From online shopping to online dating, our daily interactions are increasingly going digital and, as a result, generating a huge amount of data about our behavior. Companies like LinkedIn, Netflix and Amazon use this information to better serve their customers in an efficient way and nonprofits are now starting to do the same thing.
Data science is the art of turning the massive amount of data out there into actionable information. If you think of advancing your nonprofit’s mission like driving a car toward a destination, then data science represents all the tools you’d use to navigate the many twists and turns your organization needs to make to get there.
To understand how well you’re serving your constituents and anticipate their future needs, there are three main types of insights that data science can provide to help your organization work even smarter:
For a real life example, let’s take a nonprofit that is at the forefront of using data science to advance its mission. One of DataKind’s partner organizations, Crisis Text Line, is a free, 24/7 text line available nationwide that connects anyone in crisis to crisis counselors. Anyone can text Crisis Text Line from anywhere in the U.S., at anytime, to receive support. Having handled over 5 million text messages to date, Crisis Text Line has a tremendous amount of information to help them maximize their impact. They already have a data scientist on staff, Bob Filbin, focused on using the organization’s data to inform its daily work. They also recently partnered with DataKind and volunteer Noelle Sio of Pivotal on a DataCorps project to do even more with their data.
Let’s see what descriptive, predictive and prescriptive insights came out of it.
Photo by Dean Shareski
Descriptive insights measure past activity and usually involve counting how many times something happened. It seems simple, but sometimes you’re trying to measure something fuzzy and hard to quantify - like gratitude. During their recent project together, DataKind volunteer Noelle helped Crisis Text Line get a better view of how helpful the texters found their conversations by measuring gratitude in the texts themselves. She used a technique called text analysis to count the number of “thanking” words (thank, thx, thnx, tks) in the messages. This would be impossible for a human to do in any kind of efficient way because of the sheer volume of messages to look through. Thanks to data science, Noelle was able to take a fuzzy concept like “gratitude” and measure it so Crisis Text Line can better understand its impact on those it serves.
Photo by MoDOT Photos
Most crisis centers and hotlines face the challenge of prioritizing incoming requests. Given the high volume of texters and their wide range of needs, how can Crisis Text Line quickly respond to those requiring urgent interventions? How can they help direct those with ongoing needs to appropriate long-term support? By analyzing Crisis Text Line’s data of past conversations between texters and crisis counselors, Noelle discovered that people who text in more than four times or use words like “school,” “friends,” or “hurt” in their texts are likely to become “repeat texters.” Repeat texters may indicate an individual that needs to be directed to long-term support. By identifying potential repeat texters early on, Crisis Text Line can better triage incoming requests and better respond based on the individual’s needs.
Photo by Doug
With further analysis, Crisis Text Line may be able to not only predict who is likely to be a repeat texter, but also to make automated suggestions to counselors on what to do about it. Once Crisis Text Line further investigates the different types of repeat texters and their varying needs, they could then prompt their crisis counselors with suggested actions to take. For example, the crisis counselor might be prompted to ask certain questions or suggest certain resources based on the texter’s needs, thus enabling Crisis Text Line to provide personalized support on a massive scale.
Many organizations worry they’re not ready for “big data” or “data science.” However, time and time again, we’ve seen that organizations that don’t consider themselves data companies have huge opportunities to use data science in their missions. Like Crisis Text Line, your organization can use data science to improve its programs, better anticipate needs, or scale your services while still providing customized support to your constituents.
Here’s how to get started: