A Simple Guide to Data Analytics for Nonprofits

More than a trend or a buzzword, data analytics are here to stay. Newcomers to arts management may find themselves asking, what does data analytics mean for me, and how and why does my organization need to use it? If you are new to arts management, or the data world in general, this two part series is for you!

In an effort to improve mission-based programmatic success and retain a loyal audience base, arts organizations are utilizing tools that have become available as a result of the 21st century technology boom. In particular, many organization leaders have made the switch from verbal communications with patrons and donors to technological software that efficiently pulls information from the aforementioned groups. The practice of data analytics has been a widely recognized tool for understanding organizational efficacy and sustainability over the last ten years. Still, many arts managers cannot fully comprehend the necessity for using data analysis tools in their day-to-day operations, especially if their organization is small or newly established. This paper aims to give readers detailed information about the uses, types, and long-term benefits of data analytics in the arts management field.

Overview

 There is a vast amount of data analytics tools and software that exists, all of which can significantly further the mission and programmatic aspects of a nonprofit organization when used consistently over time. In general, data analytics refers to the collection of internal and external information about quantifiable metrics that relate to an organization’s performance strategies and tactics for future success. Analysis tools can be used by arts managers to find improved ways to reach and appeal to desired audience segments. The extent to which data analytics can inform an organization is vast and perhaps overwhelming at times; however, this means that arts managers can tailor their analysis to measure only the metrics that are relevant to their mission and programming. In fact, the majority of nonprofits use data analytics to track crucial financial and operations metrics in order to make budgetary decisions for future programming. Indeed, the core reason for implementing data analytics practices should be for the expansion of the organization’s mission: “Tracking program and outcome-related data should be the bread-and-butter for nonprofits because it’s one of the best ways to articulate what they are delivering and the extent to which they are delivering on their mission.” It is of critical importance that arts organizations focus on measuring the data that is directly relevant to desired effects and impacts in their respective cultural communities—that is, focus on the information that will yield the highest level of optimization for the goals at hand.

Image: Blurred image of a Google Analytics dashboard.

Image: Blurred image of a Google Analytics dashboard.

 In terms of the types of technological platforms that can perform data analysis, the options are vast. Due to Google Nonprofit opportunities and pure dominance in the field, the most well-known tool is Google Analytics, which gives organizations the opportunity to understand website data with easy-to-use metrics. The most informative aspect of this software is the ability to track the location and search engine use, which can answer questions regarding the reach of the organization and how users are accessing its online platform. Moreover, Google Analytics allows users to customize the analysis with specific goals, so that organizations can easily access and track those metrics that are critical to long-term success.[7] Another basic tool that all organizations can easily implement is the use of tags and Google tag manager. Tags allow organizations to track website content, traffic, and interaction as a means of understanding simple data on their digital platforms.

 Arts managers seeking to gain more detailed insights and create metric-reporting visualizations can turn to other analytics software such as Tableau, Domo, and SAP Analytics Cloud. Tableau, for example, brings data analytics to your computer or mobile device with easy-to-understand visualizations and built-in statistical tool sets that turn hard data into real-world solutions. It also functions as an expanded version of Google Analytics in that it combines spatial/geographic data with up-to-date data sets on demographics such as population, race, sex, and income . For arts managers that require data-driven visualizations for board reports or government-sponsored grants, Domo excels as an application that converts numeric data into illustrious story-telling. Organizations can tailor the analysis to have Domo’s software survey data sets and then suggest to the best visualization for efficiently understanding metrics. Yet another commonly used analytics software is the SAP Analytics cloud, which is unique in that it incorporates artificial intelligence to organize the most complex big data and yield accurate predictive analysis for the organization’s future trends. This software also contains a built-in financial planning feature, which reduces the need for nonprofits to have too many disparate digital platforms to track daily operational inputs.

Types of Data Analysis

Image: Computer screen with icons of different data types.

Image: Computer screen with icons of different data types.

There are a myriad of ways in which data analytics tools can inform organizations about past, present, and future activities. Analysis that reports on current metrics can identify the most loyal patrons and audience members, assess which programming they attend frequently, and allow organizations to then appropriately target said individuals with relevant marketing and programming tactics. For example, understanding the consumer-based trends within an organization can be a key component in developing consistent ticket-buyers for major programming. Another data analytics tool on the rise in recent years is Social Listening, which tracks instances where your organization is mentioned digitally. Arts managers can utilize this tool to actively analyze who is talking about their organizations and in what context; hopefully, consistent Social Listening can aid arts leaders in the quest to understand who they should target and how. Conversely, some nonprofits can choose to conduct analysis on external data in an effort to glean information about specific demographics within their communities. Sometimes referred to as “big data”, these types of metrics are compiled of “very large, very diverse data sets” about a multitude of environmental segments, such as average age in a community or socioeconomic statuses in a city. While this type of analysis can be quite informative about an organization’s community, big data should be used sparingly in making major operational decisions. Knowing general demographic information is definitely an asset for arts organizations, but the most impactful change will stem from data-driven decision about internal metrics.

Image: Chart of the sources of nonprofit data. Credit: NTEN, “ The State of Nonprofit Data ” (2012)

Image: Chart of the sources of nonprofit data. Credit: NTEN, “The State of Nonprofit Data” (2012)

In terms of the types of analysis that can be done, organizations can tailor the output based on the overarching result they are seeking (i.e. mission advancement, programming expansion, donor acquisition, etc.). Statistical analysis incorporates regression and frequency models to make new predictions based on prior donor and patron behavior. Arts organizations can create a model with accurate numeric data and plug in various inputs to understand how different scenarios might play out. Forecasting is a type of analysis that tells organizations about when resources will be needed and how much. For example, a financial director might use forecasting to understand how budgets should be allocated given the current monetary trends within the organization. A more simplistic, yet highly valuable analysis is known as segmentation or descriptive analysis, which divides data sets (audiences/donors) into groups so that organizations can understand the variations among their constituents. Organizations that wish to hypothesize about future audience and patron behavior should implement predictive modeling, which uses a combination of historical and comparative data sets. In keeping mission-related goals in the forefront of operations, arts managers would benefit greatly from employing optimization analysis. Data analytics used to this end is perhaps the most efficient way to keep organizations on track with their financial, programmatic, and mission-based goals; the analysis helps lead staff to see how operations can be improved or which tactics are yielding the best results.

Part II of this series is coming soon!

Resources

Blackbaud, “The Definitive Guide to Nonprofit Analytics,” (2014).

Cardinal Path, “The State of Digital Data in the Top 50 Nonprofit Organizations in the U.S.,” (2016).

CDW, “A Technology Boost for Fundraising,” (2016).

Idealware, “The State of Nonprofit Data,” Nten (2012).

Kathleen Grennan, “A Handbook For Arts Managers: How Google Analytics Can Help Solve Operational Challenges,” AMT Lab (2016).

Christine Sajewski, “Making Data-Driven Decisions For Marketing-Focused Outcomes,AMT Lab (2016).

Wei Wei, “An Arts Organization’s Guide to Integrating Digital Analytics into Social Marketing,” AMT Lab (2017).