National
Animal Charity
Microsoft Dynamics CRM
Master Data
Data Integration
Organisation-wide
Customer and Supporter Data

A national animal charity was progressing a wider change programme designed to support its long-term strategic objectives. A key requirement was to create a single customer and supporter view by bringing together information held across multiple, disconnected systems.
The Golden Record project needed to establish a clean, consolidated and reliable data foundation that could support the charity's implementation of Microsoft Dynamics CRM and provide a clearer view of how customers and supporters interact with the organisation.

Supporters and customers interacted with the charity through multiple channels, but the existing CRM environment could not unify those interactions. Data was spread across disparate systems, with differing levels of completeness, accuracy and consistency.
Without a single supporter view, teams had limited visibility of relationships and interactions across the organisation. The move to Microsoft Dynamics CRM created an immediate dependency: the charity needed a cleansed Golden Record that could be taken into the new platform rather than carrying fragmented and inconsistent data forward.

Project Recovery: Maxica was commissioned to take control of a project that was not delivering the required momentum, introducing professional project management, governance and coordinated stakeholder engagement.
Data Discovery: Twelve initial data sources containing 5,360,643 records were identified as necessary to create a comprehensive master record.
Data Quality Rules: Analysis of the source data identified negative trends and informed custom rules to exclude organisational data, remove false entries and filter records that did not meet minimum quality requirements.
Integrated Delivery: Maxica worked with the IT team to establish API feeds into a central data lake, creating a controlled staging point for processing and matching contact data.

A data matching tool extracted relevant personal information from the source systems and matched records to create a unified master record. API feeds moved data from the 12 sources into a central data lake, where it could be processed consistently before matching and consolidation.
The rule base removed unsuitable entries and standardised the most recent address and contact information. This produced the Golden Record: a consolidated data set designed to support Microsoft Dynamics CRM and give the charity a stronger foundation for understanding customer and supporter interactions.

5.36 million source records assessed: Data from 12 systems was brought into a controlled consolidation process.
4.34 million individual records created: The matching and cleansing process produced 4,342,516 unified individual records.
19% record reduction: Consolidation removed duplication and unsuitable records while retaining the information required for the Golden Record.
Delivered within one year: Maxica took the solution from project recovery through to go-live within a year, while creating a scalable foundation to incorporate further data sources.

The engagement combined project recovery, data governance, technical integration and stakeholder management. Rather than treating cleansing as a standalone technical exercise, Maxica connected the data work to the CRM programme and the charity's wider requirement for a single customer and supporter view.
"Maxica has delivered exceptional management of the project from discovery, data audits, governance, planning, budgeting as well as effective communication and relationships with many different stakeholders. It has enabled insights driving strategic decisions all the way up to senior leadership and trustee level. As a result of this project, we have been put forward for an award at the Chartered Institute of Fundraising."
Head of Data and Analytics

If fragmented customer data is limiting your CRM transformation or preventing a reliable single customer view, Maxica can help bring project delivery, data governance and integration together to create a practical route to cleaner, more usable data.
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