Powering AI with Wealth Intelligence: Activating Windfall Use Cases

Today, we're gonna be talking about powering AI with wealth intelligence and how to activate windfall use cases. So we'll go ahead and jump into the topic today. First, just to give you a sense of who's talking, I'm Kathleen Atkins, our VP of marketing, and I'm joined here with Matt Donahue, our head of solutions engineering. If you catch me saying y'all at any point, he's influenced me and somehow have picked up that language through working with you. Thanks, Matt. And we'll be jumping into the agenda. So today, before we get into that agenda, we'll go ahead and actually kick off with our first poll because we really love to keep these interactive. So let's go ahead and launch that poll. Here we go. So tell us a little bit about why you joined today's webinar. You can pick, multiple options here. We just love to get to know you and why you're here. We'll give you just another minute to pick some options. Great. Thanks so much for, interacting here. It looks like the most of you have been able to go ahead and respond. So I'll go ahead and, share this with you so you can go ahead and see that, got a pretty good mix here. A lot of people wanting to learn about new ways to leverage AI, which we'll definitely be talking about today, how to incorporate wealth intelligence into AI workflows, and then a good mix across the others across the board. So thanks so much for letting us know, and we'll keep going into the agenda today. So we're gonna be giving you a quick windfall overview for those of you who are less familiar. For those of you who've been to a windfall webinar before, we'll do that quick overview and then jump right into new materials, where we're gonna talk about wealth intelligence and how it fits in AI workflows, predictive AI scoring and prioritization, as well as enrichment in both real time and batch activation, and then, show you an example with some Gen AI dossiers and, how you can leverage, an API for real time use cases. And then there will be time at the end for q and a, But go ahead and, pop questions throughout into the q and a, and we'll try to take a look as we go as well, but definitely setting that time aside at the end. And then just quickly, you will learn a little bit about windfall, those topics I just mentioned on the agenda, and which are gonna deliver the fastest value, and see that new API, access that we have as well as want to call out that we won't be going into a detailed explanation about how we build data or any detailed information about products and services. So if you are wanting to learn about that, we definitely encourage you to reach out to us and happy to schedule a meeting with you. You can let us know in the chat, in the q and a, or send us an email. We'd be happy to schedule time with you. So let's just jump into that quick Windfall overview. So Windfall was started in twenty sixteen, and our vision has stayed the same throughout that time, to democratize access, workflows, and insights on people. And our cornerstone is actually household net worth, but we call this people data because there's so much more to capturing net worth and to capturing this relevant data, like career informations and life events and asset ownership and so on. So that's why we refer to this as people data. And when we started, which is still true today, there was this major gap in regards to the precision of the traditional network data available. So first, Windfall's providing precise net net worth data. We're not saying Jane Smith is worth greater than two million. We're not using bands like that. Instead, we're saying she's worth precisely forty nine point nine million. And a lot of folks are looking at household income and home value, which are not as useful to understanding where a household's overall capacity might be. So if you're what if you're targeting someone who's retired and they don't have an income? You're not really to get able to get a full picture of that unless you have a more precise full picture of the household net worth. And that really leaves organizations struggling with what's good versus what's bad data and having accuracy problems or just not seeing traditional wealth data solutions as being, able to bring business outcomes. So Deloitte actually studied this in a a deeper look at the data and published a study showing that these types of the legacy data are actually only fifty percent accurate. And why is that? So taking a look at what's going on with the typical kind of data that you can see is that if you look at this example of Jane Smith, when you look at a high level, it actually looks pretty good. But as you get more granular, especially in the, like, the upper edges of wealth where that's where where things really start getting messy. So the reason being these legacy providers are primarily built on survey and census data, and that's often aggregated at a high level like a ZIP code. So if you look at somewhere like San Francisco, which is where I'm based out of, at the ZIP code level, you might think actually everyone in that ZIP code is a millionaire, and we all know that's definitely not the case. Each household in that ZIP code is different from their neighbors. Some are homeowners and some have renters in their household, and they're all gonna have different net worth and other attributes than the neighbor across the street from them. And the other problem is really around timeliness of data. So if you're relying on, say, census data, that gets stale pretty quickly, and data from these legacy providers might get updated annually or maybe quarterly. And the world changes really fast as we've seen a lot with the pandemic and the great transfer of wealth, and there's a lot moving in people's lives and in the world all the time. And ultimately, when that data is, not precise and not, updated, this leads to targeting the wrong people and wasting a lot of money. Deloitte showed that that's upwards of twenty billion annually, from this data that's fifty percent accurate. And that's really where windfall enters. We think about this today. We we solve this, and we work with over fifteen hundred organizations across the country. We're a hundred percent US focused with our data and track over one hundred million US households with twenty million of which we consider affluent that we define as those with a net worth of one million or above. And, really, the net worth assets minus liabilities, look at a balance sheet on a household. So say someone living in San Francisco, like I mentioned, has that million dollar property, but they actually have an eight hundred thousand dollar mortgage. We would take that into account. So the one million minus the mortgage, and that person would show us having two hundred thousand, as net worth and wouldn't show up as affluent as a very simple look at how that could work. And we take that all into consideration and update our data on a weekly basis. So some of here are some of our really incredible customers. We've got across luxury retail, travel and hospitality, financial services, and we work with a ton in the nonprofit space, which we're pretty well known for. And then when we think about how we help these kinds of organizations at a high level, we really empower with accurate data. So identifying and prioritizing who you should focus on that's within ideal customer profile or donor targets and then also help you to really understand your database. This could be additional segments or cohorts or personas that we're able to glean more insight on through analysis and segmentation and helps us determine data strategy based on where you're winning. And then finally, all this data is most useful when it's fed into other workflows. So we think about engaging. How do you take these insights and leverage them to engage with your customers with personalized messaging, modeled marketing audiences, and other use cases that that Matt's gonna get into here in a bit. So we'll jump into where wealth intelligence fits into AI workflows. And before that, we're gonna do one more poll here. Would love to get a sense from you on how do you currently leverage data in your workflows today. So let me go ahead and share that poll with you. Here we go. Give you just a moment to fill this out. And we'll go ahead and give you a minute to to let us know. We'll try to tune what we're presenting based on where you're at. We'll give you just another minute, but looks like a pretty good spread across many of these options today. Okay. So taking a look at this, you can see there's a a good chunk of people here who they look at data on the daily from the CRM or some who are enriching hourly depending on the situation. And we also have people who've developed personas based on data and third party data as well as some not currently using data and workflows. So we'll make sure we cover on some things that could be relevant to all those categories today. And if we really think about data, we like to think about it in, like, how you can power AI with data, with wealth data, and really activate the right use cases. And as a foundational start, we like to kinda level set on a maturity curve for how well data is able to support AI in action at the starting point. So this x axis that you're gonna see is maturity, and this is gonna be a measure of how sophisticated your use of data is, not, like, how long you've been around. And the y axis is gonna be the business value that it can bring because the more mature your data foundation is, the more AI can actually do for you. So we'll break this into three stages of data maturity. So the first is what we call establish, and this is where most organizations start. So working out of their CRM, segmenting on transactions, or maybe starting to layer in third party data or enrichment, look like a good, batch of you here might fall into this category, which is a great place to to start, and we can show you some examples of how to get started there. And the next phase is with Drive, where you actually start getting more value from that same data through smarter segmentation, better reporting, tailored direct marketing, and predictive models. And then the next is with Orchestrate. And this is where data begins to automatically trigger action. So AI can generate content, systems can alert teams when something changes, and prescriptive workflows start to happen. And the key point to all of this is that it's not about good or bad answers. It's about identifying where you can start doing more of the work in your organization. And the core topic today is really about how to understand what data can help you drive forward and make that actionable. So with that, I'm gonna hand over to Matt who's going to talk about predictive AI and scoring and prioritization. Awesome. Thanks, Kathleen. I'm very excited to dive into the details here as we think about how you can use WinFalls data within your workflows and how it can leverage some of your AI solutions as well. And so the first thing I wanted to discuss, as we think about data enrichment, you know, wealth is a really great foundational starting place. It doesn't really provide you the full context, right, on a constituent's profile. And this is where Windfall's additional data attributes can provide your recommendation engine or your segmentation strategies additional context. Additional context. And so if we look at, you know, two different constituents here who have different network profiles, there's likely a lot of additional considerations if we're trying to predict whether or not they're likely to make a gift to your organization. You know, the first is, you know, how they connect to your organization, you know, what their relationship is with you, if they are aware of your mission and some of your work. You know, the second might be other assets they own that are, you know, indicators of their lifestyle or affinities, you know, if they're supporting other organizations, you know, if they're generally wealthy and and philanthropic, you know, likely a better fit. Do they own different assets? So as you think about individuals that have a more sophisticated real estate portfolio or own a second or third home, oftentimes, this can serve, you know, the backbone of someone's net worth profile. Although their wealth could be tied up, right, in those physical tangible assets, they may not have as much liquid cash on hand to make a major gift. And so if we were to look at these two, you know, prospects or constituents from a net worth perspective alone, you know, they're both relatively qualified for your organization to make a major gift. And this is where leveraging machine learning models can really help us optimize for outcomes. So really taking a look across a variety of different data attributes and help your organization surface those constituents most likely to make a major gift. Or if you're a commercial organization, you know, those most likely to book travel or make an investment. And so we're flexible in terms of our ability to use your first party data as well as Windfall's wealth context to build these predictive models. And the objective of modeling is really to help you better prioritize records within your CRM file. There are a lot of constituents you could potentially reach out to, or assign to a major gift officer. We wanna help you focus your time, energy, and effort on those that are going to be most likely to make a meaningful gift to your organization. And this is where, you know, wealth screening certainly goes a long way in providing you additional context outside of your gift history with a constituent. You really begin to understand their net worth profile and other life events that may make them more likely to make a gift. You know, if we see they have recent liquidity or they recently got promoted, you know, that could be a great opportunity to engage that constituent. But in many cases, you know, requires looking at a lot of different data points within your CRM, and you're trying to parse out who's most likely to make that gift and, you know, respond to your outreach. And this is where modeling can help really stack rank your database to better understand who's likely to engage with the organization. And so as we're thinking about using data for predictive AI use cases, your model scores can be a really powerful tool for segmenting your CRM file and dictating, you know, which direction you you go in for servicing that constituent. You know, reassigning that constituent to a major gift officer portfolio. Are we putting them in a mid level giving portfolio? Are we positioning, you know, more information around our annual fund and really just trying to build a relationship as we think about, you know, stewarding a larger gift over a longer time horizon? And so this is really where data can really begin to power a lot of your workflows as we think about not only providing you context on net worth and career information, but also a predictive score that can help guide some of your workflows. And we have a a lot of experience in this space both for working with nonprofit organizations, you know, as well as commercial teams as well, so across, you know, retail, travel hospitality, financial services. So there's a variety of different types of models that we can build that are really bespoke to your organization. And so as we think about, you know, nonprofit as one example, you know, we can look at, you know, models that are really optimizing around an annual fund, identifying those that are most likely to participate in your annual fund or maybe make a leadership gift at a a larger level. You know, our most popular use case, you know, really understanding major gifters within your CRM file based on your organization. This may be, you know, a gift in excess of ten thousand dollars. You know, for others, you know, maybe a gift over a hundred thousand dollars. So you have the ability to be flexible there in defining, you know, what it means to be a major gifter to your organization so we can, you know, really tailor that model to your team's objectives. And then there are a variety of other use cases as we think about using modeling, you know, if we're trying to surface those that are most likely to upgrade or make a planned gift or respond to direct mail. There are a lot of different models we can build leveraging WinFall's data, including your first party information, so gift history and their engagement with your organization, as well as WinFall's third party context. On the commercial side of our business, you know, we're oftentimes building lead scoring models, so helping your team more effectively prioritize records within your CRM so that can inform routing or team assignment, as well as building marketing fit models as we think about building marketing audiences, you know, for your team to deploy across your digital channels. So as we think about how you leverage, you know, model score or some of the data insights that Windfall can provide your team, I wanna provide some tangible examples for you that you can kinda use as takeaways from today's webinar. And so with Windfall solution, you're gonna gain a lot of additional insight into your constituents or leads within CRM, including detail on their net worth profile to the nearest one hundred thousand dollars. If you have some of our modeling products, you know, how likely they are to make a major gift or engage with your organization, and then other characteristics that just provide more context about that consumer's profile. You know, have they had a recent life event or a liquidity event, where more timely outreach may be impactful? But as you think about choosing the right data layer, this is really where context can really play a role in terms of the outcome for your organization. So comparing two different, you know, data vendors that are providing you insight into net worth, you may have, you know, data vendor a that's providing you a range. They provide you insight into whether or not someone is qualified and some basic details on that that profile. Maybe you have an idea that they're philanthropic and supporting organizations. You know, they're certainly affluent. We don't have much other context on the profile other than knowing you should potentially be discussing, you know, a a gift with this individual, but maybe not a major gift. And so this really determines whether or not you assign them to a major gift portfolio or what cadence of outreach that you're going to do to this constituent. And so is this, you know, constituent qualified? Maybe. We know they're philanthropic. We know they're affluent, but there's certainly probably other folks in the CRM file we might focus on first. And so you might, as a result, enroll as constituent or contact into one of your drip campaigns. Well, that may not resonate based on, you know, the status of this particular household, you know, what they're expecting in terms of engaging with your organization, as a result, may go dormant. You then have, you know, other drips that you're running to try and reengage folks. You know, ultimately, you're able to to secure a gift that's more meaningful from this prospect. But the the journey there was, you know, pretty long in terms of having multiple touches, multiple outreaches, and testing and learning as you go. Well, with Windfall, we're providing you more precise intelligence. So we're not looking at a a wealthy neighborhood or providing you a bucket of someone's wealth. And so with Windfall, you might actually learn that this constituent is a lot wealthier than your legacy vendor was flagging them. And we see as well that they are philanthropic. I'm gonna provide you that additional career context as well. Well, with this additional information, it's going to really change how you approach personalizing outreach and thinking about engaging this constituent. So right away, we know this is someone that we want to qualify for our team, and we wanna do more personalized outreach. And as a result, by having this constituent in the appropriate workflow and routed correctly, you know, we're able to really improve their overall experience with your organization and reduce the time to close. And so this is where choosing the right data layer becomes really important as you're thinking about the segmentation layer, you know, rules of the road as you're thinking about assignment, and then also any other types of, you know, AI campaigns you're running. You know, the foundation of predictive AI is really accurate data for it to make decisions, and this is where Windfall can help drive those for your organization. So let's talk about how you go about, you know, scoring and enriching your database and a couple different ways that you can leverage Windfall in your day to day workflows. So it all really starts with providing Windfall insight into your constituents. This could be through a native CRM integration, you know, using an SFTP that connects to your data warehouse or uploading, you know, CSV files to the WinFull application. And from there, we have the ability to do a a variety of different things. You know, the first is really providing you additional context on those records. So providing you an append with enriched data. This is really to help your team identify additional characteristics of those, you know, leads or contacts within your database and help inform some of your initial top level segmentation. But from there, we can do a lot of additional use cases as we think about, you know, building different personas, building predictive models, or identifying some of those hidden gems that perhaps your team hasn't prioritized historically, but we now know they're a really good fit for your organization. And so this really where enrichment can help drive action for your organization. So just as some examples of the types of data that we have available across our data dictionaries, we can really begin to provide you insight into constituents' net worth, their career, to have a donor advised fund, to they own multiple properties, you know, other demographic data attributes. We're really providing you richer segmentation opportunities. So you now understand their transaction history with your organization. You know, perhaps first party data they've shared with you as well. Maybe you have age, for example, or gender information that folks have self reported. You can then layer that on top of WinFalls attributes to create very specific segments to go out and and target for your campaigns. And so this can trigger a variety of different use cases, you know, workflows using this data. You know, it could trigger automated email campaigns, you know, registering tasks for your team to really focus time, energy, and effort on the right records within your CRM. Perhaps that's assigning a task to provide an update to a constituent on the impact of their gift or sharing your annual report. Could also inform routing. Maybe someone is a first time donor to your organization or a first time purchaser for your brand. How do we ensure that we're providing that white glove experience and really setting the stage for, you know, a larger gift in the future? And lastly, you know, creating a repeatable system. You know, we view data enrichment as an ongoing process with your organization. We're giving you the latest and greatest information versus, you know, one time append where maybe you get some early results from that project, but you kind of exhausted all of the data that's available. We really wanna provide you the most recent information possible so you can continue to enroll people in different flows, create additional tasks, and really create this flywheel using data for your business. And so with this, you can really begin to prioritize your constituents or leads a little bit better, you know, create actionable segments that allow you to, you know, visualize insights about your constituents and really begin to drive personalization at scale using data. We know that's been a hot topic for a long time, you know, as we think about personalization and segmentation. But AI really just makes it that much easier as we think about engaging with your lead records at scale and providing AI some additional context on those records. And so let's take a look at an example here. This is looking at a particular segment within the Windfall application where we're evaluating households with the children present in the broader New York City metro area. In this case, actually, New York, New Jersey, and Connecticut. So not just the MSA, but, you know, the entire states. And we can see the overall, you know, size of the segment here. It's around eleven thousand leads or constituents in CRM. We have some wealthy, records in this file, so pretty significant wealth represented by these households. And we have the ability to, you hover over and view additional insights into, you know, where these folks are based. And so with this data, you know, we can begin to make some decisions as we think about territories. You know, is the region large enough based on current staffing, and do we see more opportunity to to win additional folks within this market? You know, with more data, you know, we can begin to inform some of our personalization. You maybe wanna build a couple different segments here outside of just looking at those higher net higher net worth families in the the broader area. You maybe wanna really zero in on particular geographies or other attributes to really make that message resonate and build a smaller list size for our team to focus on. And then, also, you might learn there are markets where there's untapped potential. You have records within your CRM today. You don't have an office or a team local to that particular market. But it could potentially be a great place to consider a site visit and, you know, doing some additional outreach to those constituents or donors. Or if you're a wealth management firm, you know, evaluating staffing as you're hiring additional RIAs or considering m and a activity really could just begin to help inform your overall strategy outside of thinking through, you know, how you're gonna work through that pile of high quality records. And so just as an example, you know, pivoting to financial services use case here, and we have a a lot of different folks on the call here today, so I wanna make sure it's relevant to everyone. This is an example of how you might leverage Windfall in that context. So we work with many firms that are offering alternative investments that require an investor to be accredited. There are a couple different ways you can be an accredited investor. One is through household income, Another is through net worth, and then third is through a series certification. But Windfall is really focusing on that net worth test. So is someone qualified to invest in alternatives? And we have a a flag that helps these firms better understand those that are accredited. And so when you're screening your database, you know, we can really identify a side of those that have invested historically, you know, who has the the net worth to pass that test where they're able to make a meaningful investment with your organization? And so we usually, you know, start by taking a look at yes or no. Are they accredited? If no, you know, we're typically disqualifying that record. If they are, you know, we can definitely break down that population a little bit further, you know, based on other windfall attributes. You know, do they work in particular industry? You know, how accredited are they? You know, are they ultra high net worth and, you know, working with a family office, or did they just pass the accredited hurdle and maybe are looking to invest the minimum? So oftentimes, organizations are grading their their database using, well, first party data that they collect on how much someone wants to invest as well as when false third party context, which can help inform how much someone could event invest. And so, you know, if they're, you know, not at the the top of the list, you know, perhaps we wanna go the general nurture route. If they're, you know, at the top of the pile, we wanna assign these folks to investor relations. And so as we're building relationships with prospective investors, you know, helping get an additional human touch and explaining the offerings that the firm has, inviting, you know, these folks to their deal room, you know, going through more specific processes required for someone to make an investment. And so for those that are not assigned, you wanna make sure that they are prioritized for one to one outreach. If they are assigned, you wanna make sure that the team is actively working those those leads within their CRM. So this is just an example how you could stack a couple different data attributes to create a workflow using WinFalls data. Looks like we did have one question come in here on just understanding interest or affinity. Windfall has the ability to help your organization better understand the types of philanthropic causes that a constituent is supporting. So in an investor context, you know, may be helpful to know who's supporting the environment depending on the alternative that you have available that may or may not be a good fit for that investor. If we're an oil and gas company, you know, perhaps we wanna deprioritize those that have more strong, you know, interest in the environment. You know, if we're offering, you know, renewables, it's sort of the opposite signal. Right? So we do provide that at the the NTE category level. So, you know, the environment, for example, or education or animals. So this can be helpful as you're thinking about tailoring the matchmaking process. In the commercial space, we see this helpful for, you know, matchmaking leads with different advisers who share a common DNA or interest category or positioning the right type of product to that investor. In the nonprofit space, this is super helpful for programming and just understanding what your constituents are interested in more broadly. There may be, you know, cases where they're already supporting organizations in your NTE category. You know, if you were an educational institution, they're supporting other educational causes, that's helpful context. But if you're also seeing they're supporting the arts, you know, maybe that can help inform the types of programming that you're getting in front of that constituent. So a bit of an aside, but wanted to share that additional detail based on the questions in the the q and a. Another really common use case we see is just understanding potential share of wallet opportunities. This example, again, is contemplating a financial services organization, but this kinda holds true across verticals that we service. You have your first party transaction data. You know, how much has that individual spent, donated, or invested to your organization, and you have windfalls, you know, third party context on their household level net worth. And so for a financial services organization looking to improve education around their their products with investors, oftentimes, there's a a minimum required for an alternative. So there might be a fifty thousand dollar minimum where an investor comes in, you know, really wants to see and learn more about the program and evaluate performance of that initial fifty thousand dollars before they decide to allocate more of their their net worth or their investable assets to that firm. And so this is where using WinFalse data, you can identify those that had made more modest initial investments or deposits, who has headspace to really grow with your brand, and similar parallels here play out across verticals as we think about, you know, maybe those first time donors who made a a lower gift with your organization, but they have the ability to become, you know, a major gifter over time. So this is where you can really begin to develop, you know, a short list of who you wanna invite to upcoming events, perhaps introduce your leadership team to, and really focus in on improving reinvestment rates with your your investors and increase that that lifetime value using Windfall's data. And this is an example of some results we've seen in the alternative space. This was an organization that was using Windfall across a variety of use cases. They first wanted to enrich their database to understand who is a credit accredited. They had a couple different lines of business, some that were more well suited for retail investors, others that required accreditation. And so using Windfall, they're able to identify a very large pocket of accredited investors within their CRM file, and then also those that were qualified purchasers. So that's an even higher hurdle rate as we're thinking about, you know, investable assets. And, typically, qualified purchasers are making investments of a million dollars or more. So the ability to surface the highest net worth individuals within their CRM was really impactful in informing their investor relations outreach. They also partnered with Windfall from a marketing perspective, so using Windfall to generate new demand through paid media. So using Windfall for marketing audiences of who they want to target across these platforms, and they're able to generate pretty significant volume on their platform in the first three months working with Windfall as well as creating more of a queue for their team to work through as they're thinking about engaging with some of these investors who have, you know, pretty significant share of wallet opportunity. In terms of where they went next with Windfall, you know, really using market intelligence to better understand, your growing market opportunities. They're evaluating potentially staffing additional folks on their team outside of corporate headquarters. So it's helpful for them in understanding where they saw opportunity across the US and using our platform to really drive some of those insights. We have many clients who build total addressable market analyses with a consultant or perhaps are preparing these for a board presentation. You know, Windfall's new market insights product makes it easier for you to review this on an ongoing basis and track your penetration over time. So just as an example of how this might play out, if we were looking at the Florida market where I'm based, you know, we could begin to understand where, you know, a firm had offices and what opportunities currently exist to better service high net worth consumers within the state of Florida. And so, you know, we can see we have locations here in Tampa, Miami, and Orlando. There's lots of opportunity here in Naples and Palm Beach, which may not be a surprise knowing Florida geography, but also helpful in just quantifying how large is that size of price. And so identifying, you know, the number of households that meet that target criteria is really impactful as you're thinking about making a business decision outside of, you know, using, you know, gut feel or, you know, census data, which only provides you a very limited snapshot of of what's going on at that particular particular neighborhood. And lastly, we have dossiers. These are a great way of just understanding additional context on constituents within your CRM. This is a newer product as well, like market insights that we've built over the last year or so. This can help you create sort of a human readable output using generative AI to better understand how you might engage with a prospective investor or donor within your CRM. It'll provide recommendations of how you might reach out to them as well as insight into their career profile and where they went to university and the windfall related attributes. And so this can really make data more actionable for your team and knowing where to spend time, energy, and effort. So with that, we wanna talk a little bit about our API here as well. As we're thinking about data workflows, the more timely you receive that data, you know, certainly more actionable it is. And so we have many organizations that are screening with Windfall on a daily or weekly basis. But more recently, we have released our our API, which allows you to get more real time intelligence. So you could think of data enrichment as having, you know, two different tracks. The first one would be a batch file processing or CRM process, and we're taking a look at a much larger population, and we wanna screen, you know, multiple records at once. This can really help us get the most up to dated information at scale, so refreshing, you know, our insights on consumers every single week. This informs, you our segmentation and how we ultimately build campaigns. The second is looking at someone who's higher intent. In that moment where they're considering potentially making a gift to your organization, you know, attending an event, or have registered as a a subscriber to your newsletter, and maybe there's an opportunity to have a fast follow-up conversation with this prospective lead while they're kind of at that particular moment in time. And so the batch process is really designed around, you know, email segmentation strategy, event planning, some of those use cases where you may need to know more about your consumers at scale versus the API, which is really designed to give you insight on a specific person at a specific point in time. So you can imagine Jane here filled out a a lead form on our website, and we may wanna know more about Jane so that we can determine, you know, which team we wanna assign Jane to as well as what drip campaigns to enroll her in. She's learning more about our organization. And so if you submit that through the Windfall API in a matter of less than a second, you can get insight on, you know, Windfall's data for her household if we match, and that can really begin to guide some of your routing. And so we see it as a really powerful extension of sort of that batch process that we've supported historically, where now your organization can really begin to get more instantaneous insight into someone's net worth profile and other characteristics. And this is really where we see real time data, you know, amplifying business value for your organization as you mature. So similar to our data maturity curve, you know, we see the the API here really helping drive some of that real time routing for your organization, you know, orchestrate data across systems, and provide you that timely information. So, you know, there are many organizations that aren't ready to use the API today. They're sort of just establishing their data workflows, and bulk screening, provides them tremendous value. There are others that have a very significant number of new donors to file or new lead form submissions every hour. They wanna gain more insight into those records in a timely manner. This is really where you can build some of those repeatable processes for your organization. And so some common use cases we see for the API across the the verticals that we service, you know, first is really lead form enrichment. So, again, someone comes to site, they fill out that lead form. Instead of waiting to send that record to Windfall as part of your weekly batch process, let's provide you insight on that consumer right away. So really just speed to lead insights, that can help inform routing, as well as personalization. The second would be pertaining to integration with your CRM. This could just be taking the lead form submission, you know, getting the Windfall Insights, then pushing it into your CRM. But there could be cases where you have your own proprietary CRM. Windfall doesn't directly integrate with, and you want to get more real time insights loaded up in there. So you could also use Windfall in that capacity to send alerts or load records into your your CRM as they're flowing into your your platform. And then the others had more to do with just real time insights. So as we're seeing, you know, changes in records, someone comes back and makes another purchase or donation with your organization, you know, proactively rescreening those records outside of your sync schedule just so you have additional context and understanding how you want to follow-up with that person. And then leveraging this data, you know, in your predictive models, you know, maybe you're using one false data to determine who you want to mail. So having some insights there, sort of on demand becomes really powerful as records in your system are kind of changing very regularly. So here are four different examples of how you could use WinFalls data in workflows. And a couple of these we've taken a closer look at already, but I just wanted to share again as we're thinking about using the API. The first one is, you know, that qualification and assignment of inbound leads based on their profile. You can really begin to leverage additional third party data here, or perhaps you relied on form fill answers in the past to dictate where that lead goes. You third party data can play an important role there in filling in some of that additional context. Can really begin to inform some of your workflows. So as we think about, how we want to personalize outreach outside of who we assign the person to, what's the most relevant message for us to send? So getting some of that additional, you know, data there can really drive some of your personalization work. And then lastly, as we're thinking about more scaled use cases across your database, you know, identifying those that have opportunity to increase wallet share or those that have, you know, current intelligence data as well, you know, how do we use that information to really develop talk tracks that are going to be meaningful as we begin to engage these constituents? Now here are a couple examples of how we've seen customers using the API across these different use cases. I'd say the most common is lead form enrichment. So customers that have high inbound volume, or even if they have moderate inbound volume, maybe they have a smaller team. So understanding which leads to prioritize is really important. You're using one false data to, you know, score and route those leads without having to wait to sync their database has been really helpful in driving their their workflows and outcomes. We've also seen it used for, you know, real time insights into new records that are created in a CRM. May not be necessarily a lead form. Right? There are a lot of reasons someone may show up in your CRM, but providing more real time insight outside of windfalls, you know, daily or weekly syncs. So you have the ability to begin to figure out how you want to engage those records regardless of where they're coming from. Maybe they're not as high intent as the person who filled out the lead form, but we see that as some recent interaction with the brand that got them into the CRM. Or you're doing, you know, some bulk uploads and you wanna provide some additional insight on those records. Just allows you to get additional information pretty quickly. It also seems that some success with organizations that are embedding us into their other tools, so using our data to provide alerts or notifications for their team. Perhaps this is when a new high value client is identified by Windfall, you're providing an appropriate trigger. This could be orchestrated through your CRM. So if you're on Salesforce using flows or HubSpot using workflows to send an alert to Slack, or if you're on a different platform, you can just set up the API directly to do this. And then other, you know, more extensive workflows as folks are kind of evaluating how they wanna use AI tools, so leveraging, you know, windfalls data as an input into an AI agent's workflow or evaluating, you know, messaging as we think about, you know, passing data through to an AI platform to really ensure that we're crafting a story that makes the most sense. This is certainly the most advanced usage of the API, but a way that you can really begin to layer, you know, Windfall into your broader tech stack. So let's walk through an example to really bring this to life of how a client has used our API. And so for this particular client, they wanted to improve their sales process and helping their team assess who has the ability to make a major purchase. They're selling multimillion dollar residences. So as you can imagine, understanding who has financial capacity is pretty important. But also understanding, you know, when someone fills out that lead form, how qualified are they right away is equally important. And so this is where Windfall's API was really helpful in accelerating speed to lead and additional insight for their team as they're making decisions from a staffing perspective. And so they used our API to, send us leads as they came through the funnel and provide additional context, as they were evaluating potential assignment. So this was used for a qualification and, you know, lead prioritization and ultimately informed some of the initial sales qualifications, you know, as the client was going through that qualification process with prospective residences. And so the way this worked, you know, they fill out the lead form. It has some basic information. Much of this is, you know, helpful as we think about matching to WinFalls dataset, so really collecting rich contact data. It just makes it more likely for us to match to that household within our graph. So they require, you know, information like first name, last name, country, phone, email. You know, address is optional if they'd like to provide it. You know, it certainly helps, but can add friction in getting folks to fill out the form. So they left those as more optional inputs. Every person that submits the lead form, you know, then would call the the Windfall API, and then we would push data into their BrightDoor CRM. So based on our API response, you know, we match that record. You know, a new record would be created in BrightDoor with the corresponding Windfall data, And then they're able to determine, you know, what they wanted to do with that particular lead record. So did they wanna, you know, push that over to the sales organization to immediately prioritize? Did they wanna put them sort of on ice for a little bit, layer them into a nurture campaign? Or did they want to consider potentially a direct mail, getting a piece in home while they're sort of in that consideration process? So just surfacing those that were the best fit for a variety of different use cases and using some of Windfall's data there to make some of those decisions. And then as they, you know, view insights on a a record, you know, also having the ability to pull up their profile within the Windfall application. So, you know, data is getting pushed into Brightdoor, their CRM. But this particular customer also purchased, you know, profiles as part of their subscription with Windfall, really just to help their their team quickly glance at a record and understand if they're qualified. So as I mentioned, you know, multimillion dollar real estate they're trying to sell. So their qualified lead, you know, really has a capacity above ten million dollars. And so we can see this particular matched record here. Andrew Mills has a net worth in the ultra high net worth category. You know, it's a strong match to to Windfall's dataset. You know, Andrew here has multiple homes already in the US and a trust associated with this household. So really helpful context for the team as they're evaluating, you know, whether or not Andrew is a good fit to reach out to, and perhaps some additional conversations to have as well as their understanding, you know, his current real estate portfolio. You know, is he looking to sell a property before buying a new one, or is he really just extending his real estate portfolio? And this would be incremental to, you know, other real estate that he owns. So it really can just help inform some of the conversation that the team is having as they're engaging with Andrew as a new lead. And, again, dossiers can be helpful here as well in just making that data more insightful. So, you know, if this is included in your your subscription, you can generate a a dossier off of a profile, which is another really powerful way of making it more human readable and actionable for your team. You can share that, you know, with other users, etcetera. And so outside of just looking at a profile at a glance, you know, really trying to get some of those generative insights here on how you might actually engage this person as you're thinking about reaching out to them.