Name: Product Update Briefing - Data Intelligence
Uploaded: 2025-11-20T20:16:05.668Z
Duration: 1 h 12 s
Description: Product Update Briefing - Data Intelligence

Transcript for "Product Update Briefing - Data Intelligence": Hey, everyone. Thanks for joining us today. This is the product update briefing for data intelligence for 2025. We always like to start with a bit of housekeeping. So audio for this webinar is broadcast through your computer speakers. If you run into any technical issues, generally refreshing your browser is the best way to get things up and running again. But you will receive a link to the webinar, to the recording by email generally within twenty four hours. So if you are having any technical issues, the recording should hopefully fix things for you. We do have a area for q and a, so you can submit your questions there. As you're leaving questions, we always like to say, please do include context, alongside the question that you're asking. That'll just help ourselves and our team members who are helping to monitor the q and a, to know which slide or which section of the presentation you're referring to when you ask those questions. So our safe harbor statement, this presentation does contain forward looking statements that involve inherent risks, uncertainties, and assumptions. It outlines 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 if you're making any purchase decisions, please make those decisions based on features and functionality that are currently available. Blackbaud knows that security is a top priority for you and your organization. That's why we're excited to introduce the Blackbaud Trust Center. This is your new centralized hub for all things related to Blackbaud security. At trust.blackbaud.com, you'll find things such as audit reports, including SOC and PCI documentation, security white papers, dedicated knowledge base for frequently asked security questions, Blackbaud security credentials, and self serve access to information for risk assessments and due diligence. You can access the trust center using your Blackbaud ID, so no extra credentials are needed. This resource has been designed to make your security reviews faster and easier, reduce the time spent on due diligence, and provide you with direct access to the information you need whenever you need it. It's part of our commitment to transparency and to supporting your organization's security needs throughout your journey with Blackbaud. And just by way of introduction, my name is Carrie, and I am a principal product manager on our data intelligence team. I am based out of Austin, Texas, and I'm joined by my colleague, Sam. Hi, everyone. Glad to be with you today. My name is Sam Veddable. I'm the senior manager over the data intelligence product team. I'm based out of Nashville. And in the spirit of the season, we're getting close to Christmas. Fun fact about, where I live is that several Hallmark Christmas movies have actually been filmed in our downtown. So so glad to be with you all today and really excited to talk about what's happening in data intelligence space. So I did wanna start off by setting the stage a little bit and just acknowledging that our presentation today is gonna be a little bit different than some of the other product update briefing sessions that you'll likely attend. While other sessions are going to be focused on, teams who support a very specific solution like Razer's Edge NXT or Financial Edge NXT, for example, our team is really responsible for enabling customers to leverage cutting edge data intelligence across all of our solutions. So this means today that we'll share some updates that are happening behind the scenes, but will have a large impact on all of our data intelligence capabilities. And it also means that some of the content that you're gonna see in our presentation today may be referenced in other sessions as well, most notably, the razor's edge NXT session. So what does data intelligence mean? Ultimately, our data intelligence capabilities help you translate data into value so you can move your mission forward. Now our data, AI, and actionable insights help you answer many of the questions, ones we've all struggled with in the fundraising sector. On the left hand side of this slide, our work really helps you drive meaningful progress across a variety of different giving time horizons and gift sizes, maximizing your opportunity in annual giving or direct marketing, sustainer giving, peer to peer giving, major or principal giving, and planned giving as well. Before we get to the rest of the slides, I did wanna ground our conversation in just a little bit of context. Now there are three observations that I wanted to share with you all today. First, not all constituents want to engage with you in the same way. I know this seems obvious, but it's true when we look at the data. A few years ago, our team did a longitudinal study that evaluated if we could estimate the long term value of an individual early in their relationship with an organization. And there were three key findings that came out of this study. First, that individuals tend to self select into a value lane early in their relationship with the organization. Second, that these value lanes tend to be sticky and consistent over the duration of the relationship. And third, there are these opportunistic moments with within each of these value lanes to be able to influence an individual's behavior, but largely, the the behavioral patterns here tend to be consistent. So this points to an important but a challenging perspective in that the sort of egalitarian, same approach for everyone that many organizations are using may not be the right tactical choice. I mean, candidly, the challenge is that most organizations don't really have an appropriate amount of staffing to be able to manage all of those individual, tracks engage, intentionally. The second observation is that when you don't have the ability to to manage these engagement tracks intentionally, you you miss out on opportunities with individuals that may not necessarily be prospects now or valuable now, but will be in the future. Now this is important context in light of the fact that we know that there's gonna be an enormous amount of wealth transferred over the next twenty five years. Cerule associates released a paper last year that, estimated this transfer amount to be north of a $112,000,000,000,000. And, notably, $46,000,000,000,000 of that transfer is going to go to the millennial generation. Now just a spot check here, and I'm not calling anyone out, but who's doing a mind blowing job of engaging with their younger constituencies? The challenge for many organizations is that they're really focused on elephant hunting to drive short term returns and are missing out on filling in the top of their philanthropic buckets. This leads to our third observation. Artificial intelligence has seen a massive transformation and evolution over the course of the past four years. We believe there's going to be some incredible opportunity here for organizations, but it's gonna require us to think and rethink a little bit of the structure and approaches that we've traditionally used in fundraising in light of, in light of how they manage their constituencies. And so harnessing your organization's data is mission critical. However, it's increasingly difficult. 19 individual states have now signed legislation, and some have even enacted new requirements and obligations for organizations in respect to individuals' data and privacy rights. Now this is great, but there's not a federal approach to this, and this means that there's gonna be nuance between the states that organizations, particularly those that are operating in multiple jurisdictions, are going to have to navigate. And this is complicated by the fact the amount of data that is created each year is massively exploding. Now there are estimates that there's almost a 149 zettabytes of data that was created or were created in 2024. And just to ground this in something that's a little bit more understandable or comprehensible, that's the equivalent of about 5,000,000,000,000 of high definition television content. And if we wanna maybe play cosmic calendar, it's a different way to look at this. If you imagine the age of the known universe compared to this value and you mapped out, this on a calendar, we wouldn't even be on the first day of that calendar year. That's how big 5,000,000,000,000 worth of content is relative to where we are at this point in the universe's history. So this data explosion creates an increasingly amount or an increasing amount of quality issues. We are dealing with this massive influx of new data, managing those inputs, making sure that they're consistent, accurate, and usable for your organization is really tough. Now, thankfully, this is a space that we have been very deeply involved in for more than twenty years now. And when I think about our evolution over that time horizon, every step, every individual increment of functionality and insight that we have developed have really built on the lessons and experiences of the past. And this has really helped us to solve some tremendous challenges for the nonprofit sector and have even led into the development and release of some new capabilities that leverage the power of large language models and even open up, as was announced at BBCON this year, the opportunity for us to iterate and develop agents for good. Now when we take a macro view at where the technology sector is heading, the data intelligence team believes there's really two Archimedes levers that we can lean on to drive meaningful benefit for our customers. The first is gonna be context. Context is just so important. And just to ground this in an analogy, imagine if you walked into the Empire Strikes Back right at the moment that Darth Vader tells Luke that he's his father. Now if you don't have the context of everything leading up to that point, you wouldn't understand why that moment is so impactful. Context gives that moment weight and allows you to engage meaningfully with the broader story. Now this isn't just limited to movies or stories or jokes. The same is true when you come into a new job, for example, and context is gonna be critical to your success. It gives you the ability to make a prediction. Right? So this gets to the second domain that we're focused on in models. Now models are gonna be grounded in context. Without context, models are gonna be relatively generic. Think about the last time that you tried something completely brand new that you'd never done before. Now you you didn't know necessarily what outcome to expect because you didn't have the experience. You didn't understand how your actions might result in a very specific outcome. And when we look at what's going on in the large language model space, we believe that these experiences that are driven by these models are gonna be, objectively affected by the quality, breadth, and depth of context that the model has to work with. And the challenge here is that, historically, these have been largely seen as two distinct elements. Right? Models were available that maybe they were only partially leveraging your context or you had lots of context, but you didn't have any models to help you all drive decisioning. And so we believe that when you bring these together, this overlapping focus on context and models allows us to deliver transformational experiences in our software that really unlock the power of your data. It allows you to engage with the right people at the right time, to find ways to partner with them that really drive your organization's mission forward. So when you hear members of our team talk about a system of intelligence, that's what this is getting to. It's the ability for us and for you to unlock outcomes. So as we run through our content today, we hope you'll see the connection between these three themes, your context, models, and outcomes that are really deeply connected to the data. You know, AI is tremendously excited exciting rather, and we feel like our approach here is gonna be really important in how we help leverage the technology for good. So our approach we're calling intelligence for good, it leans on three pillars here, that it's convenient, powerful, and responsible. Right? We wanna make sure that AI is approachable, that it's easy for our customers and our partners to be able to understand and leverage it, that it's powerful, that it harnesses all of the depth and breadth of experience and data that we have at our fingertips. I think that's one of the things that we really bring to bear in this space is the amount of scale that we have in terms of data as we think about what's going on in the nonprofit, sector. And finally, that it's responsible, that we're respecting and reflecting, what we expect for AI to be able to do and reflecting or respecting rather the regulatory and governance landscape to make sure that we are effectively and responsibly rolling out these solutions to our customers. Because, again, at the end of the day, our AI strategy is really about helping our customers really move their mission forward through that combination of data, leading edge AI tools, and expertise that deeply understands your business challenges and the sensitivity of your relationships with your donors. So we're, again, here to help you really achieve more with your mission. The intent here is to really think about how we can leverage this technology to drive deeper and more connection, to make collaboration easier. We announced agents for good that enables you to unlock more possibility as AI works alongside of you, expanding your team's capacity and helping you to reach new goals. And, additionally, something that was announced at BBCon that I did really just wanna double down on and and share with you all today in our product update briefing is the announcement of a free AI certification so that you can feel more confident and make the most of these new tools. So this is a sector specific AI certification with the AI Coalition for Social Impact designed to really help you use AI effectively and efficiently. And so you're gonna gain these practical skills, earn continuing education credits, and join a community of change makers who are really leading the way in responsible AI. So the first course is gonna arrive in 2026. So please do make sure I think we've got a link over in the resources section. Sign up for the wait list and be among the first, to get certified. I think this is gonna be a tremendous asset for all of our customers to be able to leverage, and even our team is looking, forward to really being involved and just starting to, to work in that space. Yeah. Thanks, Sam. I was about to say the same thing. I'm really excited about the certification and seems like a good opportunity too just for everyone to learn from each other in addition to some of these, industry experts. But for today, we're gonna tell the road map story through Horizons. So I have one section called now. That's everything that is currently available, things that have been recently released. Then we'll move into next, so enhancements that are coming soon. And then towards the end of the presentation today, we have a section called under consideration. So these are gonna be larger key themes that we are considering as we're doing discovery calls, doing research to help inform what we build going forward. So let's start with now. And in particular, I'm going to start with enhancements that are now available for Prospect Insights and some for Prospect Insights Pro as well. So Prospect Insights is included with Razer's Edge NXT, and it helps use, that context combined with models to drive action, to help you identify and prioritize your best major gift prospects who are already within your environment, within your database. So one update that we recently released is to give you more granular control over permissions within prospect and sites. We've heard feedback from, a variety of individuals during some of these feedback calls that it's great you can give someone that personal portfolio permission, but it's really important that you can control whether or not individuals are able to see unassigned prospects. So before this change, if someone had that personal portfolio option, then when they're in, like, a low likelihood queue or under giving, In some, they would see only individuals who are assigned to them, but they could also go to that untapped candidates list, which is a list of prospects who are not currently assigned to any fundraiser, and they could add them to their own portfolio. That's what that personal portfolio option represented. We have updated the permissions. So you do now have the option to choose which users are able to manage unassigned prospects. So if you don't want fundraisers or someone with a specific role to be able to manage those unassigned prospects, then you can edit the role and choose whether or not to select this box that you see here on the screen. We've also updated the look and feel of prospect insights for The US version in particular. This visual that I have here on the screen, is actually already available for the Canadian version of Prospect Insights and has been from the start. But we've updated this, what you see here on the screen to include analysis and recommendations because we kept hearing questions about well, wait. What do these scores mean in the context of a prospect that I'm reviewing? I'm trying to understand target gift range and the values that I'm seeing for this individual. So we now have this updated view, which does include that analysis section to explain the models in the context of the constituent that you're reviewing. It also calls out the recommended action, and that recommendation might be different depending on which queue you're reviewing. So if you're in untapped candidates or low likelihood, for example, But that recommendation is always going to relate back to that primary action button that you see underneath the individual's name. So if based on what we're seeing in the data and with the predictive analytics, we're recommending that you qualify and assign an individual, then that's going to relate back to that button where you can qualify and assign that constituent. Another update that we've made, is that our scores are now refreshing on a weekly basis. So every week, the system goes through and looks for new new gifts, new giving information, and it will update all constituent scores accordingly. We are also still refreshing scores on a quarterly basis to include our licensed and proprietary data. So it's that combination of giving to your organization as well as the licensed data used to create these models. We've also made an update to the finished review work flow within ProspectInSights and ProspectInSights Pro. So within these solutions, the intent is you start with these prioritized lists, and you determine for each individual, do I want to add an opportunity? Do I want to mark them as qualified? Or maybe I want to dismiss them to review again later. Previously, in some queues, you would see the option to review again in six months or twelve months. Those were the only options. Or sometimes you could click finish review, which would permanently remove that individual from that queue. We heard questions about that behavior. Either, we weren't clear on what the finish review button would do, or you're asking for the ability to review again in six months where you might not have that option. So with this change, we've made it consistent. Within each of the queues, you'll see the option to review again in six months, review again in twelve months, or permanently remove from that queue. Along with this change, we have also added in the ability to add context when you're disqualifying or dismissing a prospect. So as you're reviewing untapped candidates, for example, if you mark someone as disqualified, you'll have the option to select from one of these, options listed here showing your reason for disqualifying. Oh, maybe you can hear my dog. He's excited about this change too. So you can select the box for one of those, but then there's also an open text field if you wanted to leave a comment. Again, you can leave this as context for why you are making the decision to disqualify somebody. The screen on the right shows how this will appear to anyone who has permission to view that individual within Prospect Insights. So you can see the date that they were disqualified, the user who took that action, the queue that that individual was in. And if you chose an option, that would appear here and then that context would also appear in this view. Carrie, I think part of the intent here is to really, improve our models too. One of the things we're super interested in, again, thinking about context and models and these action oriented experiences is how we get better at serving up the right people at the right time. Yeah. Absolutely. Thanks, Sam. So, like, as an example, if we're seeing, you know what, we're we're missing wealth information. Maybe there's a new data source that we can add in or, just in general, if there's updates that we can make to our models so that they better fit within your process. Absolutely. Thank you. So with this redesign within prospect insights where we have the new layout, we've also moved that portfolio quality, tile into a related link. So underneath related links, you'll now see one for analysis, and that's where you'll go to find the portfolio quality metric. We've also added some new metrics to this view. So you can get an overview of all prospects who are currently assigned and the target gift range value for those individuals. So what is the total target gift range of everyone in portfolio? What's the average target gift range of those individuals? You can also see some statistics here related to actions that you've taken. So how many prospects have you qualified since the beginning of this year, and what's the target gift range of those individuals? How many have you assigned? And that could be an assignment from anywhere within Raiser's Edge NXT over the past twelve months. And, again, what is the target gift range of that population of those individuals? You also get a high level overview of cumulative giving by assigned prospects. So what is the total cumulative giving for the past several years for all assigned prospects, and what is the mean, and what percentage of assigned prospects have given above $0, what percentage have given above $10,000. And then, again, this is where you'll go to find that portfolio quality overview. And portfolio quality gives you that high level view of, for everyone who is assigned, what percentage are considered high likelihood to give a major gift to your organization and what percentage are considered modest potential for giving a major gift to your organization. So this is the view that we have in the base version of Prospect Insights within The US and Canada. And then we have more information available in the view for Prospect Insights pro. So within the pro version, you still have that overview of everyone who is currently assigned to a portfolio. You also have the option to filter this view by fundraiser. So if you wanted to see the the portfolio potential of one specific individual or maybe for a group of fundraisers, you'd be able to do that with this filter. You also get a breakdown of assigned prospects by category, and you can see assigned prospects over time alongside that total target gift range over time. So the intent here is to help you see, okay, are we keeping our portfolios at a manageable size? That might vary depending on the fundraiser or depending on your organization that you can keep track of. Do we feel these are manageable? And the total target gift range, is that on track to to meet our goals? Are we setting ourselves up for success by assigning individuals with the highest likelihood to give a major gift to our organization? Again, here you can also see a breakdown of that giving behavior by assigned prospects. And you can also view that information by calendar year and see a breakdown for each year, what percentage are giving at those different giving levels as you can see here on the screen. We've also made some prospect insights, call them quality of life improvements. So all of these are things that have come up again out of feedback calls with customers, and they're meant to help as you're reviewing information, make it a little bit easier to, make a decision about what action should we take for an individual. So the first one is on the prospect management tab. When you're reviewing someone in prospect insights, you can now see both the action category and the action type, that you have set up for that individual. We're also adding in more address context, on the biographical tab. So we'll show the primary address for an individual and also include whether that's a home address or a work address. And for the Canadian version of Prospect Insights, under giving indicators, we will also include the address being used, as we're providing those estimates because, again, these giving indicators are going to be based on dissemination area or postal code for the Canadian version of ProspectInsight. And that's important to note because it's what, allows us to respect international, data governance policies. But, again, you need to know that context of which address is being used to help provide these giving indicators. And then for Prospect Insights Pro, we do have a constituent code filter that's been available for a little while within those queues. But the change we've made is you can now determine whether you want to include any of these constituent codes or you can choose to exclude any of the constituent codes. So, again, that'll just help as you're refining lists, make it a little bit easier to identify the prospects that you're looking for. So we've got more to cover, but I did just wanna ground some of what Carrie is talking about in terms of Prospect Insights and Prospect Insights Pro in a customer story. And so I wanted to talk about War Child Canada. War Child Canada is a nonprofit organization dedicated to supporting children affected by war globally, and they invest in local communities to help drive generational change. They're actually one of the largest direct mail fundraising organizations in Canada. Back in 2024, they faced a series of challenges, including a postal strike that they had to manage around and make sure that they were still able to deliver on their mission. So not only did they continue to deliver, but they beat their aggressive targets for the year. So in fourth quarter that year, they were able to recapture 90% of their target audience and ended their 2024 campaign at a 125% of their goal. Now to do so, Orchard Canada leveraged prospect point predictive scores as part of a consulting engagement with our team to drive thoughtful, strategic engagement with our prospect base. They use the prospect point scores to help segment the audience and focus on those more likely to give a major gift, monthly gifts, or respond to direct mail appeals. At the same time, they also leverage the models and data provided by Prospect Insights to make engagement with prospective donors by their callers much easier. Senior manager of development, Dean Sager, said that Prospect Insights has helped us gauge whether our asks are in the right ballpark or not, and we also found that many of our major donors were undergiving, and many of them increased their gifts in 2024. So this story just illustrates a little bit of the power of context, models, and outcome focused experiences that really bring to, to to we bring to bear in terms of driving success, in partnership with our customers. Now many of our experiences in the data intelligence space lean heavily on context, and one of the things that's super important about context is that it has really broad coverage. Right? You wanna make sure that's highly accurate, particularly when you're dealing with additional data from outside of your system of record. You wanna make sure that it's comprehensive and accurate. One of the moves that we made over the course of the past year is a migration in our technology that we use to resolve identities, by moving over to a partnership with LiveRamp. And one of the things that this allows us to do is as we think about, different datasets that we have from our third party and proprietary data assets to really be able to bring them together meaningfully, and that shows up then in the experiences that you're using. So, for example, when you're in Prospect Insights and you're looking at Sam Venable, that you're actually getting data about Sam Venable that's in Franklin, Tennessee and not Sam Venable that is in Knoxville, Tennessee. Right? So it's really important that that information is getting connected together accurately and consistently. So, we've talked about this a couple of times over the past few pubs, but this has had a really meaningful difference in our ability to match with a high degree of confidence to individuals. So it's gone up by almost 20 points to where now we can match to that high confidence level about 89% of the time for individuals and 91% for households. So, again, a tectonic shift for us, and this is something that contributes to really all of our solutions in the data intelligence portfolio. So just wanted to provide some updates here in terms of what timelines look like. So we've already completed, the migration for grateful patient solution for Prospect Insights, for Prospect Insights Pro, Persistence Key, and then it's actually contributing to some of our work with, Blackbaud AI chats. In third quarter this year, we released, we're releasing the, live ramp matching for fundraiser performance managements for enterprise data intelligence solutions and then for the direct marketing bundle. And then in the first half of next year, you can expect to see these, the identity resolution really powering prospect points, research point, and affluence insights as well. So a really important shift for us, and, definitely, you all should be seeing improved results in terms of the matching and quality that you're seeing in the data. So let's move forward to what's next. That's, identity resolution is a a key part, really, of something that we announced at, BBCon this year called Intelligence for Good. These are virtual team members that are going to be powered by AI and integrated within your Blackbaud solution. And our very first agent for good, the development agent, will help you identify and steward donors that you may not have time to reach. And the hope here is that this helps you unlock new revenue streams for your mission. So this innovation is all about giving your team extra capacity so that you can really focus on the human side of your work. And one of the things that's powering these agentic experiences is our data. So as we continue the evolution of our data intelligence solutions, we're gonna be making more of our data available through Sky APIs. This allows for super low latency enrichment of your data in batches and is really targeted for use cases where rapid matching and enrichments are important. So we've started to roll this out with our persistent key solution, which is is going to be available this quarter. I think it by the time, we're doing this pub, I think it may actually already be available. And our next expansion will be with the direct marketing analytics products as well through the same API connection. Great. So we also have some new functionality planned for Prospect Insights and Prospect Insights Pro. The first is to add some of those filters that I referenced. So the constituent code filter, we also have a filter for the ProspectInsight scores. Those are going to become available to the base version of ProspectInsight in both The US and Canada. So this functionality will help you refine those prioritized queues of individuals, those untapped candidates. You'll be able to filter again by constituent code, or by the models themselves, so by target gift range and major giving likelihood. Within Prospect Insights Pro, we are also adding full segmentation flexibility. So the Prospect Insights Pro models will be available in constituent lists, in the work center, and query as well. We are currently in a limited availability phase, which means that we are just rolling this out to our Prospect Insights Pro customers over time. And, again, the pro version, Prospect Insights Pro, is intended to provide more of that flexibility, beyond the prescriptive queues that we have available in both versions. So both ProspectInsights and ProspectInsights Pro are currently using a national model, and this evaluates thousands of data points to identify predictors of major giving behavior and uses those variables to identify the best major gift prospects in your database. We're also working on adaptive models for Prospect Insights Pro, and these will automatically identify opportunities to further improve predictive model accuracy by incorporating organization specific data points. This will all happen behind the scenes, and it will always provide the best version of the model for your organization, whether that's the national model or one that is incorporating, organization specific data. This will be an iterative approach that adheres to our trustworthy AI principles, but the end result will be models in Prospect Insights Pro that adapt to your data, providing a more precise prediction of which prospects are most likely to be your major donors or your planned gift donors. Within Prospect Insights Pro, we're also adding in new functionality that really connects it with the chat for Blackbaud AI functionality that is also coming soon. So the first example of this are optimized opportunities and action plans. So within Prospect Insights Pro, as you're reviewing, say, your undergiving prospects, those individuals who are currently assigned to a fundraiser, but we're showing that they could potentially be giving more to your organization than they have been. If you go to add an opportunity for those individuals, we will prefill some of the fields based on what we know about that individual. And we'll include an explanation so that you see which fields we are prefilling and why. So for example, we'll suggest an ask amount based on their target gift range and based on the largest cumulative giving total to your organization. Of course, all these fields are still editable, so you can adjust based on your needs, based on your strategy. And then when you save that opportunity, you'll be asked if you'd like to create an action plan with chat for Blackbaud AI. And so what this will do is create a series of actions to help you get to that opportunity goal, to that potential ask amount. So it'll say, you know what? Let's start with, this email, and it'll provide a draft content for that email as an action. And then a few weeks later, it'll suggest reaching out with a phone call, and it'll include talking points, that you might wanna consider for that conversation. Again, all of these actions are also editable. You can work with chat for Blackbaud AI. Maybe you say, I just want a series of three actions, not five, or I need it to be spread out over time. So it's working as an assistant to help you build out that plan. But, essentially, you'll end up with a series of actions all with dates in the future that are tied back to that opportunity, helping you to have a a proactive approach, put a plan in place to see how can we increase the levels of giving for this individual. Yeah. Tons of exciting stuff here. We're all really excited about the adaptive models in in particular. It's a technically, challenging thing to implement, but we're we're excited to see that roll out. Oh, also wanted to talk a little bit about fundraising performance management. We've continued to make progress on that solution. We've been working on modernizing or improving the user experience and the transition over to Sky UX. And so this allows for a lot more consistency across the Blackbaud product suites and also provides increased accessibility within the solution as well. Finally, it's gonna help prepare us for some enhancements that are coming in the product in the years to come. So last quarter, we completed the rollout of the relationship profile, which is shown right here. And up next, we're gonna be spending time in the console, so working on goals, and then we're gonna move on to the drill downs from there. Now one of the exciting things that that's opened up for us is a way to rethink the experience for customers also using Razer's Edge NXT. So early next year, we're going to be rolling out a pared down version of the solution that allows for a turnkey implementation for customers on Razer's Edge NXT. You heard me right. There is no export or import or queue management. So this new version of the solution will lean on a standardized approach to data transformation, making it significantly faster for our customers to realize the power of intentional management in driving their fundraising outcomes. So if you're interested in learning more, I think we've got a rally link over in the resources section. Please follow the link, fill out the survey, and we'll be sure to follow-up. This is something that we're rolling out to a limited subset of customers over the course of this next year, making available to a limited subset. We really wanna make sure that this is a great experience for all of our customers, and we think there's a lot of value here for the broader Blackbaud community. So let's go ahead and move a little bit further out and talk about some of the things that are upcoming or that we're continuously working on. So any, you know, data scientist worth their salt knows that quality, consistency, and accuracy are really at the heart of a good prediction. And so I mentioned the LiveRamp transition over the last year. We're continuing to look at ways that we can refine, expand, improve, and deliver more data that really drives actions. You know, at the heart of all this, right, we don't wanna bombard you all with any information. We really want it to be useful and meaningful and get you to the place where you and your organization can take action. One thing that we're working on this next year that I'm really excited about, and we've already taken a couple of steps in this direction, but as a continued, march towards a consolidation of our data products. So just to kinda ground this a little bit, it's it's in in line with some of the context. Right? So when you use a variety of our different solutions, for for example, with a predictive model, you may see different permutations of that model depending on the solution that you're using. So, for example, fundraiser performance management has, major giving EDI, whereas prospect point has major giving likelihood or prospect point or prospect insights rather has major giving likelihood. And so we're trying to really be intentional in consolidating these experiences. The benefit is, again, you've got consistency across all of those. So your users will be familiar with the scores as they navigate between solutions, but it's also gonna allow us to iterate and evolve these models more quickly because then we're managing one centralized version of that data product that then is pushing out to the consuming solutions. So, this is gonna be a huge boon for the quality, consistency, and just everything on our models. So we're really excited about some of those changes here in this next year. We're also really actively exploring this idea of a a research assistant leveraging AI. So there's a tremendous subset of challenges here in terms of assessing the quality of information, connecting it to an individual or a business, but we really wanna think about creative ways that we can help streamline this process for our customers, because we think there's a lot that this technology can bring to bear in helping solve some of the problems that are are real pain points. You know, I remember back in the days, when I was leading a prospect research and development shop, all the the research briefs that we did. You know, there's gotta be a way that we can help, improve this for our customers. So we're really actively exploring some ideas in the space, that I I think are gonna be really valuable. So, this is just kind of the tip of the iceberg. We've got lots going on behind the scenes. Again, you're gonna see some of what, we talked about here and even some things that we didn't cover in our presentation and some of the other product update briefings. But, I'll say on behalf of all of us in the data intelligence organization and here at Blackbaud, we really appreciate, your partnership. We appreciate that you're customers and, really appreciate the impact that you all are having in the world. It means a lot, and and there's so much good that we can do out there. So, thank you for your time. Carrie and I are gonna stick around for a little bit. We're actually gonna leave the session running for a while so that it doesn't shut down the q and a's early, but we'll be available for any questions that you might have. But thank you, and have a fantastic day and end to your year. Cheers. Thanks,