Sramana Mitra: I heard two things in what you said so far. One is an increasing role of data and analytics. Secondly, an increasing role of mobilizing the workflow.
Mary Beth Westmoreland: Correct. Another thing that I would say is openness. We want to create an ecosystem. At Blackbaud, we don’t feel like we have to be the one-stop shop for everything even though we kind of are. We have beautiful comprehensive solutions. What we want to do is enable innovation through our cloud so that people who have a passion in a specific area can develop something different. The trend there is to leverage the openness of the cloud to do more things.
Sramana Mitra: I’m going to start double-clicking down into a couple of things. Before we do that, can you give me a little bit of an understanding of your customer base? I imagine you work with the alumni associations of different schools or development offices of the different universities.
Mary Beth Westmoreland: We do. As you know, most university systems have the equivalent of a foundational non-profit space where they are soliciting donations from their alumni and from other stakeholders. Some of the verticals are the health and human services or higher ed and K-12 institutions. We also serve the arts and cultural space. This is the museums and performing arts centres. That’s a really good question to ask because I don’t think people understand the broadness of the market. It’s not just what you would think of as traditional non-profit. It’s really everywhere.
Sramana Mitra: These kinds of use cases that you’re talking about of data analysis and mobilization, can you actually double-click down into a couple of these spaces and illustrate how they’re doing it. Let’s do one for the arts and culture space. You can take one of your clients or you can do it from a general segment point of view and illustrate more concrete use cases and workflows that you’re seeing both from an analytics point of view and from a mobility point of view. Do the same for the university alumni fundraising point of view.
Mary Beth Westmoreland: Those are two really good use cases. I’ll use analytics with the university use case. Then we’ll talk about an arts and culture organization and how they use mobilization. Universities have a really peculiar problem with analytics because they see a lot of turnover in their data. Four-year traditional students will become alumni. They see a lot of data that changes and moves.
They have the added burden of taking a lot of their internal systems and moving that to the foundational systems where they’re asking for gifts once that student leaves or graduates. The ability to have data hygiene services is where I would point you first. I’m a university system. Every year, I’m going to take my seniors and be able to solicit donations from them online. I’m going to take all of their data as a student and then I’m going to match it with some other social and contact information.
Then I want to be able to leverage that to be able to solicit them. The first thing that I would say matters is hygiene. We want to de-duplicate. We want to do checks on their addresses because a lot of times, the addresses that they’ll have as a traditional student is not the one that they’ll have as a professional. We may use social listening tools to be able to understand where they play in forums so we then tie that back to how we solicit them. Do they prefer a LinkedIn alumni group, email, or direct mail? We use analytics based on what we see across the ecosystem to engage in best practices.
For example, this single individual who just graduated may be someone who, as a millennial, would tend to respond better to a social inquiry versus a direct mail. Some people tend to give their time versus their dollars. You want to start with a volunteerism opportunity. We use those kinds of best practices in conjunction with analytics and hygiene to help that university system be able to engage better and more effectively.