 Thank you everyone for joining us. We're always excited when people take time out of their day to join us for these discussions. Today we're going to be talking about how to use your data to diversify your fundraising. And when we talk about that, we're really thinking about data as a representation of the relationships that we have as organizations with our donors, with our audiences, donors current, past and perspective. And really thinking about data as a way and a key to shift and strengthen those relationships, particularly at scale for organizations that are operating in the thousands, hundreds of thousands and millions of donors. And so really thinking about how powerful of a resource this can be, particularly when you want to change course and change tack. So we're incredibly excited to have this and to be doing this with friends. First and foremost, I should say my name is Stefan Bird Gruger. I'm the Chief Analytics Officer at Parsons TKO. We are a consultancy that works with mission-driven organizations. And we do that to improve what we call our clients' engagement architecture. And that is the complete set of team, tools and talent that organizations need to build and strengthen those relationships. So we do this and we've been doing this for about a decade now and my full background is entirely in the nonprofit sector. And that can take a lot of shapes depending on the organization, depending on the audience and the goals. It could mean you're trying to build subscriber bases. It could mean you're trying to retain members. And certainly as is gonna be the case for today's conversation, building and strengthening those donor relationships. I am incredibly honored that we get to bring this experience to our clients and also we pride ourselves on our ability to bring our community together. So today I'm very pleased to be joined by our friends and colleagues at Earth Justice and Civis. I'm happy to introduce Andrea Estroud and Anna Berman. Really excited to have you both with us today. I wanted to give each of you a chance to introduce yourselves and talk about your experience and talk about where you're coming from. And in particular, I'd love to hear from each of you a little bit about what you see as the current moment for fundraisers, what's going on in the sector. And in particular, some of your perspectives on how data can help organizations respond. And then we'll get into the discussion after that. So first and foremost, Andrea, I'd love to hear from you first. Hi all, and thank you, Stefan and Parson T. Kale for having me on this panel. I'm Andrea Estroud, I'm the Associate Director of Development Evaluation at Earth Justice. In case you're not familiar with Earth Justice, it is a nonprofit public interest law firm. And I work there working with organization leaders to frame strategic questions, evaluate the usefulness of data around donors, gift officer performance and overall organization performance to then analyze and provide reporting that's shared within the organization to really help the leaders make informed decisions. And I'm bringing the perspective of a nonprofit fundraising organization who like many others are using data to weather the storm of global economic uncertainty, inflation and impending recession or keeping many economists and many fundraising leaders up at night. And fundraising organizations really have to be prepared for the uncertainty that is coming their way. And whether it be economic, social or geopolitical instability, you must not only be prepared for it for uncertain events to occur, but rather how to be prepared when they do occur. Great, I am Anna Berman. I'm a senior applied data scientist at Civis Analytics. I have been here for about three years, primarily working with our clients on building sustainable data pipelines. We work by providing data science technology as well as consulting services to a big slew of clients, but a lot of which have been nonprofits since our founding. And the organizations that we work with are at all different kinds of maturity levels when it comes to data. On one end of the spectrum, we have organizations that have fully developed data teams. And on the other side of the spectrum, we have clients that are just beginning their journey are just really starting to think about how to better use your data to target your campaigns and support your programs. But ultimately, the majority of my work surrounds creating pipelines for allowing our clients to unify their data, enhance their data and ultimately produce useful data assets like models, like reporting, like intelligence, such as that. So I'm really excited to jump into the meat of that presentation. Thank you both so much. It really, it means a lot to have your perspectives. We're certainly honored to work in particular. Andrea, I know we're getting some interesting stuff with you and your team right now and being able to hear those stories and really understand what life is like right now, particularly when strategies are having to shift. It's a very dynamic environment. And I think having these experiences and being able to share these tactics is what I hope everyone gets out of today's conversation. So as we begin, I just wanna talk a little bit about the perspectives that PTKO has on building these capabilities, particularly capabilities around data. I wanna just introduce this concept of engagement architecture, which is the PTKO philosophy and methodology, really thinking about outreach platforms as organization-wide capabilities. And when we talk about engagement architecture, what we mean is the collection of people, processes and platforms that organizations need to fulfill their strategies for audience engagement. And that's true across all departments, whether you're in central comms, development or program, all of these areas where you are engaging with an audience are opportunities to look at it through this way. And when you bring these things together, you are creating experiences for those audiences. And those experiences are meant to deepen and strengthen those relationships and drive engagement. And through all of this, all of those activities are generating reams and reams of data. And so a big part of what we're talking about here is how do you take that data and how do you use that data as an organizational asset that you can turn back into those platforms, turn back into those business processes to further improve the outcomes, help your team work better, faster, more efficiently, more creatively to strengthen those experiences, deepen the engagement and fulfill your strategy, whatever that may be. So with that in mind, I think we can go one layer deeper. And when we're talking about the topic du jour, and really coming back to the thesis of today's talk, refining your goals and in particular refining your diversification goal. So everyone's coming here with different experiences, coming from different organizations, facing different kinds of challenges. And I think that's an important thing to note where the sector is going through this shift and the economy is sort of teetering on the edge of we're not quite sure what or when. There are really unequal challenges and unequal opportunities facing organizations. We know a lot of organizations that are struggling, they're seeing a drop off in individual giving already. But at the same time, there's a handful of organizations facing catastrophic success. The nonprofit sector can be counter cyclical. So you might be in this moment where you have tremendous opportunity that you could seize and you have this chance to build it and what you need is to build capacity in order to seize that opportunity. So recognizing this difference, I think it's important to ask yourselves, what do you mean and what are you looking for when you say you wanna diversify your fundraising? And just a couple examples of what that might look like, you might be talking about diversifying your revenue sources, changing what the makeup of your donors look like. And so if you have a drop off in individual giving, you might be thinking about, how can I get more grant support? How can I get more major gifts to offset that loss? And then vice versa, you could be looking at just expanding the overall pool of donors. So you might be thinking about, how do we actually change the makeup and the look of the people who are giving to us? So thinking about things like age, thinking about things like race and ethnicity and gender and ideology in your donor portfolio. So lots of different ways that you can think about this and we'll talk a little bit about what those look like functionally when you're working with data, when you're thinking about how you turn the insights from that data back into your team. But that's just one lens I wanna bring to this. And as we talk a lot about the operations, I wanna bring up this framework. This is a framework that we use, what we call our anatomy of data strategy. And it's really saying that in order to use your data effectively, you have to have all four of these components. You need to have that clear strategy definition. You need to know what it is you're trying to accomplish with your data, with your audiences, everything from the mission down to sort of the tactical decisions you're making about your donor engagement. Next, there is the tracking and technology. And this is what people most often think about when they think about data and analytics is, do I have the tools in place? Am I collecting the data? Am I capturing the data? Do I have the ability to merge and manage it? Do I have the staff to merge and manage it? That's a very sort of operational side of that data, but that's not really useful unless you have that third step, which is reporting and analysis. Do I have the ability to turn that data into something that can be used by my team, can be used by my platforms to do what they're doing? So can I convert it into the right outputs, whether that's a dashboard or a report or just a well-timed email? There's a lot of different shapes and sizes for how that data gets into a usable format. But last, but certainly not least, there's adoption and optimization. How do we take advantage of this data and these insights and actually make sure that our team are building them into their workflows, that our systems can actually access that data for things like segmentation? How do we actually put this data and the things we learned from it into practice? So I think that's a full range of all the things that I would want somebody to discuss when they're talking about data and how to leverage it. I think we touched a little bit on that strategy question. I will just note, we're not gonna spend the whole webinar talking about that. We do have, you would need a whole other webinar and the good news is that we do have that. So here are just a couple other webinars related to that topic for this topic of donor engagement that folks might wanna go back to. We've got recorded versions of this that people can see. There's our Giving Tuesday retrospective, which we did late last year. I'm sort of a prelude to this conversation where we're thinking through, how do you take recent experiences and extract the lessons learned from your team in terms of how to set new goals and set new strategies and pivot those strategies? And then we've got another webinar here on a model for equity and inclusion and fundraising and outreach, which really touches on that diversity question. What do you mean when you say you want to diversify your audience? Well, that webinar provides a framework for how to think about that, how to talk about that, how to look for those opportunities to change your strategy. Next up, the other three stages of that anatomy for data strategy are gonna be a big focus of the rest of our conversation today. And with that in mind, I'm very happy to turn it over to my friends. Anna, I wanted to ask you first to talk a little bit about the work that you do at CIVIS focused on the ability to capture and manage and manipulate and create usable outputs of that data. And then after that, Andrea was gonna ask you to talk a little bit about what it looks like internally to put things like that into practice. So with that in mind, I will turn it to Anna first. Thank you so much, Stefan. That was great. I know we already touched on this a bit, but just a quick introduction to CIVIS analytics. We are a provider of data science technology as well as consulting services. And here up on the screen, you can see a number of the amazing nonprofits that we are so happy to support. Ultimately though, our goal with every organization is to enable data-driven campaigns and decision making. And we do that by providing two things, the first of which is CIVIS platform. This is a flexible analytics infrastructure and that enables nonprofits to bring all of the data together and provides a workbench of analytics tools for data professionals to work with and to analyze their data and create all this amazing reporting and modeling all that jazz. The second thing we provide are consultant services to organizations that have teams on the smaller side, as we discussed earlier, or that might not even have data teams at all. These consulting services can include everything from helping your organization to architect the data warehouse, to providing the capability to build some of these data assets that we're gonna talk about today like predictive modeling and reporting. Next slide, please. All right, diving right in. Stefan, you already touched on this a bit, but I wanna just continue the conversation about the challenges and the opportunities that we really see facing the nonprofit sector. First, at a global level, consumers across all sectors are developing different expectations for the brands and the causes that they support. Even with the decline in organizations' ability to use cookie-based targeting, consumers are still increasingly expecting timely, personalized, and relevant engagements with those organizations. And we definitely don't see nonprofits being exempt from any of this. According to M&R's annual report reflecting on 2021 Giving, we saw 71% of nonprofit surveyed saw a small decline in year-over-year revenue, 60% saw a decline in the number of GIFs, and 60% saw a decline in average GIF size as well. I'm sure that this isn't really a surprise to many of you. You may have seen similar trends in your fundraising efforts this past end of year. And there are two large compounding challenges that are relating to this topic. The first of which is something that we hear consistently in conversations with our clients, and that's that their current supporter bases are pretty homogenous. And this presents a really significant existential question for fundraisers. As the baby boomer generation ages out of their giving years and as Gen X and millennials ages into theirs, these two younger generations are bringing with them a different set of demographics, a different set of attitudes, different giving preferences, and overall just different expectations. So as you seek to expand your donor base, it's going to require diversifying your fundraising efforts to reflect those differences. The challenge there with diversifying your fundraising efforts is that too many nonprofit teams operate in silos across systems and teams, which is making it extremely difficult to gain a definitive sense of the current demographic composition of your supporter base. And likewise, it makes it nearly impossible to get a clear picture of what is driving their giving and ultimately leveraging that information to build the omnichannel campaigns that will acquire and maintain those future giving generations. Next slide, please. Now these are definitely tough challenges and there are no clear cut answers to these things, but I'm a data scientist, so I'm going to be a little bit biased here and say that I have certainly seen how data science can make a really significant impact on these two challenges. I also know that data science is a buzzword these days. It can mean a lot of different things to a lot of different people, but broadly speaking, data science is the process of cleaning, organizing, transforming, and learning from data, all with the ultimate goal of discovering useful information and informing decisions. In other words, data science helps organizations make sense of their data. What I found in my work is that many, if not most, nonprofit organizations have already amassed a large amount of data about their donors, but that also means that a lot of nonprofits are sitting on this great underutilized data asset. By putting in the work to utilize these data assets and applying a data science framework, we are able to discuss questions like, what is the current composition of your audience? What are the content and channels that are most effective in engaging your current audience? What are the content and channels that are diving the expansion of your audiences that you want to grow into? And ultimately, what specifically engenders loyalty from your donors and supporters? And what opportunities do we have to scale that further? All of these questions get at the heart of not only enabling nonprofits to build more diverse audiences, but also to diversify their revenue streams to better align with the consumption habits of both their new and existing supporters. To simplify all of these questions, essentially ask, how do we leverage our data to better our segments? This approach to segmentation is something that the commercial industry already has really honed. For example, we worked with a national fitness chain on building out their membership profiles for just this purpose. These segments included things like the fitness enthusiast, the casual gym goer, the fitness newbie. Once we had those segments in place, the national fitness chain was able to tailor their messaging to deliver to these different segments. And doing so enabled them to meet their members where they are on their customer journey and build really personalized relationships. This approach is really common in the commercial space, but there's definitely no reason why this can't be applied to the nonprofit sector. It can really help your organizations build nuanced relationships with a younger and more diverse audience. Next slide, please. Okay, so we talked a lot about what data can achieve, but how do we set ourselves up to really get the most out of our data? After setting high level strategic goals or on driving better audience engagement, the first step for many nonprofits is organizing and unifying their data. Again, this is one of the biggest problems facing our sector is that too often, organizations are still operating with that silo data, and that makes it nearly impossible to do a number of things, including truly understanding the composition of your existing supporter base, identifying areas of need, identifying areas for growth, and ultimately measuring your progress over time. So our advice to clients typically begins with telling them to get all their data in one place. For a smaller organization, this could be something like a CRM, but we find for most enterprise-level organizations, they're gonna need something more like a cloud-based data warehouse to handle the requirements around data transfers, transformations, and storage. There are a lot of data warehousing options on the market that can fit whatever budget you might have, but some of the things that you wanna be considering when you consider a cloud-based marketing or a cloud-based data warehouse is whether or not your organization is staffed to implement and maintain that data warehouse, the compatibility with your future or current tech stack. And ultimately, what parts of the organization is this warehouse really supporting? Is it your mission? Is it your fundraising? Is it maybe both? This last point is really important because implementing a data warehouse to support direct response fundraising is likely gonna have a pretty different set of technical requirements than a data warehouse that is supporting your programmatic work. Next slide, please. Of course, getting all of your data into one place is just phase one. Next, we wanna talk about how to organize, structure, and enhance your data to develop both a comprehensive understanding of your current audience, as well as how to highlight potential areas for growth. A surprising thing that we learn from many of our initial engagements with clients is that they lack a clear understanding of the demographic composition of their audience. For a long time, organizations have relied on gut or intuition to describe the current composition of their supporter base. And sometimes maybe they throw in the occasional audience survey over the years, but because of the previously discussed issues of data silos, even teams within the same organization can have really different answers to fundamental questions like, how many supporters do we really have or what is the retention rate of our supporters? Luckily, data science offers a proven approach to getting the answer to these questions. A typical data science workflow that we have worked on with a number of our clients includes first enhancing first-party audience data with third-party data. There's a lot of demographic data that depends on the market that can help your organization accomplish this. At Civis, we maintain a national consumer file that enables our clients to build more complete supporter profiles. We do this by appending demographic information, income information, as well as a number of other data points. Once this data has been appended to your first-party data, you're left with a much clearer picture of who your supporters really are. Okay, so you've enhanced your data. The next step here is you'll want to perform some kind of identity resolution. This will allow you to match and merge all of your John and Jane Doe records across all of your integrations and build an authoritative list of your total audience that's ready for analytics, modeling, and targeting. This is key for truly understanding the donor journey and the actual lifetime value of a donor. It also creates the foundation for better analysis around ROI of your marketing and acquisition campaigns. Next slide, please. Okay, so at this point, you have done all of the hard work of unifying, cleaning, and standardizing your data, and now you are finally ready to begin with the truly transformational process of building a data strategy to grow and diversify your audience. The truth is getting clean, reliable data is an essential input to any larger engagement or data science strategy. But the good news is that organizations who pursue data science often see a significant return on investment. Not only in growing their audience, but also in revenue and unlocking foundational insights into who that audience really is and what motivates those individuals to get involved with your organization in the first place. One very cool example of this from our work comes from a national environmental organization. These folks were sending sustainer asks to a wide portion of their overall audience. And this is something that we see fairly common in our nonprofit clients, that they're broadcasting but same asked to a really wide swath of folks. And this type of approach creates a barrier for the organizations that are really seeking to diversify both from a demographic perspective as well as from a revenue stream perspective. In the case of this organization we worked with them to build a model to identify the contacts with the highest likelihood of becoming a sustaining donor. With this information, they were able to really significantly reduce the size of their monthly sustainer ask. So reducing it by 75% while also targeting the contacts who were the most likely to convert. And these contacts did convert with a rate of 1.3 times their traditional prospects. And importantly, by honing their sustainer appeal list that freed up the rest of their file for more personalized and appropriate communication. So with that, I will turn over to Andrea for to talk about Earth Justice. Thanks very much. And Andrea, just as we pull up your slides I wanted to say Anna, thank you. I think there were a couple of things in there that I really appreciated. In particular thinking about how you can work on your data at scale, understanding all the different buckets of data that exist in an organization. Because as professionals, each of us usually have, there's your lane, there's the dataset that you work with, the list that you work from. And so recognizing all those other pools of data including the ones outside your organization and how you can append, amend and really grow what you know about your donor base seemingly like magic instantaneously and what that unlocks. So I really appreciated that. We, you and I both come from a data perspective thinking about this as data scientists and as agencies, organizations that can come in and do this change. Andrea, I think with that I'm very excited to turn this over to you. I really would love to hear from you what does this look like from a fundraiser's perspective and to hear from you what's been working well. Sounds great. Thanks, Stefan. I just like to begin by just giving a little more information about earth justice. As I mentioned earlier, we are a nonprofit public interest law firm founded in 1971. We really go to court to defend the planet and its people, earth justice. We believe that the fights for justice in our environment are inseparable. And we have a passionate belief that the power of the law can be used to preserve the environment and build a healthier future for all. And we're committed to the law, our clients that we represent and the planet. And we're thankful to our donors who support us in carrying out our mission. Next slide. And so I wanted to talk to you a little bit today about donor data and donor analytics. Donor data is valuable since it's fundraising strategies, the people to target, the platforms to direct most of their efforts. This data should not only be collected but share it throughout the organization. Donor analytics doesn't just refer to donor data. This term actually encompasses all the ways you can analyze your donor data in order to gain meaningful insights into your constituency. And there are really four areas of donor data analytics that we look at. And one of those is the donor engagement analytics. And that's really kind of looking at donor engagement history, how they've interacted with the organization previously. We look at donor giving analytics. So again, how they give, their communication preferences for giving. It's really getting at donor giving habits. Then we also, and kind of in thinking about donor giving habits and donor giving analytics, one thing that we've really seen thus far is there's a general trend away from giving through direct mail. And so what we are expecting for this year is about a 10 to 15% decrease in direct mail. And what that really means is that our online group will have to ramp up quite a bit for online donations. So that's like one area where that data becomes very useful because it tells you where you need to allocate resources. We also look at predictive donor analytics. And that really gets at things like donor and prospect giving capacity, donor and prospect giving propensity. Looking at donor demographic analytics that really helps us for getting information in terms of things like who connectors are. So finding new ways where we can connect with additional people through donors that we have who wanna refer and connect us with their network. And whether or not they have family who've given, looking at things like, again, age, Anna mentioned, looking at age and gender and employers and areas of interest. All of those things are really valuable, especially when you have various programs. For example, at Earthjust, there's different areas that we focus on. You wanna make sure that you're catering to what your donors have interest in. And then just kind of pointing out some areas where donor analytics really help fund raising organizations is it really helps to reach new markets. So really discovering new segments of donors who are willing to support the organization. And then part of that data is either creating lists or deciding how you wanna do social media advertising and contacting. It also helps with understanding the donor better. So any type of gaining insights into, again, interest, hobbies, their communication preferences, the program areas that they're interested in, catering to individual donors. You can really personalize your outreach to an individual donor based on the data that you're collecting and looking at, as well as catering to different segments. And that's really just adapting that outreach, depending on the age group you're looking at or the gender or the location, the geographic location of an area. Or some of the professional groups that they're involved in, as well as segmenting out your high value, mid value level donors as well. Next slide, please. So, erratic change in our socioeconomic ecosystem can really pose imminent threat to the ongoing viability of fund raising. And in order to really navigate through these times, many nonprofits use forecasting and scenario planning. And I kind of want to talk to some of that. And each year at Earthjust, as we really, as we prepare for our budget season, we're utilizing forecasting to help us make informed decisions. And then when situations are only are arising, such as when the pandemic occurred with COVID, or when we are looking at this impending recession, we take it a step further and start looking at scenario planning, which is typically done every two to three years at most organizations. And so I just really want to talk about forecasting and kind of how it differs from scenario planning and so forth. Forecasting predicts what will happen in the future by relying on exploration of recent and historical data. It works great for forecasting revenue and understanding when you may hit a certain revenue target within your fiscal year. The certainty of a forecast is probable. Forecasting models often fail to predict quick and significant changes in market conditions. So it's what's expected. So forecasting is always using data that's expected. And a weak spot when using forecasting is because it challenges your ability to assess risk in dynamic market conditions. And these models often break down because you're experiencing a new event that hasn't necessarily occurred before and it's not being included into your model and for you to test that statistic. So planned events like a pandemic or recession aren't really accounted for in forecasting. It's more focused on, again, what's certain rather than the uncertainties. And now since you have historical data to look at times when there is a recession, you can actually model based on that data to some extent. So you can't model on what hasn't occurred before but if something has occurred, for example, if there were to be an additional, like another pandemic come up, you could actually look at how the previous pandemic impacted your revenue or impacted the data that you're collecting, your donor's behavior and kind of use that as a guide for future forecasting. Because again, forecasting is very fact-based so you need to have, it's there are no uncertainties there. And a forecast is something that you typically like, you're looking at it on a daily and you can like, it's a short-term perspective but it allows you to really see how you are coming along based on what you're measuring, whether it be revenue or something else. And then scenario planning, however, is used to make assumptions around future outcomes, around possible risk or uncertain future events and how your fundraising environment can really change in response to the future, to the unknown future. And in order to do this, you really must identify specific uncertainties and how it might impact future fundraising operations. Scenario planning takes into consideration data from past events as well as events that are currently being monitored and probable disruptions. So again, that's things like this impending recession, events like we're seeing the inflation or when you see gas prices increase, scenario planning uses a mix of really quantitative and qualitative data whereas when you saw the forecasting, forecasting is strictly quantitative but scenario planning includes quantitative and qualitative which really allows you to look forward to the future and see how fundraising for major mid-level plan given and foundation donors react to certain market situations. Scenario planning should look at a base case. So a base case, a best case and worst case scenario. So you are truly like planning for what potential things could occur. Scenario planning is typically more strategic than forecasting and offers greater flexibility and preparedness than forecasting models. And because we've seen such a decline in things like the stock market and inflation going up, it's uncertain how long this will last, right? So you have to like keep in mind that it could go longer or shorter than expected. Same goes for recession. We've had recessions that have lasted a couple of months or as much as many years. And with scenario planning, it's really recommended that you take it a step further even and incorporate something called contingency planning. And in contingency planning, you've created a likely budget or forecast. And with funding, you feel confident you can depend on. And from here, you have to look at the what ifs. So that's really where the what ifs come in. What if you don't bring in a certain amount of fundraising dollars you were counting on, you have to prioritize what you currently have in your budget and work out a backup plan and alternative ideas. This is not something that's done in a bubble. Scenario planning and contingency planning really need to happen with a wide group of stakeholders involved in the process from across the organization and even getting feedback externally as well. Next slide, please. Thank you. And so with all we've discussed today, we have to remember to lean in and prepare our fundraising efforts for uncertainty. The way we go about that is to really utilize the data to help make smart decisions. So I kind of want to talk through some examples specific to how we've used data at Earth Justice beyond the forecasting and scenario planning. So really kind of looking at cranking up stewardship. So now is the time to really crank up your stewardship just because we're in the middle of economic uncertainty. You don't want to lose your connection with your donors. You want to make sure you maintain that and you want to make sure you have your donors managed. So one example of this is we had our mid-level giving group or team that just by adding three additional positions, they were able to better manage their portfolios and increase mid-level donors by more than 20% and mid-level revenue by more than 25%. So you want to make sure you have the staff in place to manage your donors. It's extremely important and campaigns don't stop, outreach to donors don't stop just because economic times are hard. That's even more of a time to connect with your donors. So definitely make sure you're cranking up the stewardship and connecting. And it was helpful to see the value in adding those additional resources because it makes you evaluate the other areas where you may want to add resources as well. And so that's like another good way to really utilize that data. We also have utilized engagement scores. So at ERGEST as we implemented a lead management dashboard. By the way, we love dashboards and dashboard reports. But this particular dashboard utilize a donor engagement score for our plan giving team. And this really allowed them to increase leads and prioritize them. It helped plan gifts reach an aggressive goal of two years prior to the campaign and it allowed them to identify donors who wanted to be contacted, their interaction history, it provided information on giving intention that was all part of the score and whether we were actually in their estate plans. And this usually is like one year of information within this dashboard that allows gift officers to go in and sort through the data and pick who they wanna reach out to. One valuable, really valuable thing about this that I wanna elaborate on is the fact that when you're looking at this type of information, making it available on dashboards where multiple people can see it. That's something that is necessary. That transparency is needed if you really wanna make sure you keep an eye on how your fundraising efforts are going and how your connections to donors are going. You also want to look at segmenting donors. You can better cater to individual donor segments. At ERGEST as we've looked at our major giving donors. And so regardless of the group you're looking in, for example, we've looked at in our major gifts, you're able to further segment that group out. And this actually has helped in terms of targeting outreach and making sure you have the appropriate messaging for each of those groups. It also helps in terms of when you have multiple programs being able to segment out the information that's going to them. Because again, an engaged donor that's interested in what you're sharing is always gonna be someone who wants to come back and like continue to give and sustain their relationship with the organization. And make sure, so I have asking capacity. So we've looked extensively at making sure that our donors are asked for the right amount by gift officers. So are they asking to capacity? You don't wanna ask a donor who typically gives at a major gift level at other organizations to give it a lower make giving level unless they've specified that, you know, that's a level that they wanna give at. But being able to identify what the giving capacity is and how gift officers to what level they're actually asking at that capacity or not is extremely valuable to fundraising organizations, especially during this time. And then you want to focus on your major donors. So major donors and high value donors, you have to let them know how essential they are. You wanna create curated events for them. You wanna meet with them. You obviously wanna thank them for the donations that they give. And thinking about things like, you know, you have to be very creative in some of these groups because with stock market, with the stock market being down and us noticing that, it's also caused our major gift officers to really increase their fundraising efforts being that major gifts oftentimes are tied to the stock market. So when we see a decrease in the stock market, sometimes there's a decrease in major giving. And so you just have to have your gift officers prepared for that and looking for creative opportunities and ways to connect with the donors so that they can maintain that, you know, those gifts coming in. And then also make information visible. And so as I mentioned earlier, you know, Weedle has a lot of dashboards to really make information visible through the organization. Gift officers are able to go in and see, you know, where they are, how they're performing to go, even do drill downs and some of the numbers to see, you know, not just like, you know, there were X amount of donations, but these were the people who donated. So they're able to really kind of go in and see that different information. And that transparency of data is very useful. I think Anna spoke to it earlier, having a lot of data in these various systems, if you can't tie them together and pull them out and share them and synthesize it for your gift officers and for the leaders in your organization, it really creates a challenge for you and your fundraising efforts, especially in times when there is economic uncertainty. And then I'll, if you have questions, let me now turn it back over to Stefan. Perfect, thank you so much. I think that's a really very valuable insights and great to hear how you're working on this internally, how you're thinking about it. You know, one thing in particular that I really appreciated, you know, when you're talking today and when we spoke earlier in that scenario planning approach to this, how that's a big tent activity. You know, that's the kind of thing where you wanna bring in broad swaths of your team, potentially even beyond the department, getting the perspectives of your peers and other departments and thinking through what's going on? What's happening in the sector? What's happening with our audience? What should we be taking into account? And I think anytime, and similarly, you know, you're talking about how you love dashboards, you know, dashboards are often meant to democratize the data, make it easier for people to access, not the data but the insights as well. And so thinking through how you can share those, which relates to one of the questions that we got, which is what is the role of knowledge management, knowledge management systems in these organizations? And one of the conversations we were having in the chat there was you can have a platform. Many organizations don't have a platform, you know, a place where you put your lessons learned, where you share these ideas, where you share the scenarios that we're preparing for. But even if you do, it takes these habits, you know, you have to be able to really think through what's my next step and what's my next opportunity to add to this repository of knowledge. So I really wanna thank you for, you know, we've had a couple of conversations there in the chat so far. You know, I think there was one question that I wanted to ask a little bit, you know, to get deeper into. And I think my context for this question is thinking about how development is often downstream of program or comms and or, you know, just the brand of your organization in really thinking through how can we help fundraisers recognize who is in their pool of prospects? What type of data do we have or do we wish we had about the people that we can be reaching out to? And is there something about, you know, using data in particular and thinking about our audience from a data perspective that makes it easier to get at that and both to shape those questions or shape the type of outreach that we would do to them. But even just understanding what the composition of our donor base is. And so I'll open it to both of you. I mean, Ana, I was curious, you know, I know you do a lot of work with a lot of organizations, a lot of databases, what types of things have you seen that can be useful in that context? For sure. I think, like I said, enhancing that data set with potentially a third party data set is incredibly useful in these scenarios. You know, you only have, you know, what you have available but there might be a demographic append on the market that could really, you know, not only give you some demographic information but might only give you, might give you some kind of information about voting history or about lifestyle attitudes, those kinds of things that are really helpful when creating personalized conversations and relationships with these new prospects. I'll also say that it's possible to get a little bit more technical with these sorts of situations. I've definitely seen examples of this in the past where you know what your audience looks like, maybe you've even appended some of the data to know who your donors really are using data. But then you can also, with this third party data append, have data about, you know, maybe potential prospects in your area. It's then possible to create a model to kind of find folks in your prospect pool that look the most like the people that are already your donors. So you can identify kind of a donor look alike and those might be the best prospects for you. So there are really a lot of options available but getting that robust data set to begin with is really the first step. And that actually, like I said, another point you made, Andrea, which I know resonated and was exciting and we discussed as being a common ask, which is how can I use data to get at new audiences, to acquire new donors? And I know that was one of the things that you talked about and sort of what you just described with those look alike campaigns. Andrea, I'm curious, do you have any other stories you could tell us about where data either helped you find or build or directly gave you these new audiences or even gave you that Eureka moment? Like, ah, there's people like this. And you described a couple of scenarios like that but any other stories you could share? So I would say in terms of thinking about the data. So again, we have events that we put on and we are able to get additional information from that. Again, we also append data as well as Anna had mentioned but I would say other things to really look at. So we have petitions and so we get a lot of information from petitions as well in terms of like what our prospective donors could be interested in because a lot of times when we send out petitions they are not necessarily for our donors or they're non donors that are also participating in that. And so we're able to gain a lot of information and insight from looking at that. Something else that I've utilized, not since I've been at Earth Justice, I know Earth Justice has done that previously but I've utilized in other places are personas. I feel like personas of certain prospects are very valuable and useful to really kind of get an understanding of what a prospect in a specific segmented group looks like what their interests typically are, what revenue group, what political affiliation, there's a list of information that is centered around like what an individual looks like based on personas and I feel like those are extremely valuable as well. Andrew, that brought up something that's near and dear to my heart, which is you brought up petitions and I expect that those petitions are happening in another unit, another department, another part of the organization, advocacy, some sort of programmatic unit. And that is the sharing that can happen back and forth between teams and how they can benefit one another. You can learn a lot about your perspective, new prospects for donors who are active in other parts of the organization and how do you make sure that pipeline is open? But vice versa, I think development teams often have the richest, the most nuanced, the most detailed kinds of information. Talking about things like data appends that mostly comes up in a development context in the nonprofit sector. And so when you have so much information, detailed information about your audience, that's in sites that you can give back to comms, you can give back to program to help them be better at understanding who the audience is, where you're starting to get gifts from these subsectors or sub parts of your audience that maybe you didn't really realize could be a part of the programmatic work. So I think there's a lot of give and take that can happen across once you start knocking down those departmental boundaries between teams, between data, between insights. So, Stefan, I absolutely agree. Making sure you have different programs and departments that are communicating with each other and having open share of data and information is extremely essential for being able to kind of really analyze that data. One other thing I feel like is very helpful as well is beyond just digging into the data and data mining, all the different data, because it's a lot of it is talking with the different teams and really figuring out, okay, what questions do you have that you don't feel like you have answers to? And then seeing, okay, do we have data? They can answer this question or do we need to go get and obtain that data to answer this question? Or can we pull it from somewhere else? So really kind of having those conversations that shape, this is the information I really want to get at and know and learn more about, I think is very helpful, as opposed to just kind of randomly, blindly going and just kind of searching. It really starts with, what questions do you want to have answered? Get that, a key and core PTKO mantra. Answers get all the credit, but questions do all the work and creating a space for your team to ask those questions. That's the start of that. So I really appreciate the work that you're doing and the emphasis that you've put on that internally. You also mentioned local events, which I will use to segue into a question we got into the Q and A, which is it's a new dawn, it's a new era and event planning for nonprofits. We had galas, we had fully remote during the pandemic. Now we're all feeling our way through what our event portfolio looks like. When we're thinking about things like hybrid events of all shapes and sizes, you mentioned how you can get data out of those events and really broaden your understanding of your audience. What data do you have? Do you wish you have? Have you encountered that are helping people make those decisions in terms of how they design and plan those events? Pretty specific question, but I'm curious if either of you have had experience with that. So for the events that we, so we do a lot of very curated, so they're not big galas for us. We do very curated events, especially for our major donors, taking them in some cases on, I don't wanna call them excursions, but going out and seeing certain wildlife and doing things that are very focused on our mission and our purpose and protecting the planet. So we do take them on those type of excursions. And so being able to get the feedback on one, not just their experience level, but also like who else they would wanna bring into and in terms of connectors for those type of events, I think is extremely valuable for us. Because again, that wide is your prospect pool. If you give someone an amazing experience and they've communicated that back, that's extremely helpful. So it's more than I give a specific dollar amount, it's more of an experience that's been curated and how that can be, how that can appeal to others that are similar types of donors. And I mean, I think for my own experience and perspectives, and we actually had a webinar just on this about virtual events and data and experience around that. But thinking through, first of all, when can you avoid it? If you have data that shows, is this person more interested and more likely to engage in one form or another? Can you diverge your event pool? Because they are very different experiences. But then also just really thinking through what is the life cycle of an event? Because the event starts long before they walk on the door. It starts with the promotion, the invitation, warm up, building sort of the thunderclap. And for the virtual component, are there corollary things? Is there other content they're consuming as a part of the event? Is there a conversation on social media happening around the event depending on its scale? And what happens after the event as well? I think all of those could be factored in. And each of those have their own data pool. Where, what channels are these people on? What's the best? What are the interests? What is it that drew them to it? How do we use that to curate content? So yeah, I think that's a good question. Well, with that, we are coming right up on time. And I wanna end by just jumping to this last side and saying thank you so much to everyone for joining us. We really appreciated and thank you so much, Anna and Andrea. Really, having your perspectives and your willingness to share those with our community, it really means the world to us at PTKO. And at PTKO, we do things like this all the time. We really value the insights of our community and we do everything we can to share those with our community. So we have articles, we've got videos, we've got events. We have our podcast hosted by our CEO. We really encourage everyone to come check out our stuff. And thank you, thank you all very much. And with that, I wanna say have a wonderful day and good luck. Good luck to all of you fundraisers out there. Thank you for your work.