Name: Product Update Briefing - Data Intelligence
Uploaded: 2025-05-08T19:30:52.802Z
Duration: 59 min 4 s
Description: Product Update Briefing - Data Intelligence

Transcript for "Product Update Briefing - Data Intelligence": Everybody, thank you for joining us today. This is the data intelligence product update briefing, for first quarter, first several months of '20 '20 '5. So before we jump into the content, as always, we wanna start with some housekeeping items. The webinar audio will be broadcast through your computer speakers. So, hopefully, you all can hear me. If not, if you just see my mouth moving right now, where you need, captions, you can hover over the stage and click on there's a little CC button on the bottom of the screen that'll turn captions on and off. And if you are encountering any issues, audio, technical, otherwise, usually just a quick refresh of your browser is the best way to get it working again. You'll notice that there is a q and a button at the top right, and you can use that to submit any questions that you have for us today. When you do submit those questions, please make sure to be as specific as possible. The more details, the better we can address your question. We do have a team here in the background who will be answering questions as we go throughout the webinar, but sometimes there might be questions that Sam and I will try to address at the end. And so if that's the case, again, the more context you can provide, the easier it'll be for us to to give the answers. Next to q and a, you should see, I believe it says docs. You can click on this to access several links and resources that you may want to access during our presentation and maybe save for future reference. You can also adjust your settings by using the cogwheel at the bottom of the event space. And finally, you can also use the tabs on the top of the event space to see today's agenda and learn a little bit more about your speakers, about Sam and myself today. So our safe harbor statement, this presentation does contain forward looking statements that involve inherent risks, uncertainties, and assumptions. It outlines the Blackbaud's current plans and general product direction as of the date this presentation was created. Functionality described in this presentation that is not currently available is subject to change at any time without notice at Blackbaud's sole discretion. It does not represent a commitment to develop or release specific features within the time frame discussed according to the presented design or at all. So it's really important to please make sure that any purchase decisions you're making are based on features and functionality that are currently available. So over the past few years, Blackbaud has made a significant investment in security. Our program is always evolving to prevent and detect current threats and to anticipate future threats. All these changes were designed to evolve and protect our products and customers. The work is ongoing, and it all ties into a common goal, which is to mature our cybersecurity program against industry best practices to ensure a comprehensive and effective program that can prevent and detect current threats and also anticipate future ones. So we've aligned our program to the cloud security alliance reference architecture, which creates a common roadmap to meet the cloud security needs of our organization. So this is both a methodology and a set of tools that enable us to fulfill a set of common requirements that risk managers must use to assess the operational status of internal IT security and cloud provider controls. We've matured our program against the NIST framework, which focuses on identification, protection, detection, response, and recovery. We focused on strengthening our program against the CSA's cloud controls matrix. So CSA is the world's leading organization dedicated to defining and raising awareness of best practices to ensure a secure cloud computing environment. Blackbaud is the only company exclusively focused on social impact to have received the designation of trusted cloud provider from the Cloud Security Alliance, And we have matured our cyber risk management program to improve how we identify, qualify, quantify, and reduce cyber risk. Aligning our program to these frameworks have allowed us to adopt a defense in-depth strategy when it comes to protecting our systems and data. So we wanted to talk about this today because we have a specific example from our analytics portfolio, which is ResearchPoint. Encryption has been an area of overall focus for cybersecurity improvements, and we have broadened encryption of data at rest for production data and backups by enabling TDE, which stands for Transparent Database Encryption for ResearchPoint. TDE is an industry standard best practice methodology that provides customers with the added security of full database encryption for all fields, including free text note fields. These enhancements help to maintain the confidentiality and integrity of our customer's sensitive information. So, again, we wanted to provide an update for research point clients about where we are as of today. So as of today, all new customers are being put into the public cloud where their databases are running on SQL with TDE, Transparent Data Encryption. We began relocating our existing clients from private cloud in July of twenty twenty four and have recently completed all relocations. So, again, wanted to call this out. If you own Grateful Patient Services and you've been waiting for TDE before using ResearchPoint, know that this is now available to you. And I suppose maybe we should take a step back and do introductions here as well. So nice to meet you all. My name is Carrie. I am a product manager on our data intelligence team here at Blackbaud, and I've been with the company for about seven years at this point across a couple different teams. And I'm joined by Sam. Hey, everybody. I'm Sam Vedable. I'm the senior manager of the data intelligence product team, and both Carrie and I are so delighted to be here. Thank you for spending an hour of your day with us. We've got a lot of exciting things to get to, so let's jump into it. So I wanted to start out by setting the stage a little bit. Today's presentation is a little bit different from some of the other product briefing sessions product update briefing sessions that you might be attending. So other sessions typically will support or talk about feature teams who are supporting a specific, products like razor's edge NXT or financial edge NXT, for example. But our team is responsible for enabling our customers to be able to leverage cutting edge data intelligence across all of our solutions. So this means today that we're gonna share some updates that are happening behind the scenes, but have a large impact on all of our data intelligence capabilities. And it also means that some of the content that you'll see today in our presentation may be referenced in other sessions as well. Most notably, in the razor's edge NXT session. So what does data intelligence mean? Ultimately, our data intelligence capabilities help you translate data into value, so that you can move your mission forward. And we aim to do that by bringing three assets to bear. Rich tapestry of data that leans on more than twenty years of expertise, creating data intelligence solutions, and the strongest, most robust philanthropic data set in the market. What's it saying? To understand the future, you've gotta understand the past. Artificial intelligence, that leans on our intelligence for good strategy, making sure that we're delivering AI that's powerful, responsible, and accessible. And finally, actionable insights, because we know that analysis without action is really meaningless. Right? It's not about charts, data, and predictions. It's about what you do with it. Our data, AI, and actionable insights help you answer many of the questions, once we've all struggled with in the fundraising sector. Some of them are over on the left hand side of this slide. Really help you kind of work through this. Right? And we're really trying to drive meaningful progress against a variety of giving time horizons and gift sizes. So maximizing your opportunity in annual giving or direct marketing or sustainer or peer to peer or major in principle and planned gifts. So let's talk a little bit about intelligence specifically. Intelligence is really the intersection of three distinct domains, data, predictions, and outcomes. We start with data. We make a prediction about what's likely to happen based on that data, maybe a likelihood to give, for example. And then outcomes really contextualize these data and predictions. And this creates a beautiful flywheel effect. Right? The individual domains really act as accelerants to each other. And there are things that we can do to really improve in each of these domains. We can think about expanding our data set. We can change the technology that we're using to deliver some of the predictions, and then we can think about how we can drive some of the outs outcomes and actually serve them up in some of our application experiences. But every once in a while, there's a new technology that comes along that really significantly accelerates the speed at which you can iterate. And artificial intelligence is that moment for us, and we believe that it is gonna be transformational for the nonprofit sector. But that means we've gotta pay extra attention to the quality of the data. We've gotta think differently about where and how we make predictions, and we've got to understand and embrace the impact of near, more direct rather, and near real time connections between our data predictions and outcomes. So this diagram here is really at the heart of what we're working toward in the data intelligence group. How can we help accelerate the power of intelligence, not just in our applications and our products, but how do we drive this across the entire company? So we're we're gonna use this framework to guide our discussion today just like we have in the past couple of pubs In the context of outcomes, where we'll start, we'll we'll talk about prospect insights and fundraiser performance management. On the data front, we have some updates in terms of some news that we shared back in the November pub about some of upcoming enhancements to our data. And on the predictions front, we'll talk about changes that are coming to prospect insights, Blackbaud Copilot, and our model delivery. Note though that even if you don't see the specific product that you own from the data intelligence world, specifically on this list, know that every product that we provide is gonna be touched in some way by what we share today. So I wanna double down on this a bit a bit. I know that I mentioned it, you know, the enhancements to our data are going to be a really big deal, and we've got some exciting, data points to be able to share with you here later. And and they're really gonna lead to some dramatic improvements in just about every single product. So let let's start with outcomes here. You know, outcomes really starts and ends with using data and building predictions that have some sort of outcome in mind. Right? We wanna be able to find more donors. We wanna make an ask that they're actually likely to give. Maybe we wanna use language on a peer to peer fundraising page that's more likely to persuade or engage. Right? Because of our AI platform here, we can really incorporate some of those outcomes into a feedback loop to really consistently and constantly improve the performance of our models, adapt as donor behavior evolves, and really any outcome produces data that then we can use to consume internally. So we also wanna make sure as part of our experiences that we're providing exposure to our customers across the entire products. We when we feel like that insight and awareness will drive outcomes. So outcomes are really at the heart of our design decisions, and Carrie is gonna talk about an example right now. Yeah. Thanks, Sam. So over the years, we've heard about some key challenges that have made it difficult to translate data into action. For example, it can be difficult and time intensive to export your data for analysis and then import all of the results back into your system of record. If you add new constituents, you have to wait for your next analysis before you can see their predictive models. For some users, myself included, it can be really easy to get lost in the details, maybe fall down rabbit holes, and that ultimately delays your outreach to these constituents. So prospect insights was built to solve for these problems. It automatically scores all individuals in your razor's edge NXT environment to identify and prioritize your best major gift prospects. Existing scores are refreshed on a quarterly basis, and newly added constituents are scored within forty eight hours of being added. It was intentionally designed with action in mind, So it highlights only the key information needed to help you make that qualification or assignment decision. You can use the under giving queue to help align ask amounts with a prospect's target gift range. So this queue highlights individuals who are assigned to a fundraiser. They have high predictive values for giving a major gift to your organization, but their last three years of cumulative giving to to your organization all fall below that predicted target gift range, suggesting that they could increase their giving levels. You can also use the low likelihood queue to support portfolio churn, removing prospects with a low likelihood to give you a major gift and making space for your untapped candidates. All of the queues list the prospects in priority order based on those who require action first. So for example, the untapped candidates queue will show you unassigned prospects with high target gift range and major gift likelihood values, and the prospects with the highest predictive values are listed first. Prospect Insights automatically creates these lists for you. These lists of your high priority major gift prospects. Now the base version of Prospect Insights is meant to be very prescriptive. It helps organizations who are maybe getting started with their major gift program by identifying the best major gift prospects in the near term. In The United States, we also have a version available called Prospect Insights Pro, which is meant to serve larger organizations with more advanced needs. So it helps organizations build a pipeline for future major gift prospects, identifying those who maybe are great for mid level giving programs in the short term, and they show high potential to become a major donor if you can get them engaged with your organization. It also identifies opportunities for planned gifts and blended gifts with additional predictions and cues, and it does offer more filtering options for some lightweight segmentation needs. Throughout the presentation today, we'll talk about functionality available in each version as well as planned enhancements for each. And we've been monitoring the results to ensure that prospect insights does provide the outcomes that we designed it for. And at this point, some of our customers have had the solution long enough for us to see the impact in terms of major donors. So on average, we're seeing that the number of high value prospects assigned to a fundraiser increases by 20% for ProspectInsight's customers. We're also seeing that the number of donors giving a gift of $10,000 or more increased by an average of 13% in a twelve month period. We're also seeing more recaptured donors. So the number of recaptured lapsed donors increased by 19% in a twelve month period. And again, Prospect Insights is really trying to drive action. So we're seeing that on average, it takes about six minutes to review, qualify, and assign a newly identified prospect. So we're really excited to see some of these results, and I'm excited to also hear feedback from new users as you get up and running with the solution. Here's one example. We recently published a customer story from one of our Canadian customers, Vakova. So Vakova has been serving people with disabilities and the surrounding community since 1969 through various programs, services, and social research. They took part in our early adopter program of Prospect Insights for Canada and used the functionality to help them with their Giving Tuesday campaign. They shared that prospect insights has led to more personalized and effective donor engagement. And Kathy also shared a story about one donor who made an online gift of $5,000 following just an initial outreach, and she shared that that person wouldn't have been on their radar otherwise. So, Sam, can I hand it to you to share more details about where we are with the rollout of Prospect Insights? Yeah. Absolutely. We've been super intentional in our rollout process for ProspectInSights to our customers both in US and Canada. You know, one of the seven key components of trustworthy AI is this idea of human agency and oversight, and we believe the controls are really big part of the story. So in that spirit, we really wanted to give organizations the opportunity to think about sort of their internal business processes and policies before they started to use the solution. So we rolled out prospect insights in waves, and we're delighted to share that now all organizations using r e n x t, in both The US and Canada should have access to prospect insights. There is a little bit of a gating process before the predictions will actually start to show up. So we we wanted to be sure, again, you have an opportunity to think through how you wanted to leverage the solution at your institution. So it's gonna be on the, portfolio menu item in the new left hand nav. But do note that, you'd have to be a specific admin type, an organization admin, in order to turn on the solution for your organization. So, Carrie, do you wanna maybe talk about some of the considerations that were important for our Canadian experience? Yeah. Thanks, Sam. So, I did mention that we ran an early adopter program for the Canadian version of Prospect Insights. And the reason that we needed to start with this early adopter program versus just taking what we've already built in The US and rolling it out for everyone, there were two big changes, that we need to make for the Canadian version. The first relates to data privacy. We wanted to ensure that we are providing the best possible predictions and data that we can while also respecting international data regulations. So all of the predictive models and the wealth indicators in the Canadian version of Prospect Insights are gonna be based on the postal code, the average wealth values for a dissemination area of that postal code, again, to respect the data privacy regulations for Canadian customers. The other thing that we were testing is this updated layout. So this version that we'll also talk about in more detail, it shows analysis and recommendations, and it has this tabbed view approach, in order to help put the scores and the information in context for that individual prospect that you are reviewing. Now although prospect insights has been rolled out to all, you do have control over which users can access and view the data. Yeah. So let's talk a little bit about what that looks like. There are a couple of notes just as it relates to the access controls once it's enabled. Once it's enabled, all admins are gonna have access to the solution by default. But note that just like many other areas in ResourceMFG, you can set up user roles to control what folks have access to. So, for example, you could choose to only allow access to manage a personal portfolio or, alternatively, all portfolios. What that basically means is users with a personal portfolio will only be able to make updates to their own portfolio and manage prospects who are specifically assigned to them. Users, on the other hand, who have access to all portfolios will have the ability to make updates to any portfolio. But we also know that some organizations have more nuanced access needs, and that's what Carrie is gonna talk about next. Yeah. So we've been holding discovery calls to learn more about how people are using prospect insights after enabling the functionality. I will do a quick, shout out here or plug in the doc section. You'll see a link that we have where you can sign up for discovery with our team if you haven't already. There will also be a field in that it's a survey where you can indicate if there's a specific, topic or product from this presentation that you'd like to speak to someone about in more detail. So, please fill that out with us, to schedule some more feedback calls if you have feedback to share. But during these feedback calls, several people mentioned a desire for more granular control over permissions prospect insights. And more specifically, they asked for the ability to decide whether a user should be able to view and manage unassigned prospects. So with the current functionality, if someone has that manage personal portfolio option, then they can view unassigned prospects in the untapped candidates list, but they can only assign them to themselves. That's what the personal portfolio functionality is doing today. With this coming update, you'll be able to decide whether someone should have access to unassigned prospects in that untapped candidate's queue or if they should truly only be able to view prospects within their own portfolio. So another theme that's come up during our feedback calls relates to understanding the predictive models and the wealth estimates for each prospect. So to help answer those questions, we're building out an analysis and recommendations for The US version of prospect insights. Now this view is already available to our Canadian clients, but the analysis section will explain the prospect insights models in the context of the prospect you're viewing. And the recommendation section will outline the action that we're recommending based on the predictive analytics. So this view is also gonna bring in some additional details from the constituent records, such as constituent codes and prospect status to really help you determine whether to qualify and assign a prospect or dismiss them to review later. So we've talked a little bit about insights when looking at an individual, but what about when you wanna get a sense of what's going on from a big picture perspective? Yeah. So our team is currently working on expanding the metrics available in Prospect Insights and Prospect Insights Pro. The base version of Prospect Insights, it does include a portfolio quality metric already, which shows the percentage of high potential and modest potential prospects assigned to a fundraiser. We're going to add in metrics that show actions you've taken over a rolling twelve month period. We're gonna surface the number of prospects qualified and assigned along with their total target gift range. So these metrics will give you the ability to tell a story around the impact that you're having with the actions that you're taking within prospect insights. And for the pro version, we'll also be able to view the total number of prospects in portfolio, aggregate target giving by portfolio over time. You'll also see a breakdown of assigned prospects by prospect insights pro categories. For example, the number of assigned prospects that are considered your top prospects or emerging prospects. Now for the pro version, we actually did just release this update earlier this week. So if you go to the prospect insights pro page, on the right, you'll see related links, and you'll find a new page for portfolio summary. And next step will be to bring, some of these updates to the base version of ProspectInsight as well. So another enhancement that we made to the ProspectInsites Pro, relates to the queues and the individuals that we're surfacing. This is another update that came about based on feedback calls. When we first started, we took a relatively conservative approach in who we were surfacing as a top prospect, But we heard feedback that organizations, especially those who do have a prospect researcher, would rather go through additional prospects, maybe disqualifying them, versus potentially missing out on somebody who just missed the cutoff. So we've adjusted the back end logic to surface more prospects, and we've added more queues to enable more purposeful segmentation for those researchers. Now in the build a qualified prospect pool section, we have a queue for secondary prospects to qualify. So these are individuals who all have a high target gift range, but a low likelihood to give. You should review these prospects after going through your top prospects. But, previously, we wouldn't have highlighted them at all because of that low likelihood to give. Another update we made relates to the smaller predicted gifts queue. So, previously, there was one queue called smaller predicted gifts, and there were multiple recommendations that we had for different prospects within that queue. For some, we may have recommended you set up an action to reengage with that individual, see if you can increase their giving likelihood. For others, we suggested they're probably good for mid level programs, but maybe not for major gift programs. So you wanna make sure that they are assigned to a person who is working on mid level programs. And third, there were some who we'd recommend you just unassign altogether based on what we're seeing in the data and with the predictive analytics. So now we've broken those up into three individual queues based on those recommendations. And after making the change, we've already seen an increase in usage, so I think it's helping to clarify the intent behind the queues. As I mentioned before, Prospect Insights Pro is intended for larger organizations who have more segmentation needs. So these queues in Prospect Insights Pro now include a filter for constituent code and a filter for all four of the prospect insights models. You can use these filters to refine the prospects that are displayed in HQ. For example, you might use these filters to say, show me my top prospects who are tagged as parents or volunteers, have an excellent or very good planned giving likelihood, and a target gift range above $100,000. We do also have more segmentation updates planned for Prospect Insights Pro, but we'll talk about those a little bit later in the presentation. First, we'd like to share some additional wealth details that our data engineers have made available. Yeah. One of the balances that we try to strike with prospect insights is to provide the right amount of information that actually encourages a user to take action and avoid getting stuck in that sort of analysis paralysis. So in this spirit, in p I pro, we've expanded some data under the business ownership and security section on the right hand side of the page to give you richer information, but also more confidence to take action. So business ownership will provide the estimated number of businesses owned by members of the prospect's household. Ownership value is gonna indicate the individual's estimated ownership value for the businesses that are indicated in business. The value is gonna be calculated on the value of the businesses and the estimated percent ownership by members of the prospects household. If just a caveat, if the percent ownership isn't disclosed, the ownership value may display as zero. Below those values are securities. So these are gonna provide the estimated stock holdings based on information of public company officers, directors, and major shareholders. A major shareholder in this context is gonna be someone that owns at least 10% of a company's stock. Now this value is gonna represent, again, all members of the prospect's household. Direct value, field underneath provides the estimated value of the stock holdings indicated under securities that are within the individual's control. This value is, again, gonna represent all of the members of the prospect's household. So lots of really good information that we're surfacing now in PI Pro. We've talked a bunch about prospect insights. Let's spend a little bit of time talking about fundraiser performance management because I think there's a lot to be excited about here. So fundraiser performance management, in case you all aren't familiar with it, is one of our premier data intelligence solutions for customers who are laser focused on optimizing their fundraising team's performance. So there's a a software component, and there's a consulting component combined with models. Now for the last few product update briefings, we've been talking about our work preparing to roll out Sky UX. That's our kind of Blackbaud design language across the solution, which is gonna bring enhancements to usability, accessibility, super important, and give the solution a fresh look and feel. But we're also thinking about how we can better configure some of the workflows to drive action with your team, which should be a theme you're hearing today. This is really just the first step in our journey to build out a greater integration between fundraiser performance management and other Blackbaud databases of record. So we we have a few pages that have already been updated. They're actually shown here on the slides, the reporting library, and then the control panel, and we're planning to roll out the rest of the changes throughout the year. So in q two, just to give you a a little bit of, foresight here, we plan to roll out an an updated version of the relationship profile that's shown over on the left hand side of this slide. And then in q three, we're gonna roll out changes to Targeter in our drill downs with the remaining, portions of the product suite following that. So we're super excited to bring these updates to our customers. It's been a long time coming, but it's gonna be, I think, really impactful. Carrie, do you wanna take us from outcomes to data? Yeah. I can help transition. So data is fueling everything that we do. Right? Data is what powers our predictions and ultimately the outcomes that we are trying to drive. And, we did mention that there are a few ways to enhance our data and some updates that we're really excited to share. And so we wanted to open up the hood a little bit and talk about some of the work that we have ongoing and that we're doing within the data domain. Yeah. So any data scientist worth their salt news that quality, consistency, and accuracy in the data is really at the heart of any good prediction. And so we've been really laser focused on things that we can be doing to enhance the experience, not just in our predictions, but really across the data suite. So I I mentioned this last quarter, but one of the things that's really core to the data experiences is this idea of identity resolution. So when when Blackbaud looks at constituents in a customer's file as part of an analytics project or when prospect insights is looking at our NXT constituents, for example, accurately matching data from third party sources to the correct constituent in the customer's file is really critical in our ability to, to return accurate screening data and provide actionable insights. So that that's what we mean when we talk about identity resolution. It's really about connecting the data together. And we mentioned in our last product update briefing that we've contracted with live ramp to use their industry leading, service to power our identity resolution across our solutions. So over on the side here, I did wanna call out some of the insights just that we're seeing in terms of the impacts, the quality of our data. So this is looking at the percentage of individuals that we can match, to that persistent key to that, identity resolved identity rather with a high degree of confidence. So before live ramp, we were matching at the individual level right around 70%. But after the live ramp introduction, we've seen a lift of about 20 points. So a massive increase in terms of the coverage that we're getting with our data, and that extends even further when you look at the household, ratings as well. So this is gonna be a huge improvement to our match rates, which means that our customers are gonna get better screening results and more accurate predictions to use. So what does this mean for our customers? I wanted to talk a little bit about, the University of Georgia. They use our predictive scores and some of our segmentation strategies to really drive increases in donors, dollars, and ROI for their leadership annual giving program. So this is really at the heart of what we're all about. Right? These are awesome outcomes, and this is even before some of the changes that are coming with LiveRamp. So speaking of which, we did wanna give you all, just some expectations in terms of when you'll start to see this rolling out across our product suite, by product. So in q two, we're gonna roll out this this quarter. We're gonna roll out the enhancements to grateful patient solution, prospect insights, prospect index pro, persistent key, and Blackbaud copilots. In quarter three, you'll see that start to show up in enterprise data intelligence and prospect points. And then in quarter four, you'll see it show up in ResearchPoint, Affluence Insights, and Fundraiser Performance Management. So one thing just to kinda call out here, we've been doing some parallel testing behind the scenes. So that means we we run the results from the old service and compare it to the new service, as we prepare for the rollout. Grateful patient solution, just to name one example, it's seeing improvements in the referential data enrichment anywhere from 26 to a 60% depending on the field. So it's a huge lift. We think it's gonna significantly improve the quality and breadth of our data to customer the customers have access to, and there's a speed component to this as well. We're actually greatly reducing the amount of time that it takes to get some of those matching results. So just a monumental shift for us, and it's gonna illustrate just a key part of the story that's been a part of our journey over the past few years. And this may resonate a little bit with you and your organization's situation. So, historically, you know, many of us have thought about data as an asset. You something that sits there and it holds value. You probably heard the phrase, you know, data is the new oil. Right? The challenge is, I think, that's a little bit of a problematic framing, because oil, when you pull it out of the ground, isn't inherently valuable in and of itself. Right? It has to be turned into something that solves for a job to be done. Right? Oil isn't useful until it's turned into petroleum jelly or gasoline. And so that's led to this really transformational idea for us, which is that data, it needs to be treated with a high degree of respect. We really need to cultivate it. We need to treat it like a product in and of itself. And it's one of the reasons that we looked so long and hard at our identity resolution because it's a key part of our data product story, but it it doesn't just end there. You've probably seen a version of the slide previously, but one of the things that we've, been looking at is when we consider sort of that data as an asset model. Historically, what we've done is we'll build a prediction, and then we'll build it into kind of a single application experience. So there's a prediction for major giving and prospect insights. There's one in prospect point. There's one in, fundraising performance management. Those may be a little bit different from each other. Right? The challenge that presents is that if you wanna iterate or improve on those models, it's really just isolated to that one experience. The shift over to that data product framework, though, helps us think about how we can kind of encapsulate that core outcome that we're trying to drive. So from those examples, increases in major giving, right, through major giving likelihood, And we wanna disseminate that data product throughout our application experiences and through our data enrichment. So it's a big, big shift for us, but I think it's gonna yield some really transformational improvements as we head forward. But, Carrie, maybe it'd be helpful. Do you wanna ground that in an additional example? Yeah. So I think the major gift likelihood is a good one. Another is thinking about that target gift range value. And what I really appreciate is that our data science team takes a really intentional approach when updating our models. Our goal is that these models drive action. So we're reviewing which models perform better from, you know, a statistical fit standpoint, but we're also considering how the changes translate to what we highlight within each product. We're reviewing things like which constituents are we highlighting and how do suggested actions change when we change the models. And so where we previously had different versions of a model for different offerings, the goal is to have a single source of truth that we can highlight in different ways for different products if needed. So, for example, with prospect insights, they both benefit from the underlying target gift range value, both Prospect Insights and Prospect Insights Pro. However, we are able to highlight higher gift ranges up to a million dollars plus in the Prospect Insights Pro version for those larger clients. And a single source of truth also makes the data easier to govern. So if we need to update the model for any reason, say based on a feedback loop or to respect a data deletion request, we can make that change once and have those updates reflected in any product utilizing that model. So this is just one example of updates that our data engineering and data science teams make behind the scenes, which benefit multiple products across our analytics portfolio. And as I've been talking about Prospect Insights, you may have been wondering how does this compare to other Blackbaud analytics solutions such as ProspectPoint. Both versions of ProspectInsight started with functionality to solve some of the problems that I called out at the start of the presentation, automatically scoring constituents, reducing time to action. And our prospect point models offer additional benefits, such as the flexibility and segmentation that organizations like the University of Georgia use to drive increase in donors and donations. So our long term vision is to be intentional in consolidating the data intelligence portfolio so that we can speed up innovation. It should be less about the specific names of products, how we package our offerings, and more about how we drive outcomes for you. That's one of the reasons that this data as a product idea is so foundational to our approach in a world of connected systems. It allows for some incredibly incredible extensibility, not just in the data intelligence product space, but also in experiences directly consumed in Raiser's Edge NXT and Blackbaud Copilot, just as a couple of examples. So the next step in our journey is to evaluate where we feel that a ProspectInCites Pro experience will be beneficial to our customers. Raiser's Edge NXT and this will be targeted to our razor's edge NXT customers at least to start with. Now to be clear, our intent isn't to create any contract changes or disruption for customers. We're just working to find a way to add even more value to all of our solutions. And then for those who are not on Raiser's Edge NXT, you'll still have all of the benefits brought by the enhancements to the data through our partnership with LiveRamps identity resolution. We are planning new functionality for Prospect Insights Pro to allow for some of that flexibility and more advanced segmentation needs. So the plan is to make the Prospect Insights Pro categories, such as the top prospect, emerging prospect, those different queues I mentioned, and also the model scores available for use alongside the information found in constituent lists and query. This will allow for additional segmentation use cases, such as finding your emerging prospects who live in a specific area to help plan a trip or filtering for top prospects who have had no contact in recent months. So here's an example of how we're combining the best functionality from our different analytics offerings to help consolidate and simplify the data intelligence portfolio. So let's turn our attention to predictions. You know, we're continuing to build on this track record of deep expertise and starting to leverage some of the technology enhancements that only just now are making some of these approaches available. And, again, it's really all about outcomes. So the idea is that when it matters, right, we're gonna do something about it. We've we're in the process right now of moving all of our models to be adaptive. So, historically, you might have heard us differentiate between prescriptive or custom models, but I think that sort of misses the point. Right? What we're really trying to get to is a state where the most effective prediction is gonna be the prediction that is leveraged in the experience that you're in. So there may be cases where for a specific customer, there are additional data points that we wanna integrate into that model, and the model automatically takes those into account. And for other customers, the models that we have built that are looking at the national dataset are gonna be more effective than those individual data points. And so we really wanna bring to bear the best prediction for the problem that we're trying to solve and really think about how that helps move organizations along. So we call this adaptive models. We're working on bringing these to Prospect Insights Pro, and this is just to get a little bit more precise, gonna automatically identify opportunities to further improve the predictive models to improve their accuracy by incorporating organization specific variables. So we're gonna time the release of this, with some of the updates that are coming from live ramp, so that we'll be incorporating the highest quality data into the models. And this is, of course, gonna be an iterative approach that adheres to our trustworthy AI principles. So the end result is gonna be models in PI Pro that adapt to your data, providing a more precise prediction of which prospects are most likely to be your major donors or plan donors. So these are the same principles that, are gonna be carried forward, not just in Prospect Insights Pro, but also in other areas. Yeah. So another example is predictions feeding into generative AI as with Blackbaud Copilot. So Blackbaud Copilot is an AI powered coach and assistant that allows you to interact with your data in natural language to ask questions and get insights. Blackbaud Copilot is meant to help fundraisers understand, plan for, and engage high priority donors and prospects. For example, it can make recommendations on cultivation strategies for key donors or prospects, suggest next actions, and highlight important deadlines for pledges, actions, events, and opportunities to help keep you on track. Now this isn't asking it's not like asking a a general AI tool, like ChatGPT, which was trained on the entirety of the Internet up to a certain date. We've grounded Blackbaud Copilot with data and insights from the Blackbaud Institute, which is our research lab focused on the business operations and latest trends of social impact. And so that means you're getting insightful responses grounded in our sector research and your specific business data. And because of our approach to data that Sam covered earlier, which treating data as a product that can be surfaced in different experiences, Blackbaud Copilot also incorporates the predictions used in prospect insights so that you can ask questions about your best major gift prospects. And with Blackbaud Copilot, your data belongs to you. We're not training our models on it. We're building it on a bedrock commitment to security and privacy. So Blackbaud Copilot is currently in the customer technical preview stage, and we're gathering feedback from early usage and making improvements before making it more widely available. So we've touched on this a little bit, but I I just wanna emphasize, you know, our future focus is really thinking about that data as a product strategy and really marching towards this big idea. How do we help our customers achieve greater outcomes through better data that lead to smarter choices? So, again, we talked a little bit about these blue boxes as just being examples of how we can continue to deepen and expand our impact across the entirety of the Blackbaud suite. And a big part of that comes down to our intelligence for good strategy. I mentioned this a little bit earlier. Right? AI is super exciting, and the technological breakthroughs, like generative AI, have the potential to transform the way we work. In fact, we're already seeing that happen in some cases. But navigating the frontiers of tech is a really serious responsibility, and so we're committed to harnessing the new potential of AI innovations in a way that's responsible and that ensures the social impact community really benefits from accessible, powerful, and responsible AI driven capabilities. So really important for us. This is the guidepost as we think through opportunities as we head into the future, and that's really a key part of our strategy. So as we head forward, you know, we've talked about some of these things already. The purple boxes are gonna indicate some of the things that we're continuing to invest in. So, again, how do we lean more into the data products space? How do we think about dissemination of those data products across our capabilities and across our application experiences? How do we think about, AI as sort of a service that's available, again, in that same way? And then how do we incorporate some of the outcomes data and the feedback loops to better refine, better improve our models, even even near real time. So, again, it's a it's a really excited exciting moment rather to be in the data space. Carrie and I, and others on the team are really having a great time, working here. We're just so excited to have you all with us as part of that journey. Just a couple of things maybe before we close out for today. First off, a reminder, BBCon in the city of brotherly love, Philadelphia registration is open. So if you sign up now, you do get the early bird pricing. It's always nice to get a little bit of, discounts, and, looking forward to seeing you all there and interacting. And then just wanted to double down in the docs section. There is a link to the discovery. We would love to have conversations with you. Love to hear about how products are working, where you guys are are struggling as an organization. That engagement with customers is super important. So please please please connect with us. It's one of the best parts of the job. So, with that, I think we're gonna wrap up today. Carrie and I will probably stick around a little bit behind the scenes to answer any remaining questions. But again, deeply appreciative to all of you that have spent, the last fifty two minutes or so with us, and hope that you have a fantastic rest of your week. Thanks, and cheers. Thanks,