# Nonprofit: Amplify Your Work and Mission with AI Auto-transcribed by https://aliceapp.ai on Wednesday, 18 Sep 2024. Synced media and text playback available on this page: https://aliceapp.ai/recordings/6TKXRqByASMnvGEpc4wfeis5O0Qajm1I * Words : 9,115 * Duration : 00:49:44 * Recorded on : Unknown date * Uploaded on : 2024-09-18 18:51:37 UTC * At : Unknown location * Using : Uploaded to aliceapp.ai ## Speakers: * Speaker A - 30.97% * Speaker B - 5.33% * Speaker C - 19.88% * Speaker D - 9.7% * Speaker E - 11.49% * Speaker F - 8.26% * Speaker G - 14.37% ---------------------------- Speaker A [00:00:00] Good morning. Speaker B [00:00:01] Good morning. Oh, my goodness. It's so good to see all the familiar faces in the audience today. And a warm welcome to those of you that are new with us for the first time. My name is Kim Bradbury and it is my pleasure to welcome you to our nonprofit community keynote. Now, if you recall, the last time I was on stage, it was two years ago. I was brand making new into the role, brand spanking new into the company. And can I tell you what a difference two years can make and how different it feels to be, yes, in this place with you, but more importantly, in this space with you. After having an opportunity to travel for two years into your locations to understand the work that you're doing and the missions that you drive forward, I wholeheartedly believe that everyone at some time in life needs a helping hand. And it doesn't necessarily have to be from a catastrophic event. It could be housing assistance, financial assistance, mental health counseling, family counseling. Regardless of whatever the reason is what I know to be true, regardless of race, creed, color, and financial status, none of us are exempt from this thing called life. So after almost 30 years, I decided to make a change. I chose impact and purpose, and then I chose Salesforce because Salesforce believes in paying it forward. Case in point, very early in the company, in its infancy, Salesforce decided to set up a company pledge where they pledge 1% of the company's equity, 1% of the company's time, and 1% of the company's products to higher education institutions and to non profit organizations, because they too know that every now and then, someone needs a helping hand. Listen, we know that you guys are working day in and day out in your communities to improve them and drive your missions forward. And we know that it's not without challenges, budget challenges, capacity challenges, and, oh, uh, by the way, then there are those it challenges. And that is exactly where Salesforce can come in to help with our nonprofit solutions. So here's my invitation to all of you today. Number one, relax. Speaker A [00:02:43] We got 40 minutes. Speaker B [00:02:46] Take a load off and open up, uh, your minds to the art of the possible as Salesforce shows you how we can help you take your missions to the next level. Now, before I exit, I would be remiss if I did not thank each and every single one of you for being here at Dreamforce with us this week. We know and realize that time is the one asset that none of us can get back. And we appreciate you choosing Salesforce. Now it is my pleasure to introduce you to two wonderful humans. Please help me welcome Lori Freeman and Nora Steven Kitner. Let's take it to the next level. Speaker A [00:03:32] Thank you. Speaker C [00:03:33] Kim Loride. We're here. We made it. We're finally doing the nonprofit keynote together. Speaker A [00:03:45] As we look around the room, we see so many familiar faces. And I, uh, would be lying if I didn't admit that as I sat down here this morning, I thought, this feels like a gigantic living room from the seventies, maybe the eighties, right? If you're a little off trend. So, uh, this year, something special is happening. We are streaming live worldwide, so I'm gonna ask y'all to indulge me, because Nora's mom couldn't be here today. But, you know, when you're on tv or at the Today show or something, you try to get on. You're, like, waving in the background. You try to say hi to your mom. So will you guys, can we say hi to Nora's mom? Heather, on the count of three, okay? I'm embarrassing Nora right now. Two, one. Hi, Heather. Speaker C [00:04:32] Oh, my God. Thank you for that. She is going to love that. She's going to love also the word matching outfits. Yeah, she is really going to love that. So thank you to everyone for saying hi to Heather. Speaker A [00:04:42] She really is. Heather's amazing. I love her. This is the 10th keynote that I've had the privilege to get to stand on stage and talk about the work that we do together. Nora, do you remember the first time that you presented at a keynote? Speaker D [00:04:53] I do. Speaker C [00:04:54] I was so nervous, but luckily, I had a really good support system. I had the pleasure of standing next to Heath Parks, who is a treasured member of our community. Yeah, give a hug. He's watching online. So we're going to say hi to Heath as well. And we were talking about program management in NPSP. Speaker A [00:05:13] Ah. Uh, yes. NPSP. For those folks who don't know what NPSP is, it's the nonprofit success pac, and we have been working together on NPSP for almost two decades. That's a lot of work, right? It's a lot of time. It's a lot of collaboration. Last year, we launched the nonprofit cloud, the next generation fundraising programs and outcome solution. We started talking about generative AI, too, right? There's never a dull moment here. Speaker C [00:05:37] There really isn't. I mean, the pace of innovation is just wild, right? It's almost impossible not to feel a little bit left behind. But what I've come to understand in talking with you and all of our nonprofits in the room is that AI is like having another set of hands working alongside you. Speaker A [00:05:53] Yeah, it really is. And the thing that I have always heard, we've always heard I've had the chance to work with nonprofits for two decades. I haven't met anybody yet. Uh, that says, lori, we got too many darn resources, too many people. What do we do with all this staff? Right? Yeah, no, nobody says that. We don't have enough hands. Right. So over the next 45 minutes, we want to try to break down how AI really can help your organization, help your mission, help all of your causes. Speaker C [00:06:18] Yeah, that's right. And we're actually going to do that by showing you some live examples. I myself have been a visual learner. I have to see it live. So we are going to show you two demos. We're going to show you an example of using AI for fundraising, and then we're going to show you an example of using AI for program management. Speaker A [00:06:34] There's no doubt about it that great AI comes from great data. The other thing we've always heard from all of you is that you want to hear from each other. Right? You want to hear, how are you doing this? How are you doing that? Salesforce. Thank you. But can we talk to each other? So we're really fortunate to be joined today by Fair Share UK. They're an example of an organization that's completely committed and connected and they're doing this work and they're going to share with you how they're doing it. Yeah. Speaker C [00:06:57] I'm really excited for you all to hear that story. Now, we're going to end the program with the best of the best, which is everyone in this room. We're going to end it by talking about how our nonprofit customers, our partners, our volunteers, our staff members and other people have come together and what they've been up to in the past year. Speaker A [00:07:16] Sounds good. Speaker C [00:07:16] But before we do that, we want to make sure that no one gets left behind. So we wanted to find some terms. We don't want anyone to be sitting in the audience thinking we're already talking about autonomous agents and agent force, and I don't even know the basic terminology. So we're going to start by defining some terms. Let's start with what is an LLM and what is a prompt. Speaker A [00:07:38] Yeah, I like it. Let's get real. I'm sure there are some folks out there who have no idea what an LLM is. I know I didn't not that long ago. So let's start with the words large language model. Now, when you think of LLMs, examples of LLMs are things like chat GPT Gemini, I'm guessing there's some folks in the room who are working on their own large language models. Essentially. Think of this as a gigantic group of data, structured and unstructured data. We're going to come to that later as we talk this morning. You want to be able to make agency of all that data, right? That's where prompts come in. Think of prompts essentially as, uh, instructions that you're giving that data with the intention to predict something or to generate something. Speaker C [00:08:23] Yeah, that's right. If you've played around with chat GPT the prompt is the question that you're asking, it's what you're requesting. And then the LLM is span. This is my explanation of it as a non technical person. It's spanning the world Wide Web, all the information in the world wide Web to give you that output. So let's do a quick reminder of what is predictive and what is generative. Speaker A [00:08:44] Sure. So predictive, exactly like what it sounds like. You're trying to predict things that you see in your data. You're trying to predict a result, right? That could be predicting a major donor, right? Lord knows we have lots of donors being able to identify which of those donors are going to be the highest value to your organization, who you just spend more time with. That's predictive. Speaker C [00:09:03] Yeah, that's right. And we actually have some customers who are using predictive AI today, like Team GB, which is Team Great Britain and Northern Ireland Olympic team. Can I just say that I miss watching the Olympics every day? Can that all the time. As a result of using Salesforce's AI to predict the best time to send an email, they've seen a 140% increase in contacts. Now, myself, I'm a former fundraiser, so my mind immediately goes to, ooh, think of all the donors and the prospects that could be in that list. Speaker A [00:09:36] Yeah, so that's predictive. Now, let's talk about generative, kind of the new kid on the block, which sort of makes me want to break, uh, out into a new kid on the block song. But I'd probably lose half of the room. In any case, generative, like predictive, is looking at large sets of data. The difference is it has a point of view and it's generating a starting point for us. So that point of view is what separates it from just going out on the World wide Web and doing a Google, um, search. Speaker C [00:10:05] Google, Google. You know, who knows? They're naming LLMs all the time. We're going to see an example of generative AI here in just a moment. But before we do, I did want to talk about agent force. If you were able to attend the keynote yesterday, you heard a lot about agents and Agent force. Speaker A [00:10:23] We did. We spent a lot of time talking about Agent Forest. There's pictures everywhere. A, um, person who came from the nonprofit sector into technology. When I see all the agents, all the robots, I sort of go, now what? Now? So we want to kind of break this down. So let's just start with the word agent, which relates to agency. And as I've thought about AI, as I've thought about data, I'm pretty passionate about talking about data strategy. Think about agent force as giving your data agency. This is a new term for us to talk about these things. But the idea of being able to automate things, the idea of being able to give technology to the folks that are on your teams to be more effective and focus on the things that are the highest need for a human. That's Agent force. Speaker C [00:11:10] Yeah, that's right. That agency term, ever since you said that, it just kind of clicked with me. It's made me a little bit less scared of Agent force, if I'm being honest, and I work here. So we're not going to dive into agent force, but please stay tuned as we start to develop and our solutions for nonprofit. But we're going to spend the next couple minutes diving into some examples. Speaker A [00:11:33] Let's do it. Speaker C [00:11:34] Yeah. So we're going to give you two examples, and we're going to. They're all live and real, but they're within the context of a fictitious organization called Steps. Now, let's pretend that Steps is a nonprofit organization that works with program participants or clients. Now, Lori is going to play our fundraiser, and I'm going to switch it up and play a member of our program staff. And I'd also like to introduce you to our third colleague, Serkan. He's behind the scenes running our amazing demo and responsible for all the amazingness we're going to see today. And then you also may notice something that may look a little bit different. The screens may look a little bit different if you're currently using Salesforce. And that's because they're in our new user interface, which is called lightning enhanced. And that's going to be available next year, which is pretty cool. So over to our fundraising department. Over to you, Laurie. Speaker A [00:12:27] Okay, let's get a sense of who's in the room. How many folks do we have in the room that are major gifts? Officers? Anybody? Show of hands? Okay, a few hands go up. Hopefully some of those major gifts officers are at home raising their hands. For those folks who don't know, the role as a major gift officer is to be able to look across all of your donors and identify the most high potential donors that you should spend more time with. The difference in focusing on 400 versus focusing on 40 or four. Right. So Einstein can help with this. So what you see here is a list of all of the major donor prospects that are in my portfolio. We have a lot of information about these prospects. If you look over there on the far right hand side, I think, yeah, for everybody in the room, I'm just getting used to this living room situation. What you see is the Einstein score. And what the Einstein score is doing is looking at all of the information that's in nonprofit cloud. As you would expect, the higher the score, the higher the likelihood that individual is to become a major donor for your organization. So I'm going to sort, and I see here that I should be spending a little bit more time with this Alex Garcia fella or individual. So, all right, now I'm taking a deeper look at the donor, and there's a lot of great information, but I want to be able to get a quick take on what our organization has done with this individual. I want to be able to take action because I want to prepare for an upcoming meeting. Einstein has prepared a major donor summary for me. This helps me really quickly get a handle on what our interactions have been like with this potential donor, which is great because I want to have a meeting with them. So let's pretend I have a fantastic meeting. I had all the information that I needed. Fast forward, we have a gala. Do you say gala or gala? Speaker C [00:14:04] I honestly still never know. Speaker A [00:14:06] I have that. Uh, where am I, how am I supposed to say it? Do I say it differently in Alabama than I say it in Washington? Anyways, we're getting ready to have an event, so I want Einstein to help me create a major donor proposal. So what this is doing is helping me with the starting point with all that rich information that we have about this individual donor. Really great first start, but I ultimately have the control to decide how I want to augment or change that information. So, looks pretty good, but I want to add in a little bit of personal information. Serkan, so can you help me out with putting a little bit of information in there about Alex's daughter's upcoming soccer game? Looks good to go. I'm going to hit send. Awesome. Speaker C [00:14:46] Um, now I'm going to pause this because I need to talk about, firstly, my jealousy, because as a former fundraiser, I think about if I had that in my organization, how much time I could have saved, how much more dev. Speaker E [00:14:59] Funds we could have raised. Speaker C [00:15:00] It would have been awesome. Anyway, moving on. I'll save that for therapy now. Also, when we were preparing for this presentation, the question that I would ask you a bunch is, why would you need Salesforce for this? Why wouldn't you just use a generic LLM? Speaker F [00:15:15] Um. Speaker C [00:15:16] Right. Speaker A [00:15:16] It's the right question. I'm sure if I asked everybody to raise their hand of who's going out and taking personal or private information from your CRM and putting it in a generic LLM, we'd see some hands go up, and we'd see a lot of hands go, wait, I didn't shut. Is people in my organization doing that? So when you put information into a generic LLM, that information gets fed back into the model. Right. So, first of all, that information is now not really secure. Second of all, if you're going out and using those tools and just getting a generic starting point, you actually miss out on all this context that you have in the nonprofit cloud. So all those individuals that are interacting with those donors, that, uh, context is lost. So you're way less relevant. You're way less personalized. Speaker C [00:15:56] Yeah. So the LLM, in order to give you the best response, needs the context of your CRM data. Speaker A [00:16:02] Exactly. Speaker C [00:16:02] How are we making sure, though, that the information that you're putting in isn't being made available to just anyone? Speaker A [00:16:08] Right. And this is the right question where we need to focus. We have what's called the Einstein trust layer. So, as you enter information into nonprofit cloud, the information that you're putting in there comes with your security information. It's never leaving your system, and that's critically important. Right. So you can have all the relevant personalization. You can solve that blank page problem and never lose the priority of security. Nora? Speaker C [00:16:32] Yeah, that's pretty powerful. I mean, this can look like a lot, right? Like, I've seen this slide a million times. It can look like a lot. But basically what Lori is saying is that the data that you put into your system, that you put into Einstein trust layer remains your data. Your data is not our data. Speaker A [00:16:50] That's exactly right. And that's how it should be. Right? Yeah. I think it's time to put Nora on the hot seat. Right. That was major giving, but I have a pretty passionate soft spot for programs. So why don't you give us a demo program? Speaker C [00:17:01] All right, fine. I'll hop in. I'm excited to play the program role. I'm gonna play a bit of a dual role today. I'm gonna play the program manager, but I'm also gonna play a case manager that works with a caseload of clients. And we all know that everyone in this room in the nonprofit sector is, is overworked, overwhelmed. You're resource strapped, capacity strapped. But let's see what could happen if you had Einstein working alongside you as another set of hands. So let's pretend I'm a case manager. I go into, um, my office, I sit down in the morning, and I log into Salesforce, and immediately on the left hand side, I see a client who is being alerted to me that is at risk of dropping out of the program. Speaker A [00:17:40] This is a great example, actually, of predictive, right. It's looking at the data in your organization that your organization has, and it knows that other individuals have dropped out of programs. It sees these signals. You don't have to go look and see who's going to drop out. Einstein's actually letting you know, hey, this person's at risk. Do something. Take action. Speaker C [00:17:59] Yeah, and this is really helpful, too, because I think the ideal goal is to know each client on an individual basis. But in reality, that's really hard if you have a large caseload. So let's say I want to reengage with this client. I'm going to turn to Einstein again, which is going to help me identify the best case plan or action plan for this client. Now, I may know this information already, maybe, but maybe I'm new to this program, or I'm new to this client, or I'm at my mental capacity. It's the end of the day. I can't think anymore. I'm going to rely on technology to help me identify the best course of action that has been proven to help other clients like mine in the past. So Einstein suggests a case plan. And just as we saw in the fundraising example, this is just a draft. I can edit this as I see fit. If the case plan is completely off for some reason, I can pick a new one. I'm the case manager. I know best, and I'm going to remain in the driver's seat. But this plan looks good, so I'm going to go ahead and assign it to the client. Now, I'm not the only case manager that works with this client, and I want to make sure my whole team stays up to date and in the loop. So right from this screen, I can post an update to Slack, which is our collaboration tool. Now there's no copy and pasting it just immediately gets posted. Now my whole team can come together and surround this client with the whole person care that she deserves. That is the power of Salesforce and slack together. Now, I meet with this client a little bit later on in the week, and while I was just looking at their information, I want to make sure I'm not missing any important details. I'm going to turn to Einstein again. Einstein is going to summarize all of the case plans and, excuse me, all the case notes and all the phone calls, all the engagements that we've had with this client. Think about the time saving here. I don't have to sift through pages of information. I don't have to meet one on one with the case managers or have a meeting just about this one client. Einstein does this for me in a really readable format, calling out those high important details. Speaker A [00:20:02] Nora Stevens Kitten or Bader Ginsburg, I have to interrupt you. Speaker C [00:20:06] I knew you were going to have that. Speaker A [00:20:10] Okay, I'm going to dork out for a second here because there's this concept that I'm not sure all of us really have at our disposal, and it's such a critically important concept, and it's the difference between structured data and unstructured data. Unstructured data is what a case note is, your free text, typing in information. Think about how many things we just type on our own Google Doc, our own word doc. We write out that data has been out of reach for the organizations that we've worked with for too long, right? And we have so much turnover in our sector, so that information leaves with the person. Other examples of unstructured data, videos, audio, pictures. When you really start to let your mind the wheels start to turn. We think a lot about using structured data in our decision making. Those are things that you pick from a pick list or maybe you, uh, check a box with the AI tools that we have. It combines structured data and unstructured data. I beg Nora to let me do an entire session on structured and unstructured data. She said no, which is probably the right call. But just start to think about all of the data in your organization and start thinking about all of your interactions, because that's data too. Think about the agency of having, or think about having agency across all that data. Nora, it's frickin transforming. Speaker C [00:21:27] I know it is pretty powerful when you think about the PDF's or the donation receipts or the pictures of checks that the fact that Einstein and AI can take that information in and still digest it. Uh, I'll admit it, it's pretty powerful. Speaker A [00:21:38] Gotcha. Speaker C [00:21:39] Yeah. Okay, let's hop back to our fundraiser. Uh, excuse me, our programs example pretty quickly. So we all know how long it takes to put program reports together, right? At my old organization that I was at, if we had a board meeting coming up, we would start on this project weeks in advance. Speaker A [00:21:55] Months. You clear the weekend, right? Yeah, we've all had those times where you're like, I have to get up early. The weekend, it's gone. Exactly. Everybody rallies around it. Speaker C [00:22:01] It takes a lot of time. So Einstein is going to help me by summarizing the programs and helping me understand how we're tracking towards those outcomes. And you'll see in this summary when Einstein brings it up, you'll see that as a result of this program, we see a 10% increase in women hired in tech. Now, I know that this is just a fake example. There's two women in tech. I would say that that's pretty cool. Speaker A [00:22:25] Good. Speaker D [00:22:25] It's good, yeah. Speaker A [00:22:26] It's structured and unstructured data. Speaker C [00:22:27] Of course it is. Speaker F [00:22:29] Okay. Speaker A [00:22:30] We've gone over a lot of concepts and we've actually gone pretty fast. All right, so let's just take a hot minute here. Our intention was to give everybody a shared understanding of some of these concepts that work across our technology. But we also want to leave you with an understanding of what you saw today. First and foremost, we saw nonprofit cloud, the next generation, fundraising outcomes, grants and programs. But you also saw slack. And I want to say right here, if you're thinking about Slack as a messaging tool, go check out a demo. Go have conversations with. It's so much more than that, right? It's collaboration in the flow of work. You also saw Einstein all over the place and the Einstein trust layer woven directly in. But I want to leave you with my favorite part of what you saw, and that's the commitment that we have to industry specific, purpose built AI. We are working directly with the organizations that are in this room and online to understand what are the things that are going to drive you forward fastest that are going to help you the most. Those features that you saw today are going to be available in beta in October. This in October? That's like two weeks from now. Speaker C [00:23:33] I know. It's very soon. I can't believe it. By the way, I still have to do my new year's resolution. Um, so also, we haven't forgotten about our grant makers. Also, beta in October is AI functionality in nonprofit cloud for grant making, which is pretty cool. Speaker A [00:23:47] Very cool. Very cool. Speaker C [00:23:48] Yeah. Speaker A [00:23:48] All right, so I'm guessing folks are feeling a wide range of emotions and thoughts. Maybe some folks are like, oh, that's really cool. Where do I get that? Maybe you're going, how'd they do that? Maybe you're going, Lori, my organization is just trying to get off of spreadsheets. We're going to meet you where you're at to, but I want to leave you with, you have to have conversations about good data in your organization, across the entire organization. So we're going to take a bit of a transition here and work with an organization who's actually done this. They're connected, they're committed, they're aligned. They're working to use their data. They have a data strategy that's committed. So please join me in welcoming to the stage Chris Gibbon Walsh, COO fair Share UK, and Susan Mahan, one of my all time favorite humans. Take it away, folks. Speaker F [00:24:42] Thank you so much, Laurie. And a huge thank you to you, Chris. You have traveled all the way from England to be with us at this dreamforce. So we're very honoured. I'm particularly honored because between the two of us, we're going to bring a little bit of the european to this morning's session. Speaker G [00:24:59] Thank you so much. And it's great to be here with so many amazing heroes in a room from all over the world. So, really looking forward to it. Speaker F [00:25:05] Great. Thank you. So we literally are surrounded by people, all representing their organizations, representing their cause areas, everyone here doing hard work just to try and make the world that little bit better. Now, I know that fair share is one such organization with the work that you're doing helping to alleviate food insecurity across the United Kingdom, but your mission isn't quite as simple or straightforward as that. Tell us more. Speaker G [00:25:30] Yeah. So use your imagination for a second. And on the way here, you flew, you drove, you passed all of those fields, crops full of maize and cabbages and tomatoes. All of the work and the effort and the land and the water and the nutrients and the love that went into growing those crops. And yet globally, 40% of all food that is grown is wasted. 40%. And in the UK, one in six people are in household food insecurity. 30 million people. So, uh, it would be easy to think. Right, okay, well, we've got some surplus foods, we've got some hungry people. We'll just put those two things together. It's not as simple as that. And actually, food can do so much more. The power of food to convene, to connect people, to solve problems is ubiquitous. And so what fair share does is we work with thousand food industry partners, um, amazing organizations who, uh. And we get their food, and we move it with hundreds of trucks and lorries to 35 warehouses that then goes to eight and a half thousand charities and reaches a million people. Wow. A million people. Speaker F [00:26:49] That's your supply chain right there? Speaker G [00:26:50] Absolutely. Speaker F [00:26:51] Right there. Speaker G [00:26:52] Absolutely. But I think what's really important is each of those organizations does so much more than just give food out. They are strengthening communities and bringing people together around food. And that convening power is awesome. And an example of that is a small charity in south London where I volunteer, actually. They have cues out the talks. The food is delicious. The chefs there are amazing. But actually, when people are there, maybe they have the only hot meal that day, that week. Okay. But maybe they have the only conversation, ah. You know, maybe they get out of addiction or debt or housing crisis, and all of those things around food enable them to lift up and strengthen. And that's amazing for us. Speaker F [00:27:39] That's the power of people connecting. Speaker G [00:27:41] Exactly. And there's a million of those stories. Literally. Speaker D [00:27:44] Yeah. I love it. Speaker F [00:27:45] What size of organization are you, Chris? Speaker G [00:27:47] We're only 230 people, and so we're really relying on brilliant technology to be able to scale, and that's really important and why we're here. Speaker F [00:27:54] Wow. So suffice it to say that you all have your hands full there at fair share, doing this work that you're committed to doing. Now, when I think about a transformation project, be that digital or otherwise, I think time consuming, I think complex, I think costly. What made you all take that on? Speaker G [00:28:12] So the question is relatively straightforward, which is, we need more money to continue to do what we're doing. M so, we talked about a million people, but actually, there's, uh, 30 million people in household food insecurity. We've got thousands of charities on waiting lists ready to get more food, and we need more money to keep up. Secondary to that, between Covid and now, we went from a 3 million pound turnover organization. We're likely to do 27 million this year, and the foundations aren't quite there, so we're using 40 different systems, loads of spreadsheets. The fundraisers were tearing their hair out, and so they really needed to consolidate all of that data into one place. And then, um, with that consolidation, I think what's really important is the professionalization of the fundraising department has now allowed us to hire some of the brightest and best fundraisers in the country. Because they want to come and use the top systems to be part of the development of the next stage. And that's really, really and fundamental and important to us. Speaker F [00:29:11] Yeah, that makes a whole lot of sense to me. And so when I think about now m the products that you're using, I'd love to hear what's enabling all of this, what's helping you to take advantage of opportunities and to address difficulties. Speaker G [00:29:24] Yeah, I mean, we had some choices, but I think nonprofit cloud make total sense to be fit for the next ten years, not just the here and now. So we drove straight into the new product, and that's worked for us. Datacloud has enabled us to bring all of our data together from all over the place. We were having 40 different systems and spreadsheets, really manual processes. The fundraisers weren't actually enjoying their jobs a lot of the time. Uh, now they're able to utilize salesforce properly. And the last part of that is marketing cloud, which has allowed us to build journeys. We've got two at the moment to really segment and target funders so that we can give them a brilliant, engaged, um, service. And then lastly, and I think this is important, that fin doc, we've uh, moved over to do our payments, and that's working really well as well. So that combination of products is working great for us. Speaker F [00:30:14] Okay, love that. And so when I think about, I know that this is not all about fundraising. I've heard you say that you have a lot of ground that you want to cover and you're laying those foundations in place. So what's the vision and what's the significance of realizing that vision? Speaker G [00:30:32] Yeah, I mean, I, uh, started with fundraising because every organization in this room knows that you can't do anything without the money. Right. But actually we get the money to deliver more mission. That's what this is all about. So we started there, but actually we want to give our, uh, 26,000 volunteers a better experience. We want to engage them and make sure that they get a brilliant day to day experience in a targeted way. We work with a thousand food partners, but actually 100 of them we really target in. So we think about how do we deal with the food, their fundraising, their marketing, their corporate engagement, their C suite engagement and all of that. At the moment, the account directors are trying to do that with spreadsheets and really manual work. Exactly. So actually being able to bring that over to nonprofit cloud will really help them. And they're all really, really eager. And then lastly, um, and this is the magic, right? This is where it's really going to come to life is that really knowing the eight and a half thousand charities, who they are, where they are, the services they provide, and the outcomes that they deliver, will help us tell those stories and that impact back to the food industry and the funders, which gets us more supply, which enables us to do more. And the whole cycle starts, and that's the power that we're trying to elevate. Speaker F [00:31:46] Yeah, full circle. I love that. Okay, so, advice, uh, time. I've heard it said that change is difficult at the beginning, messy in the middle, and gorgeous at the end. Now, I have no doubt that you've experienced all three of those, but let's look at where you are right now. Give us a little bit of advice in regards to why your project has been so successful. Speaker G [00:32:07] Yeah, I think what I'd start with is the business was ready. The fundraising team were like, me, me, me, me, me, me. They were absolutely wanting and ready to use a, uh, CRM and consolidate all that data. So, uh, the change program was already kicked off in the right way. The second thing I'd say is, get a really good project manager, someone who knows what they're doing and understands the organization. Give them the time and the resources to really focus on delivering a project. Fewer things better is the mantra that we have in the organization. And I think that's really important. Speaker F [00:32:40] Yeah. Speaker G [00:32:41] On that basis, therefore, is, I think, get your governance right. I was sitting on your weekly governance, as were the, uh, finance director, uh, and a fundraising director. And what that meant was we were able to just solve things really quickly. Oh, we've got slightly over on this. Fine, do it. Like, we were able to move at real pace because the decision makers were all part of the process. And also, it meant that we weren't delegating responsibility and accountability. We were all holding it together. We had really clear, uh, KPI's and objectives. We didn't deviate. We were really clear we want more money. But we knew what ladded up to that, and we were really clear on what we were trying to do. And lastly, I think this is fundamental. Choose your partners really carefully. So we went through a process and a tender of choosing our, uh, implementation partner, which is solution junkies who are here, who were absolutely unbelievable, and I can't speak highly enough of them, but also, signature success helped us to backstop some of the kind of bugs that we might have. Um, and, um, we were able to bring it all in as one team and run it as one team, rather than lots of separate, different partnerships. Speaker F [00:33:46] Love that. So there's a lot of really, really good guidance in there for all of us, I think, in the room. Now, before we switch to demo mode, which we will in just a split second, I would like to take the opportunity to thank you and all of your colleagues at fair Share for joining us and for offering us great advice and for all of the amazing work that you're doing. Speaker G [00:34:04] Thank you. Speaker F [00:34:05] Thank you, Chris. So now it's time to bring all of this to life and let you see some of what fair share are doing today, some of what's going to be possible tomorrow. And there is no better person in this room to do that than my colleague, Andrea Schiller. Speaker E [00:34:28] Thank you so much, Chris and Susan. Before we jump in, I want to give a big dreamforce thank you to joy Renner and Melissa McArthur for the incredible demos that we're going to see. They built these and these are all going to be live. So as Chris mentioned, fair share has 40 different data sources that they're working from, which leads to a complex view of their organization. It's fragmented, unfortunately, and they weren't able to get a clear understanding of who their supporters were. For example, you can see here a donor and supporter profile. Now, in this profile, we're going to see location, we're going to see email, phone number and birth date, and that information is great to have, but in order to make a real connection, they're going to need more. But connecting those 40 systems is extremely complex and time consuming. Now, luckily, Salesforce was able to help, so fair share was able to use out of the box connectors in data cloud as well as Mulesoft to connect these systems. So they connected marketing cloud, nonprofit cloud, their website and various spreadsheets. From there, Datacloud was able to harmonize the data and what that means is it was able to look across those 40 different systems and identify information about, about specific supporters and attribute it to the right person overall. And what they get and what they got overall was a unified profile. So as you can see here on the left, we have all that great information from the first profile, plus richer information like RFM score and propensity to donate. Now, having that information is really great to have, but it's what you do with it that matters. So let's actually act on some data. So the fair share fundraising and marketing teams are able to start their day in a tableau pulse dashboard. On the right here, you're gonna see that there's been a drop in donations and they need to take action. So the marketing team is going to start building out a new donor campaign. So this new donor campaign will have waterfall, uh, segmentation built out. We'll make sure that we're bringing in the right attributes to make sure the right people are included and we're making the right ask amounts overall. Or you can even add in source codes to make sure that we're able to track direct mail, email and text. Now we can activate these segments in marketing cloud or through a direct mail provider. So we're actually going to take action in marketing cloud. So as you can see here, there's a fantastic journey that's been built. We have email, we have text messages and what's really cool is that we're going to be able to bring Einstein in as well. So Einstein is going to be able to help us predict the right time to actually go in and send these communications. Now, what type of communications are these potential donors going to get? Well, we can bring in marketing cloud Einstein to help here as well to actually write in the copy. So fair Share is going to write an email focused on highlighting a new program and talking about the impact that donors can have. From here we're going to see a variety of different text options that they can select from and we'll pick the one that's going to resonate the most. So we select, we send the email and we start to see some engagement which we love to see. So if you look here, there's a potential donor that has a high propensity to donate. We want to reach out and want to make sure that we are looking at the marketing and activity consent information in the middle here to ensure that we're actually engaging in the way that she wants to be engaged with. So we are then going to put this potential donor on a recurring donor solicitation action plan. We'll have a list here that we sent to the development team making sure that they're able to reach out again in the way that the potential donor wants to be engaged with. After some back and forth, lucky for us, the recurring donation comes in and we are able to track it again right within Salesforce. So we'll look at the gift commitment, we'll able to track the upcoming gift transactions. We are good to go. Now, this recurring donation plus all the other donations that fair share is going to be getting will help fuel and fund the amazing programs that Chris talked about. So as mentioned, fair share works with one, uh, thousand food organizations, 8500 charities and 35 warehouses. So managing that information is going to get complex very, very quickly. Salesforce is going to help here by tracking this information in on profit cloud in the future for fair share and a program manager is going to be able to go in, add in a new food program partner. You're going to see basic information here about who this partner is on the right side. You'll see some back and forth communications around what's been discussed. Then you're also going to see key information like benefits, outcome activities and indicators overall. And it's great to track this information. But as uh, Chris mentioned, the real magic happens. You're able to go back to those partners and really show what the outcomes and impact are overall. So outcomes and impact like fewer meals, uh, um, skipping fewer meals, reducing food waste, improving health overall. These are all really, really impactful information that needs to go back to partners and it really ties back to that full life cycle that we were talking about earlier where you're able to connect with the supporter, have a donation come in, have that donation fund the actual program, and then go back to those donors and those partners and really talk about how the dollars and donations that they've given are making an impact and helping overall. So we're very thrilled to see what fair share is building. Cannot wait for the future. And with that, I will pass back to Suez. Susan. Speaker F [00:40:19] Thank you so much. Andrea. So let's do a really quick recap of what we just saw. We started off with our marketers and our fundraisers checking out their KPI's using tableau. Then we had data cloud and Mulesoft coming together to create those unified profiles by harmonizing our data. And then we used our marketing cloud to help us to deliver supporter journeys that are personalized across many channels, including sms and email. Bring in our nonprofit cloud for fundraisers to help us identify those donors that we focus on for that cultivation process. And then with outcome management in nonprofit cloud, we're able to evaluate the performance of our programs and we're able to share that out with our supporters and our wider stakeholder groups. All of this is available to you right now, today. And then for those actionable insights built right inside of nonprofit cloud, we're bringing you tableau Einstein for fundraising. And that's coming to you in October. So lots of goodness and watch out for all of that. Seeing what other nonprofit organizations are doing via these demos is really part of the Dreamforce magic. Another part of that M Magic is the coming together of mission focused change, making people all a part of the nonprofit community and to take us through the nonprofit community and tell us more about how we can really leverage that as a resource and a network. I'm going to invite another wonderful colleague to the stage, Cory O'Brien. Speaker D [00:41:53] All right, thank you, Susan. Oh, my gosh. Hi, everyone. Um, for those of you that I don't know yet, I have the best at Salesforce because I get to lead our nonprofit community team. So let me shake out those nerves for a sec because today is my very first time on stage at Dreamforce, and I'm glad that I see some familiar faces here because you all have to laugh at my jokes. Okay? Yeah. Speaker A [00:42:24] Okay, good. Speaker D [00:42:25] Well, let's get started because I am so excited to be up here to shine a light on the most important part of Salesforce, all of, uh, you. So if you're new to Salesforce, the nonprofit trailblazer community is a global network that includes our nonprofit customers, our partners, and our employees. But we know it's so much more than that, right? Yeah. Um, as a community, for 20 years, we've been coming together to build resources and tools that help each other use Salesforce more effectively. Just makes it easier for us. Literally thousands of people just like you in the room today have volunteered their time and even built our, uh, first set of nonprofit products. Some of you probably remember those. So while all of you watching here from home and in the room are already a part of the community, I want you to leave today knowing how to get more involved. There's actually a lot of different ways that you can get involved, both online and in person. So we've got the trailblazer community portal, which is our online community, where over 50,000 of you are already engaging in nonprofit groups and answering each other's questions. There's also local nonprofit user groups all over the world. We do monthly. Ask me any things. And there's even a, uh, community led Slack workspace called Ohana Slacken. And we have the open source Commons program, which. Speaker E [00:44:01] Right. Speaker D [00:44:02] It's also my very favorite part of this community. The Commons is all about community led innovation on the Salesforce platform to solve common challenges. And the most popular way that we do that is a community sprint. So a sprint is sort of like a hackathon where you and your nonprofit peers, our partners, and our employees, we all get together, we identify common challenges, but then we build and share solutions, like apps you can install and recipes that you can follow. In fact, there is a group right now. Dar's probably here somewhere. Haley. I saw her earlier. Who's building a best practice guide for the new nonprofit cloud for you. And then there's another who are building a data kit so that those that are still using the nonprofit success pack can explore using data cloud. So if you're never sprinting before, if you've never joined us, um, I just want you to know that we love welcoming new people. Right? A lot of new people, yes. And if you've never sprinted before, it's such a fantastic experience. Everyone can contribute. Some of you right now are probably sitting here thinking, cory, that sounds great, but a, uh, sprint's not for me. I'm not very technical, or no one will think my idea is very good. And I get that because I felt the same way when I went to my first sprint in 2015, if you can believe it, the first one. But everyone can contribute. I just want you to know that it's not about your title, it's about. Speaker F [00:45:41] How you show up. Speaker D [00:45:44] Community ideas need a diverse set of skills and perspectives, and that's why we need your feedback and for you to contribute. Plus, look how much fun we have. You see these pictures here? We even have a community mascot who's a t. Rex named Sprintie. Right, right. So Sprintie. And, uh, I would actually love it if you would come to one of our upcoming events. And you're actually in luck because we're hosting three this fall. We have one next week, actually a virtual sprint, and then we'll be in the UK, in Newcastle up north, um, for our second event focused on affordable housing solutions. That's the 7th and 8 October, and then we're going to back to Chicago November 13 and 14th. So if you can't make one of these events, I just want you to find another way to start connecting. I have been an admin for 14 years, and honestly, in nonprofit tech longer than I'll admit while I'm on camera. And it's such an incredible experience. The community is here for you. We've always been there for each other and it's just what we do. It's why we do this work. As a community, we are always there for each other. And I know that that support is going to continue through whatever comes next. Speaker C [00:47:10] Right. Speaker D [00:47:10] Like I said, it's just what we do. So I hope that you'll be able to join us at an upcoming sprint. And thank you so, so much. Um, thank you very much for being a part of this community and I hope to meet you all. And just going to pass off back to Lori, who is one of our biggest community champions, uh, for one last special announcement. Thank you. Speaker A [00:47:34] That was really good for a first time on a Dreamforce stage, I'm feeling all the feels. We saved a really big announcement for the inn, and I'm so glad we got in on time, ladies, to be able to do that. Okay, everyone in this room has volunteered. Every organization in this room. Um, every organization. Online volunteers are the lifeblood of the work that we do. That's why I am incredibly excited to announce our intention to build volunteer management for nonprofits in nonprofit cloud. I'm not going to, uh, lie. This is incredibly early days, folks, but we want to share this information with you because we want you to be involved in this process. I'm sure you have lots of questions for those folks who have questions, we have two roadmap sessions this week, and my team is all setting up here. I'm sure they can't wait to see you in those roadmap sessions. Come check one of those sessions out. We'll be talking a little bit about volunteer management. We'll be talking about all the other innovations. So check one of those out if you can't make one of those sessions. There's so much other fun that's happening at Dreamforce. If you're sitting in this room thinking, how do I go back and create that data culture in my organization? We've got the session for you. If you're thinking, Lori, I'm an NPSP customer. My team, my organization, we've invested a lot in NPSP. How do we get to nonprofit cloud? We've got the session for you, too. Finally, if you haven't been to the nonprofit campground, go check it out. We're doing demos. We're having a reunion. Everybody's reconnecting. So now all that's left for me to do, other than thank you, is to ask you to fill out a survey. We really want to get your feedback. There's something in it for you, too. You get $5 at Starbucks. And as I've been joking with the team all weekend, so you have to fill out two surveys to get a cup of coffee, so at least I do. Mine's like $8.47. Anyways, please fill out a survey for us. We want to hear from you. We want to be able to take back with our internal teams that work so hard on Dreamforce and share what nonprofits need from us. So fill out the survey. Thank you. Thank you, thank you, thank you. Let's have a great Dreamforce 2024.