The Australian Conservation Foundation implemented a Microsoft Azure–based data platform to bring together fragmented CRM data, enabling a single view of supporters and more efficient data analysis. This provided greater insight into donor behaviour, improved visibility of impact, and created a future‑ready analytics foundation.
Benedict Chiu, Head of Data and Technology, ACF
We went out to market with the brief to design and build a data lake which pooled the information from all our CRM’s – after scouring the market we came to the conclusion that Rapid Circle was the ideal choice – they had the balance of capabilities and experience to rapidly execute and achieve our desired outcomes
Australian Conservation Foundation (ACF)
Not for Profit | Government & Council
Australia / New Zealand
Azure, Data & AI, Infrastructure, Power BI, Microsoft 365
Disparate CRM systems with no integration, limiting effective reporting, analytics and supporter insight
A tailored Azure‑based data lake and analytics platform integrated with existing Microsoft tools
More efficient data analysis, reduced upgrade costs, cloud adoption for remote workers, and improved insight into supporter behaviour
The Australian Conservation Foundation had several Customer Relationship Management (CRM) data repositories that housed critical information on over 700,000 people. Their two primary CRMs, Blackboard and NationBuilder, gathered information on supporters and donors which in some cases represented the same individual.
These systems were disparate, had no integration, and did not allow effective reporting and analytics. ACF sought a solution that would enable a single view of their supporters and allow them to gain greater insight into supporter needs and behaviour.
Multiple off‑the‑shelf solutions were assessed, but it was decided that a tailored solution was required — one that would enable machine learning, future growth, and experimentation with analytics.
We were able to say this is what we are after and what outcomes we wanted, and Rapid Circle would go away and build it. Then we would have regular meetings and updates, which was very reassuring.
After refining their future data vision, ACF engaged Rapid Circle to develop a technical solution that met their requirements. Rapid Circle began by assessing the current state of ACF’s data hubs and then co‑designed a long‑term solution together with ACF’s Data Operations team, supported by a clear implementation roadmap.
Given the nature of ACF’s datasets and technologies, Microsoft Azure was selected as the preferred cloud data platform due to ACF’s in‑house capabilities and the opportunity to integrate closely with the Microsoft 365 suite already in use.
Rapid Circle configured Azure using proven data lake best practices, establishing a foundation that supports future growth. Using Azure data lake services enabled seamless integration with Power BI, providing near real‑time reporting on ACF’s supporter base and delivering a level of insight not previously available.
The use of Azure data lake services and Power BI positions ACF for future objectives including semantic modelling, deep learning, and real‑time analytics.
We will continue to partner with Rapid Circle and are very happy with the data and engineering services provided. We look to Rapid Circle as a trusted partner and authority on Microsoft and Azure services.
The work undertaken by Rapid Circle gives ACF a clearer picture of its donors and supporters and has enabled ACF to gain insights into preferences that drive investment and awareness decisions. It has also allowed ACF to see the size and growth of their supporter community and better measure their impact.
As a result, ACF is better equipped to promote environmental causes and lobby stakeholders for the benefit of the environment and broader society.
ACF and Rapid Circle continued their partnership through a second phase, integrating a new Blackbaud analytics platform with ACF’s Azure data platform. This provided more timely supporter analytics and shortened the organisation’s insight cycle.
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