 Alright, thank you so much for joining us today. We're really excited to bring you this really robust discussion. I see some new faces. Just so you're aware Parsons TKO we do these monthly webinars and panel discussions to just be able to bring you some resources to help your organizations and your teams thrive. Today we are really honored to be partnering with our friends over at media cause who do similar work to us. We have a lot of synergies and comments so let me just introduce everybody who's going to be joining our panel discussion today. From our team we have Stefan bird Krueger our chief analytics officer. He manages all of our data strategy projects. We were planning to have Nate with us today but unfortunately he's not able to make it. In the media cause team we have Luke their senior more tech director. We have Dan, the senior director of fundraising, and we are really excited to have them join us today. And so let's go ahead and get started. First to stuff in. We're going to be talking about breaking down silos in your organizations how to realign messaging strategy data and people governance work through the marketing projects that your team takes on, I think. Nate is actually going to be joining us after all sorry we had some technical issues there. Let me backtrack a little bit and introduce him. He is our the chief officer who manages our technology projects. So gosh sorry about that. We had a little bit of a technical snafu there. But we're excited to have Nate join us today. So, to Nate actually, why does engagement matter and how do we focus on it if you'd like to share your thoughts. Sure. Sure. So engagement matters because, you know for every dollar we spend on outreach, we spend pennies on following up and building better relationships with people that we've met for the first time. So engagement is the way that we actually develop that connection with those audiences build affinity and make those audiences that we've reached more valuable and more successful for the organization in terms of advancing their mission. And so engagement is really important to maximize the value of all of your outreach efforts. Thank you that's awesome. And you know we have a lot of qualified members here in the panel so anybody else would like to jump in and share their two cents we'd really appreciate it. Yeah, just sort of what's helpful for me. And I'll probably be saying these phrases a lot throughout the conversation today but I like to think of fundraising really is more about having a conversation with a person. So engagement as it relates to that is really, that's the crux to me of fundraising really it's about having a conversation if we were to step back and think about what is a good what is a conversation in our own lives it's not just a dialogue. It's not just a monologue it is a dialogue right so so that and I think a big part of engagement we try and work with our clients is a lot of listening and a lot of sort of giving up a lot of giving up opportunities to have your audiences share what they think and engage with you in a two kind of dialogue way so that's kind of how I think it's helpful like I say to think of fundraising and generally sort of broadening audiences on whichever channel that you are reaching them on by as having a conversation. It helps to simplify sort of the strategy around it and in your thoughts, going into how you might pursue a particular subset of an audience, alongside of what your goals are for that audience. I wanted to elbow in there as well you know I think this concept of engagement is particularly important in the mission driven sector. You know you think about a lot of marketing tools you think about, you know a lot of analytics the technologies that have been developed to help manage communications and outreach. They, a lot of them were developed in the for profit sector, you know they were all developed a lot of these principles were designed with the bottom line in mind. But the bottom line for nonprofit organizations is some definition of mission some definition of impact, and engagement is the road to that impact that's how we fulfill our missions in the mission driven sector is by focusing on engagement so figuring out how do you identify that you know how do you isolate discrete elements different definitions of engagement. That is that's how we operationalize our strategies and nonprofit foundation, you know, wherever in the sector you said it's the it's the crux of it. No I appreciate that it's interesting to think that the concepts are from the for profit space but in the nonprofit space engagement can mean something very different so what does media causes golden rule when it comes to technology partners. Yeah, so it's something we think a lot about a media cause is you know what makes for a good technology partner. And in all of our experience, the platforms that we find most success with our platforms that are well connected. What do I mean by that I mean that their platforms that aren't sort of you know walled gardens where you use the tech on that platform that's provided and nothing else. The platforms that are I'd say more modern in their approach that are well integrated where there are more possibilities, you know that's not to say that you know everything is available out of the box but that they are platforms with possibilities be it in first party integrations that are offered or just support for middleware like Zapier so that you know you can connect them to other tools in your tech stack. That for us is so crucial because every one of our clients every nonprofit we work with has a different set of technology. And it's important to be able to use what you have right and not necessarily change because it's not working out for you because you don't always have the budget to do that and because oftentimes, you know, selecting a piece of technology is a major decision and you might be locked into a contract for a number of years. So, while we do say we are sort of platform agnostic where we work with whatever technology. Our clients have, we do oftentimes try to guide them to what we call our preferred solutions which are platforms that just have a lot of potential to work well together that oftentimes might do one thing really really well might be what you call best in breed. But that also at the same time can speak the same language as other platforms and we really enjoy sort of weaving a web of tools that are sort of purpose built and well integrated for a particular organization. So really interesting perspective does anybody else want to add to that. I think that that's a really good point is because I think there are a lot of options in terms of what your outreach technology stack looks like. And, you know, probably the most important thing for any organization isn't the technology that they pick but it's the way that they sort of understanding their audience and having data, you know, that can help them optimize their outreach and improve the way that they interact with that audience and, you know, the tools you pick can make that a lot easier or a lot more difficult. And I think that's, you know, just a really important point you know that when you're thinking about technology, you know, there's a lot of, you know, the old school wisdom is to go with like sort of best in class right where I think for most organizations best fit is a much better choice and you know they're simple things like you're going to pick a CRM system seeing what integrations the CRM system has professionally supported by organizations that have already built like a strong data connection or data bridge to another system might be just as important as some of the onboard features of that and that's often overlooked when people are doing technology selection or technology planning. Interesting things for that guys. I'm going to tap in just real quick as well, you know, you know, prior to this Luke and I were talking about, you know, when you think about data when you think about these systems. How people use them is as important as what the systems themselves do. So I think that question of, of adoption is it is it best and fit for your needs your engagement goals. It's also best fit for your staff. You know, is it a tool that your staff have experience with is it a tool that your staff know how to use and will be successful with. And so I think that's another really important aspect when when judging and evaluating these platforms. And one last thing I'll say here is, you know, it's easy to get shiny objects syndrome, right, you know where you might think that a certain platform is the bane of your existence and it may be. And you may think that just changing a platform is going to solve all your problems and that might not always be the case it might mean that you need to use the platforms you have already in a better way. And that's something that you have not heard of in the feature set of that platform to better connect it so we always, you know, take the approach of being pragmatic and working with the tech you already have and, and, you know, I think that's further kind of tech that we will recommend as well. But, you know, it all starts from a place of like, you know, a discovery process to learn really what what is important for you. But I mean, I guess one more thing I would just say here too is, you know, for anyone who's listening in here is you know if you are you know right now thinking about like your tech or thinking about a platform decision. Keep in mind that, you know, it's not something that, you know, is going to happen overnight, you know, allow a little bit more time, you know, to Nate's point I mean it's a selection process. So, you know, we have our favorites. But of course, you know you want to go through a process of sort of like interviewing the technology that you might work with in the same way you might interview somebody for a role in your team, really is like your employee in a sense is like a major technology platform you use and just because you know the website for that platform might look nice and flashy doesn't always mean that the platform itself is also that flashy. So, demo conversations are really important there. And that's certainly where we like to help as well as like, you know, get under the hood, you know, and platforms that don't allow you to easily do that like get under the hood have like a demo sandbox account as they call it. If you're not able to sort of kick the tires. That's usually a sign that something a high, you know, or that it's it's not the most open and up to date platform out there. Flash does not equal functionality. I think that's that's right. 100% I think we've all been fallen victim to this shiny object syndrome in the past so I appreciate the focus on discovery and revisiting functionality seeing how you can make something work for your organization rather than just throwing everything out. So I think Stefan you'd be probably the best person to answer this question what are the most important principles of contact modeling and if you want to explain a little bit about what contact modeling actually is for those who might not know. Absolutely. When we say contact modeling, we are thinking about the way your organization understands your audiences. So when you think about the people who you're reaching out to you think about the types of relationships that you have types of engagements that you're trying to drive towards. What are the things that you want to know about people what are the things that you want to keep track of internally. The bits of knowledge that are the basis of the long term relationships that you build with your audiences. So that's the sort of the theoretical approach you know what's what's everything that you know if you had a notebook what would you write down in your notebook about the people who you meet throughout the you know throughout your day throughout your years and the work that you do and then how do you represent that information in your technology. So designing this theoretical model and then using that to guide the way you build and implement your platforms. So you know I think right to the examples we were just discussing, you know a lot in a lot of cases people will have an email system or a CRM. And for whatever reason they feel like it's not suiting their needs it's not helping them keep track of the things that matter to them. It's not helping them keep track of those relationships. And a lot of times when people look at platform change it's because oh I know Salesforce does that so let me go and use it or just as often I know I've seen Salesforce do that before perhaps at a previous job. And in a lot of cases what people are seeing when they're happy with their system is a system that's been customized. A lot of these tools they make a lot of guesses, you know there's a lot of guesses as to what clients need and and when you bring something out of the box you're looking at the lowest common denominator of you know what this is what the most number of people need in common. So a lot of really making sure that your contact model as an organization is represented well in your tool is understanding these these principles and sort of thinking through what is unique about the way I build relationships with my audience. And then how do I customize my tool to service those needs. So yeah, I think that's the high level there. Awesome anyone wants to jump in I appreciate that. Yeah I was just going to add to that like sort of maybe the, not the high level but like beyond the ground, sort of level of this I think a lot of where organizations are trying to get to a place where we're trying to move them to is to get, get to a place where things are scalable and repeatable. So that the doers on your team can actually execute upon sort of this high level approach to your strategy right so from a practical standpoint that means like being able to have your data sets and it built in such a way that you can easily can isolate known cohorts based on a few different sets of criteria and treat them differently so for example, let's say I'm a national hunger poverty nonprofit, and I'm raising money nationally and I know that I have a number of California doers on my file today if I were setting out an appeal nationally, I would be suppressing those California doctors and thinking about people who are affected by wildfire similarly if I was raising money from folks in the Gulf States I would during hurricane season I might instead of suppressing, I'm sorry instead of soliciting those folks I might send a note asking them how they're doing. I would sort of like asked for an appeal. While they're in their own personal crisis and I think further point on that. You know we had a lot of the conversations over the past year and 2020 with clients thinking about the pandemic and like how we need to go about sort of speaking to our audiences, who are now the heroes of a pandemic and so I think a lot of how we need to a lot of how we approach our different audiences at scale requires, you know, the strategies some teams to sort of step back and think about where these potential audiences are in the real world earlier, you know, as it's all about having a conversation with a person in my opinion so like let's take the tech out of it for a second, and just imagine that you're speaking to this person face to face, and how you would approach them and what you would say to them based on all the different things you know, and you know, and a number of different criteria again all once and again this was actually the tech though, where trying to get all this to a scalable place and a repeatable place so that your doers can be as efficient as possible, executing upon that strategy. I think yeah that's in those examples that you gave are so right. You know career wise, having a strong contact model. If you're in database operations, this is the magic trick right this is the magic trick of data operations it's how you pull a rabbit out of your hat, but instead of a rabbit, it's a segment that's like very closely aligned with your messaging needs, and the hat is a database that's the metaphor here. The, you know, the question is, how do you how do you reach in and feel around for those years you know how do you find the thing that you need. What do you what do you grab on to in your database in order to be able to say people in California, people who we know are in specific zip codes that are affected. How granular can you get help precise can you be, you know, other people in various life stages, you know, if you know life stage is, you know, graduating from college and likely reloading relocating for a job right now. You can tailor your messaging to people who are, you know, it's spring and graduations coming up and you can really think about and focus your messaging on these these smaller subset so it's your contact model is a reflection of your content and really, it's a reflection of your, your theory of change as an organization, it's a reflection of your audience research. A lot of that comes together in your contact model. And, and, and, you know, taxonomy is sort of the higher level buzzword, your contact model is how your organizational taxonomy reflects on the people on your audiences. And so I think that's, yeah, that's the right way to think about it. I think that analogy about if you were to meet somebody in person and how you would approach them because I think it's easy to forget about those, you know, nuances when we're doing things at large scale so thank you for that. So how can an organization begin creating a single source of truth and stuff and if you wouldn't mind just explaining a little bit about what that means. Yeah, so single source of truth is what, what everyone's looking for, especially at the leadership level of an organization. You just want to know how is everything going. You know how can I get the big picture of my audiences big picture of my content big picture of engagement of impact and single source of truth is recognizing the fact that we don't, we usually don't have one we don't have one place where all of the information exists. So organizations try to get towards this you know there's a I'm seeing more and more organizations moving towards data lakes right now. And those data lakes are have at their heart you know this is the place where everything comes together or I can turn to to answer questions holistically. But even there when you're designing your data lakes you're often making a lot of choices a lot of trade offs. You know you can create a lake or a CRM that is you know particularly well hydrated and that you know you have filled it with everything that you would like to know about about different people. You're usually leaving some piece of what you do over on the edge, especially with the rate of change of digital transformation there's always a new tool coming into your stack. So there's this constant flux and so the principles of the single source of truth are really focused on what is it that you need to know how do we keep a focus on the most important curated pieces of data and how we're going to use them. And then whether you try to do it at the platform level and say you know we're just going to have one data lake we're going to have one system and we bring everything into it. Or I think just as often and and perhaps more scaleably is the idea of how do we want to synchronize data back and forth. So you know what are the principles, you know how do I keep track of what I need to know across these systems. When I bring something in how do I identify the bits of data they're going to be most important, most relevant. And then make sure I have the integration setup the data reporting pipeline setup, so that I can get all that data out and in the right place where my leadership team is going to use it. My email outreach system is going to use it my CRM is going to let me segment based on it, and, and having those principles in place again, make the implementation of it, much more achievable and much more successfully. Yeah, and I'll jump in here too I think that that's really on point their stuff and you know, a single source of truth in my mind is something that for most organizations may not ever be something you achieve but is something that is absolutely worth striving for, you know, as much as possible having one place you can go to know in a consolidated way like as much about a supporter as possible you know did they buy a piece of artwork from your organization did they also give a donation have they also open X, Y and Z emails you know it's somewhere where you can go to really kind of form that comprehensive picture which informs what you guys were talking about in the last slide about you know what kind of modeling you can create in the first place. You know, for our clients, you know, we really kind of look at this as a bit of a Venn diagram, where, you know, in a perfect world, all your platforms would be completely overlapped, and it would be one perfect circle, and everything would be everywhere. The reality often is that, you know, you have a little bit of an overlap between all of your platforms. And what you want to do over time is try to move all those circles, all those circles a little closer together so that you know more about people and more platforms. And you use things like you know first party integrations or middleware like Zapier, in order to try to have more one to one relationships between platforms. You know this is always something where it's not really thought of at the time, you know when you're selecting platforms or, you know, a building out your tech stack. That's not really something you think of until it is a problem right until you know you're trying to find one cohesive picture of a person and you find that you have to cobble it together from multiple platforms. You know the good news is that you know now more than ever, there are ways to get scrappy about this there are ways to do more either through, you know, even if it's manual importing into one platform you want to be your source of truth. Having a process and a practice of you know getting more data clean and into that system. You know this concept of data hygiene I think is really important here, you know it's of course useful if all your data is in one place but I mean if it if it's data that you can't make heads and tails of, you know, that's also not all that helpful so I think it goes hand in hand with a practice of you actually looking at the data and being hands on. It's tempting in our line of work to think about automating as much as possible. You're right, you know, and of course there are things that can and should be automated but there's always going to be a human touch. So you're always going to want to sort of evaluate and continue to evaluate your source of truth as you develop it and as you refine it to make sure it's as accurate as possible. And, you know, in order to you know, tend to it like you would a garden right to add another analogy into our conversation. Right, you know it's something that you can't just set and forget it's something that you need to keep up and and continue to keep an eye on. Such good points like and and I think you you raised for me another really critical aspect of having a good single source of truth, or single source of truth capability in your organization is documentation. You know you think about the effort that goes into pulling together these holistic pictures. At the best side it's all automated and it takes seconds to pull together this big picture you've got the omni dashboard we all see in our dreams. At least I think we all see we all dream about dashboard three, but you know at the long end and usually the normal end it's you ask a question, and you know your team comes back like two weeks later like ragged and like sweaty and they're like okay I finally got it. So what's happening in between there is people are just like looking around the building the proverbial building in this case and asking each other like where I don't know how to know that how do we figure that out. And like they're going through databases they're coming up empty they're trying to come up the new way to ask it. documentation is to fix their documentation is how you get to that achievable middle ground. It's so that when people have a question they know what's where they know how valuable it is they know how reliable how fresh it is. But being good about keeping notes on the state of your data ecosystem, make it possible to answer ad hoc one off questions quicker without the expense of automating all the things, and without the heartache and the headache and the delays, the wasted time of trying to rediscover things that somebody else knew even six months ago, but you know that knowledge is lost. Yeah, you are speaking our language there stuff and you know, a big part of our process you know whenever we're helping with an implementation project is crucially that documentation, usually at the end of the process to wrap it up and what we call standard operating procedures, which are meant to replace any of the online learning modules that most platforms now have which will always recommend that you know staff members go through, you know that standard training on a platform if it's a new platform or if it's one that is not on board it on. But to your point, also very important is you know, what are the quirks, the, what are the ins and outs of your instance of that platform, because you know that's where somebody can really get thrown for a loop, you know, if they know the ins and outs but they don't know where to go to look for a certain custom property or a certain workflow that you set up or what it even means and why it's there and why should it not be turned off. And that is sort of extra really, really important knowledge for anyone who is, you know, a new team member, a new vendor or partner to make sure they, you know, know as much about, you know, your custom setup as possible because every setup is ultimately going to be If I can just add one more point out to that and sort of harm back to what Nate said about sort of the people behind I think this documentation point is really important because unfortunately I think and certainly in the nonprofit sector there is a measure of higher measure of turnover in terms of staff compared to other industries for whatever reason, but it does end up causing problems over the long term when you have to retrain people on a particular task related to some ongoing tasks that some previous staff person was doing for however many years so I think that point on documentation so that you, you know, I say that you can sort of trust that if and when tasks needs to transfer to somebody else that they can do so pretty handily because everything's well documented and they can move forward without too much delay or learning curve. That's a really good point I appreciate the that addition. Sorry. So I just want to go there we go. So if you want to discuss what good data looks like I think we've talked a lot about data structure and platforms and technology but what does that actually mean good data and how do you leverage data to make strategy and campaign decisions. Yeah, great question. And this is something we also think a lot about of course, and in my mind, good data is structured data. It's data that has a hierarchy to it. Data that you can peel back the layers on right you know data where you have information of people at the highest level, say you know which programs related to your organization they're interested in, and then going down sort of the funnel or going deeper into the onion. And, you know, what else is interesting or what else have they done, you know, it all in my mind is sort of, you know, a series of clues of their behavior and their intent and the interactions they've had or want to have with your organization in the future. So it's also, you know, a practical way of structuring your data to have it have a hierarchy in a sense so that if you want to say message people with an email campaign who are showing interest in a particular program. You have a way to do so because you know maybe structured your forms and your entry points so that you see which program somebody was interested in because they filled out an interest form related to that program, and you tag them in the back end in your system that way. And you can then you know follow up with them with a more specific message right that that's a basic example but I think a really powerful one for any organization which is like, you know, what are what are some of the things you need to your work that people are being most are gravitating towards right so you know it's that and then it's like over time really like based on more and more things that they do you know what are you consolidating on their profile. About you know them, is it like they made a donation to your organization and now you have not only their email address and their first name and their last name but you have their mailing address, you know, you have some detail about how much they've given or their average total lifetime value to the organization. You know it should be sort of this additive structure where you start from a very clean place where you have a macro level sense of their intent, what they're finding interest in, and then over time as they hopefully do more and more involved in your work, either through donations or volunteerism, you know, or, you know, peer to peer fundraising, whatever it might be, that you know you're sort of bulking up their profile, and that that data sort of is structured by and large as clean as possible so that you have a full profile on them as they they do more and you know in that sense be able to target them in more ways you know have a better way to either segment them or exclude them I think crucially from some of the work you do. I mean it's something we don't always talk about but good data means that you have more ways to make sure people don't get certain messages that they shouldn't be able to get, or you know that aren't appropriate to them right. Obviously one being is you know you wouldn't want to send an appeal for somebody to make their first gift to your organization if they've already made two or three gifts, right. You of course would want to send them a different message which would be about, you know, renewing their commitment or you know, going up this year or something to that effect so good data allows you to confidently do that in my mind. I was going to add to that Luke as far as you, I think you nailed it when you said, having the confidence in the data that you're essentially what you're trying to do is really serve up as tailored of an experience to every single cohort on your file at scale right so that you're making and choosing the different cohorts that are you believe to be important and to your point that not saying the wrong thing to the to the constituent and making sure you're presenting your, your messaging in a way that's absolutely relevant and you're confident in that I think how that manifests this how good data manifests its use in in strategy and campaigns is a lot to do with this audience segmentation over email, but it also has, you know, ramifications on how you think about different channels so like for example with a channel like paid search where you're understanding the measure of intent from a particular donor. Let's say for in this in this case and you start to realize you start to see your strong return on ad spend there and you're confident in that. I suggest making a strategy choices where you can start to pursue donor lifetime value or long term ROI within those channels that have a high measure of intent, comparatively to how you might spend. How much money you might spend on renewing a donor compared to how much you might spend on acquiring a donor so understanding the costs are alongside the return against these different audiences and having that confidence in those in those data points to then make really smart strategic decisions as it relates to investment over the long term, which audiences to spend money on and which channels to spend that money in. Like it's in to just to come back is it really comes down though to that really good data meaning lacking in errors, lacking in misinformation or or just lacking information generally. Yeah, you know I'll just tag on you know we I have sort of a simple rubric that I use for like good and bad data, you know, which which can be helpful because it's in a different context of different levels of quality of data or needs for that quality you know which is it how useful is the data that you're looking at as a tool for a widest the widest group of your outreach actors you know and so you know good data in a lot of ways is accessible to many people to use to make decisions and it's understandable on how to make those decisions with it and you know, Luke one of the things that you said that I thought was really valuable and important about data is that there is a hierarchy and what that can mean is sometimes that most of your organization maybe looks at a calculated field that could be something like engaged donor or you know about you know likely donor or anything like that, and they don't necessarily need to know all of the decisions by the scene that experts in your organization made to kind of say this is what represents for us a likely donor you know but they can look at that field and say, hey, this person is a likely donor so we should treat them differently and have a better or different and more tailored engagement with them and, you know, so I think that's really important is that the data is good when it's a business tool and it's bad when it is a raw material. And so a lot of ways like you know good data is actionable, you know, and so that's one of the things that I always just look at if you can't make a business decision based on that data that it's not good data yet it's more just, you know raw material that could become data or become insights, you know, I like that distinction between, you know, business decisions versus just raw material that's really helpful I think. So how can organizations build better data cultures and bring non data practitioners to better understand how they can benefit from data. Thank you I can't help but jump in on this one. You know when we think about data and good data in particular, you know I was going to end that good data question with good data is data that people use. And if data can find its way into business processes, then it can make a difference it can actually actually change the outcomes of an organization's work. And so I think having a better data culture is one that encourages and rewards that type of adoption of data and adoption of data as a community. You know I think there's a lot about data, the role that it plays in society in you know the the ethos of our organizations that makes it feel exclusive you know even the way we talk about you know I'm an analytics expert. It gives me some sort of unique right to work with data and and you know have opinions about data. I think we as a community need to change our relationship with data. So I think organizations doing things that make data feel more inclusive, it shouldn't be one person's job it should be everyone's job to think about their work and a data context. But more than a job it should be fun, you know data should be a way for you know it's like a fun puzzle it's a game that colleagues can play with each other. You know it's a use it as a you know a pub, pub quiz game, you know how do we actually make working with data fun for our staff make it feel accessible. The big part of this and using data well is asking new and interesting and relevant questions of your data. And I think that aspect is where a lot of things go sour, you know usually questions and organizations come from leadership. They come down people run off they come back sweaty and you know and and stressed out. How do we, how do we flip that dynamic it's not something that you're being tested on when you're asked about data. It's the start of a conversation. No those questions don't always need a data answer. I think, not being able to answer a question often tells us as much as the actual answer would. And so making it safe to ask questions, helping encourage non data practitioners to generate those questions. And then also making it safe not to have the answer to those questions. Coming down on your staff or not having the answer to a question is one of the worst things you can do. Making your team feel comfortable expressing themselves and wondering about data. So yeah, I think that that aspect of creating safe spaces informal spaces for data is one of the most important things you can do. That's such a good point Stefan I mean and one of the things I just wanted to kind of tack on to that that that things really related is um you know one of the things that you say frequently that I really like is, you know data should be invited to the meeting, you know, and I think that in a lot of ways people who are not focused and looking at your organizational data daily. So, you know, you get the benefit from the insights or even the lack of insights it can provide I don't know where the blind spots for the organization are as you were saying I think one of the things that can help is if it's also just like good practice for you know just general business is if there are agendas for meetings about some of the major topics to be covered in a meeting, someone who is a data expert can come and sort of bring that data or bring whatever insights are available around those questions to a meeting and start to have people ask and think about the data the organization has as part of the, not just the evaluation process but of the planning process and I think that's a really part of data culture as well which is data needs to move up in the planning from how did it go to what should we do. And that's a really important cultural shift and it only really happens if you start to bring whatever data you have is, you know, whatever quality it is to those meetings and then people could say, Oh, it would have been nice if we had X and now you have a mandate and a sort of guide to what the kind of priority should be for cleaning up your data or making it more useful as a business tool. And that's really important because one of the other things that's true about data is that there's usually a lot of it. It's really easy to not optimize the places that really help you make business choices. And if you start bringing that data to those meetings to start making it part of the cultural, you know, norm that people have some amount of data to influence the direction of the organization, then suddenly the quality of the data around the things you care about is going to improve more quickly than the things that are less important. And so that's just like another piece of the cultural part of data to me. I just really love this idea of sort of democratizing data to write and not making it any one person's job to sort of be the master of it, you know, and that, you know, really, you need to be mindful of it from start. And that's something we really like to preach is that you know, the worst time to have a realization that you don't have a certain data point is after a campaign has wrapped up, you know, and you're trying to measure something or you're trying to pull together a report, you know, for a group of stakeholders. And so what we really try to do in our processes like, you know, at the onset of campaign planning, or any planning of a new initiative is to think about what you want to track at that point. So you have everything in place in terms of your tracking before the campaign will launch so that things are there for you to analyze later on. You know, that's not something that say a data analyst or a data expert can do by themselves, because they're not the same person who is, you know, the architect of the campaign or the the marketer in this situation. And so, I mean, it really does take a collaborative process between somebody who is more, you know, of an annual analyst who has more of a tech background who can figure out how to track something but then also people who can answer the question of what should we be tracking or what data do you want to see in this report later on so making sure we don't skip that process is important or making sure we don't wait until the day of launch to start to think about that or try to get something in places is just really really important. I appreciate that democratizing the data and also creating more dialogue to help get people more comfortable it's really, really informative. How can organizations better use their technology to achieve their goals and how do you use technology to improve the ROI ROI on the projects and campaigns that you're running. So, if I can jump in here this is something that Luke and I, I feel like work on quite a bit and hard and sort of constant conversation about. And I think we where we landed is that you know technology ultimately unlocks the opportunities for organizations as far as how they can help how far how big they can grow their their impact. Specifically, you know as far as improving ROI, I mean, to back out of it for fundraising from a fundraising lens I, I think of ROI as surely just retention. It's how can I keep someone involved with a mission for as long as possible to grow the ultimate lifetime value of that donor. So it's ultimately having all the things we mentioned about data hygiene. That's all that's all remains true but this is where I feel that once you have those things in place the optimization process can begin. And the optimization process has to do a lot with just pure testing and being very confident in your in the, the tests themselves and also the subsequent decisions you can make after those tests are made so really the sweet spot I think is once you have that that that technology in place, and you have your data measurement pieces in place that that's when you're at a spot where you can then, you know, improve all upon what you're already doing by testing and optimizing into your different tactics. And this is where this to me is the really the fun part of, you know, digital fundraising and digital marketing is really sort of going back to, you know, thinking about your questioning what what why or why something works or something didn't work and then testing those assumptions over time against different audiences is really going to be the driver of that growth in a long term. That is a really good point stand I agree with all of that I mean, you know, I think one thing that I might bring is the the eat your vegetables, you know, sort of advice here which is that, you know, in a lot of ways, organizations are limited in the quality of the technology benefit they get or their ROI that they get, because they don't focus enough on two very unsexy parts of technology which are governance and onboarding. You know, for a lot of organizations there are moments in time where they're at a really high level of quality engagement their audiences and it's usually because they have a team that has become expert in that outreach for a moment in time. You know, things happen maybe because of that expertise they get promoted and other people come in, maybe people leave the organization, maybe one department gets a new head with a new initiative and they stop collaborating with that other department the way that they used to. And, you know, that stuff is always going to be in flux and is always going to change and the only way to kind of help manage that and help kind of additively increase the quality of your outreach with the technology you have is through the way you govern it and the way that you create the documentation that kind of in the data contracts that kind of ensure that you know the outreach remains high quality and so, you know, I think sort of anticipating and knowing that different people are going to be conducting your outreach over time and making that the plan instead of the exception is a really important part of making technology. It's a really important return that you expect from it because, man, we consult with organizations all the time that are using maybe like 20% or 30% of their tools capabilities. And they don't need any more technology with more technology is going to make the problem worse what they need is like better exploitation or better use of the technology they've already invested in. And when we dig into it, you know, there's often things like well, how do you welcome a new person to an email list and there's a lot of blank looks and people are like, should we do that. Yes, you should be doing that. But you know somebody probably was doing it at one point, you know, and so part of it of technology use is really, you know that do your homework part of it which is like hey we need a run book we need to say this is working really well let's write that down somewhere and hey when a new person comes on or when I leave my job there's a process for like transferring that knowledge in a way that's really useful for the organization. Oh sorry go ahead. I was just going to, I can just totally agree with you Nate and just echo your point with an example we I had a client recently I was looking at, I was doing an assessment of their donor file and I saw that they had pretty strong LTV for donors acquired from like 2016 to 2018 and then it falls off. I was looking here so we had a person here that was doing all this engagement with our with our audience and then it stopped because that person left. I'm like well that that can't be the reason that the engagement falls off to your point like it's sad things documented and have a process point or place for process where the next person up can sort of run with the test there in. I think that actually leads really well into our final question and I'll let everybody kind of jump in on their thoughts to wrap up this conversation. How does an organization build a roadmap for platform changes and what should you consider when alighting broader goals. Nate if you want to start us off. Yeah, so I think, you know one of the things that's challenging about technology is that, you know, especially historically there's been such a sort of short lifespan breach system that you deployed you know if you deployed something this year and four years, something so much more interesting and sophisticated has arrived and you need real temptation to switch horses and to go try that new thing and add it to your outreach stack and you know I think that life cycle planning is a really important road mapping you know I think, even if you want to keep a tool, you should say we're going to be invested in this tool for four years and then we're going to come back and review that investment and either renew it and stay on it for another period of time or we're going to plan the sunset at that point, and not just immediately sunset at the end of that life cycle you know and I think, you know that's probably the first thing is to look at all the different major systems in your, you know your platform and sort of say like when are we going to be up for a review, what are the criteria for that review, and how do we bake in our strategic planning for what we're trying to do as an organization into that as well right like simple example might be if you're having a mandate to reach more people and you expect your list to go from 20,000 people to 50,000 people you can today look at the price difference of your current tool and see if it's going to be huge price jump and if it's a good idea to stay on that tool if you reach your goal or not right you're not there yet but you can look down the road and see what that, how that impact that proposed growth is going to play out into your tools. And then you can start to bring that back to people and say, Great, I'm going to start planning to reach our organizational strategic goal, but just know I'm going to have to do these things with the platform in order to support that in a useful way. And suddenly you're way ahead of the problem and instead of in two or three years being like things have been going really well and now we got to switch our tools suddenly because I can starting to like become really un economical for us or not. It's all sort of part of the plan it's not disrupting the plan, and even that disruption is planned for because that's another thing whenever you make a platform change a big tool comes in or out of your platform. That can be really disruptive you have to make sure that all those data integrations we talked about all that data quality we talked about all that onboarding and governance we talked about all of that is planned for and how to deal with it. And that's even true when you add things that are just brand new to your system suddenly there's more available data, what kind of data is that how does it tie into the other systems and, you know, all of those things are often kind of relegated to the tech person to figure out or maybe the data person to deal with the impacts of, but really they should be part of the organizational plan to sort of decide if the way we're approaching this problem is going to help us be successful because, you know, plenty of, you know, strategic ideas are derailed by, you know, the process of operating them not being smoother efficient right like there's a lot of friction and trying to create change or improve an organization and so I just say like those are the key things that think through it just to bring all of your ability to have insights about how the tool use would change and how the cost would change and how, you know, the age of that tool and where it is in its own maturity model will impact your organizational plan. Into the conversation really early and then to start planning that out and you know one, two, three, four, five year kind of manner. That's my spiel on it. I'll go next. So that's really important everything you said Nate and I think what often goes on considered, you know, when organizations are shopping for new technology is you know they see the price tag of the platform in terms of, you know, the license fee or if there are, you know, transaction costs if it's a donation platform but what they don't consider or really budget for oftentimes are you know the onboarding costs or the maintenance costs which you can and will incur no matter what platform you choose but when things really start to suffer then you know that that hasn't been baked into the budget so you don't have, you know, help to build it out right. Or you also don't have enough, you know, time in the timeline to get things up and running smoothly. And, you know, migrate and sunset and previous tool that you were using so really got to look at things pragmatically and this sort of speaks back to what I was mentioning earlier about. I'm always thinking through whether or not it really is the right choice to, you know, change platforms, you know, not just because it's that shiny object or because it's, you know, the platform in the moment and there are a lot of buzzwords on their website, whether it's really, you know, worth it, you know, the juices worth the squeeze, as they say to move over and go through the time and energy that it always will take to migrate from one platform to another. So what we usually see or what I usually see many times is one of two scenarios where you have an organization where maybe they've been on one platform for quite a long time, longer than they maybe should. And, you know, it's just platform paralysis, and they never want to leave because they feel like they know it so well or they've been sort of held captive by that platform. They're going to stay with the platform because we feel like we can't live without it because you you certainly can and there may well be a better platform in that scenario. But also on the flip side, we don't want to, you know, run into a situation where you're just moving platforms every year because you know you think there must be something better out there, and then you get burned. If the staff gets burned, there's literal burnout, you know, and you know nobody really knows how to use the tools that you continue to buy so got to play it right down the middle and got to have a strong discovery process, really think through the right combination of tech for you to be using now and in the medium and long term. Great thanks and we're actually right up against time so we're probably going to end it there you guys did a great job informing everybody and giving everybody context on how to break silos down in their organizations and we really appreciate it. If anybody wants to follow us on LinkedIn, these are the links for both Parsons TKO and media cause, we'll be following up with the slides so that everybody has all of the information. And you'll also get a recording of this conversation so that you can have all of the nuggets of wisdom that the team here shared with you today. We're also following up with a survey as well so if you have any additional questions that you didn't get a chance to ask the fellas here today then please feel free to send them to us via that survey and we'll follow up with you all individually and we'll make sure that the team of media cause and ptko answers your questions accordingly so thanks guys for joining us and we hope you have a great day.