to list preparation and data cleanup, you don't have a people problem, you have a systems problem.
Solving it didn't just free up time. It changed what the team was capable of. Campaign precision, strategic planning, and LTV-level thinking all require a data foundation that's trustworthy and accessible. This project built that foundation and made sure the team could actually use it.