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The sgENGAGE Podcast

Subscribe to The sgENGAGE Podcast to hear experts from across the social good community share best practices, tips and must-know trends that will help organizations increase their impact. Formerly called the Raise & Engage Podcast.
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Now displaying: June, 2018
Jun 21, 2018

Big data and data science are hot topics everywhere these days, and the social good sector is no exception. As nonprofit organizations continue to increase their use of data to answer questions about donors and fundraising and drive performance improvements, it’s important to understand as much as possible about data science. 

In today’s episode, I’ll speak to Carrie Cobb, Vice President of Data Science at Blackbaud. We’ll do a deep dive into the subject of data science. Listen to the episode to hear what Carrie has to say about the specifics of what a data scientist does, the techniques they use, and the variety of ways that data science is applicable in the social good community. 

Topics Discussed in This Episode: 

  • The differences between what a data scientist does compared to other types of scientists who deal with data, like statisticians
  • How data can help reveal answers to questions about why something does or doesn’t happen
  • The background and education common to data scientists
  • The techniques used by data scientists to try to find answers from a large amount of data
  • Whether it's helpful to separate what data scientists are trying to do from how they’re trying to do it
  • How data scientist deal with eliminating bias, error, and unknown information
  • What happens when the answer the data shows is disappointing
  • How data science is applied in the social good community for reasons beyond fundraising
  • The frequency with which predictive modeling should be done
  • Where data science trends in nonprofit organizations are headed over the next few years 

Resources: 

Carrie Cobb

 

“When you’re a data scientist you kind of dive into the unknown to find patterns and build connections and make predictions.”

 

“From a technical perspective, data scientists are highly educated. Almost 90% have at least a master’s degree, and almost 50% have Ph.D.’s.”

 

“I would say it is an art and a science put together. Depending on your paint and your canvas and what you’re trying to display, you’re going to choose different tools to get you there.”

 

Jun 14, 2018

Now more than ever, nonprofits need to ensure that they have high-quality, up-to-date data. However, a lot of nonprofit organizations struggle with the issue of data health. Why is data health so important in the nonprofit field today, and what can organizations do to bring themselves and their data up to speed? 

In today’s episode, I’ll be speaking with Adriene Chisholm and Alan Dix of Blackbaud’s Target Analytics about the new report from the Blackbaud Institute for Philanthropic Impact, Untapped Potential: The Case for Data Health. Listen to the episode to hear what Adriene and Alan have to say about the biggest struggles nonprofits face with their data and how it affects fundraising, what first steps organizations can take to move in the direction of better data health, and how to avoid those dreaded “yellow stickers.” 

Topics Discussed in This Episode: 

  • The most common data health areas that organizations struggle with
  • Why physical addresses are such an important piece of data
  • How data health can make fundraisers more efficient
  • Valuable data to collect beyond basic contact data
  • What organizations with a large digital presence should be doing to ensure their data is working for them
  • Why organizations shouldn’t rely purely on digital data
  • How to manage expectations about digital and social data
  • How digital data may be more restricted going forward due to privacy concerns and regulations like GDPR
  • First steps organizations can take to move in the direction of better data health
  • Where data health is going in the next several years 

Resources:

Download Untapped Potential: The Case for Data Health

Connect with Adriene Chisholm and Alan Dix

 

“We’re all trying to be C+ students by limiting our ability due to poor data health.” – Alan Dix

 “Maintenance is always easier. It’s a lot easier to maintain your car than it is to get it fixed after it breaks down.” – Adrien Chisolm

“Data health is easy, it really is. It’s like getting your oil changed. You know you have to do it every 3,000 miles, just go and get it done.” – Adriene Chisholm

 

Jun 7, 2018

We often hear about the need for organizations to take about taking a donor-centric approach to engaging supporters. But is that enough, or do nonprofits need to go even deeper to attract and keep donors over the long term?

Today’s guest is Kevin Schulman, founder and managing partner of DonorVoice, a retention and donor experience company. Kevin talks about why understanding donor identity can help organizations better understand the motivations of donors. He also explains how organizations can use donor segmentation to strengthen their relationships with donors, leading to long-lasting relationships that are beneficial for both nonprofits and their donors. Listen to this episode to hear the keys to leveraging a donor identity approach that results in improved outcomes.

Topics Discussed in This Episode: 

  • Why it’s important to understand the differences between different groups of donors
  • Why segmentation alone isn’t enough
  • The nuances of donor identity, and how it can help organizations to be more donor-centric
  • How the same donors can have different identities depending on which organization they’re engaging with
  • How to build content around donor identity categories
  • How to deal with objections to using donor identity
  • How focusing donor identity pilot programs on new donors can help organizations get past initial objections
  • How organizations can focus on donor identity using existing channels

 

Resources: 

Kevin Schulman

DonorVoice

 

“If we want to be donor-centric, you have got to get some level of understanding about who these folks are and what makes them tick.”

“In order to get the kind of data that you need, guess what? You’ve actually got to ask these people.” 

“There ought to be massive perceived risk with status quo, but oftentimes there isn’t.”

 

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