Taking a Charitable Approach to Big Data

By Samuel Greengard Print this article Print
Big Data

National Trust, one of the United Kingdom's leading charitable organizations, adopts big data blending technology to improve its efficiency and boost donations.

Charitable organizations are under enormous pressure to operate more efficiently. The United Kingdom's National Trust, a 120-year-old nonprofit landmark preservation society that owns more than 350 properties encompassing approximately 610,000 acres in England, Wales and Northern Ireland, understands the concept well.

"We have more than 4 million members in the U.K., and it is important to approach donors the right way and market the organization effectively," says Dean Jones, head of data science for National Trust.

In the past, the task presented significant challenges. "We haven't always had a rounded picture of donors," he acknowledges, "and we have lots of different units within the organization that need to communicate with them. As a result, we haven't always been able to talk to donors in a way that is most relevant for their membership or their needs."

Among the IT issues contributing to the problem: an inability to combine databases and use data in a more holistic way. "We did not have a central database or source to work from," Jones adds.

Gaining Control of Donor Information

National Trust turned to a data blending, advanced analytics and reporting solution from Alteryx to gain control of donor information. It went live with the system in 2014 and hasn't looked back.

The initiative has helped the organization move beyond sending a single marketing message to the entire donor base and it now sending specific campaigns and promotions that reach the right people in the right way. National Trust can now segment donors by numerous criteria, including demographic characteristics, properties they have visited, where they come from and how much they typically donate. It can also examine those who visit but don't donate.

At one of National Trust's properties in Cornwall, for example, the organization examined data patterns for visitors and discovered that it had a split audience. During the summer, the park tourists from all over the U.K. and Europe visited the park, but in the winter, it was typically frequented by locals.

Using the Alteryx software, along with a data analytics solution from Tableau, Jones was able to identify behavioral patterns, and he subsequently changed the way the organization communicates with locals during the summer. By downplaying the National Trust brand in communications and focusing on events, such as a major concert, the organization was able to triple attendance from the local populace.

The biggest challenge, Jones reports, was tying together multiple data sources and ensuring that all the data was clean and usable. That meant eliminating multiple entries and, in some cases, managing more than one valid record for a particular address. It also required the use of drive-time data and weather records.

"It was important to assemble data points that provided useful results and allowed us to take a more focused approach," he says.

Today, National Trust experiments with messages to discover what works best—and then puts winning approaches to work. Although the analytics program is still in the early stages, "The technology has fundamentally changed the way we communicate with the donor base," Jones explains. "We are able to personalize communications and make them highly relevant.

"This has helped us use internal resources far more effectively and achieve results that weren't possible in the past."

This article was originally published on 2015-07-16
Samuel Greengard writes about business and technology for Baseline, CIO Insight and other publications. His most recent book is The Internet of Things (MIT Press, 2015).
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