Optimize: Strengthen Your Fundraising with Clean Data

So let me here and share. Okay, you’re in my life. Yeah. Good afternoon, everyone. My name is Janet Carroll. I’m happy to be your trainer today to talk about optimizing your database. We’re going to strengthen our fundraising with clean data. We know that we’ve all Read More

So let me here and share. Okay, you’re in my life. Yeah. Good afternoon, everyone. My name is Janet Carroll. I’m happy to be your trainer today to talk about optimizing your database. We’re going to strengthen our fundraising with clean data. We know that we’ve all heard about many ways to use our data today by many of the trainers, and now it’s time to think about the quality of your data that you’re using or thinking about using. Is it data there that you expect? Is it in the right format? Is it ready to be used in your letter and email? Merges? What about your event? Analyzes. This will be our focus today, optimizing the data in your database, strengthening your fundraising with clean data. We’re going to focus on reviewing your data for you to get the most accurate, complete and reliable data possible for all of the work that you do. My name is Janet Carroll, and I’m one of the trainers here at DonorPerfect, and I’m more than happy to help you go along on this journey. Having clean data is something that we are all most concerned about, day in and day out. But tell me how many of you ever feel like this? Mean we’re constantly thinking about what our data looks like. We’re sort of frustrated with being the recipient of years, or maybe whatever the timeframe is, of data that’s not in great shape. Data is missing. We’re frustrated about not finding what we’re looking for. We’re angry that we inherited so many duplicates or transactions missing important details. Most of us unfortunately go through this. But wouldn’t this be much better? This is exactly how we should all be feeling. Right? Our goal today is to learn some of the best practice for you to maintain the best possible data, the data for your needs. Now and going into the future, we’ve made an investment in creating and maintaining our databases. Right? We need to make sure that we can optimize its value. So for you and your organization’s management team, you are giving reports to your board members. You’re giving them to the committees, the mail house, or Constant Contact, or MailChimp, your email marketing companies. We’re setting out we’re sending out communications all the time. We want to make it personalized. We want to make it sure it’s deliverable. We just have so much to be to look on the positive side of things, so we need to make sure that we indeed or cleaning it up, doing our best job possible. So it’s always in our best interest, literally, to work ahead, put in best practices and clean up our data, of course, to make the best possible ease of work every day for us, let’s make a plan for optimizing your DonorPerfect database, because we need to be on track for the all the work that we need to do.
There we go. We need to understand the value of clean data. We need to know the benefits in advance is because that’s our biggest incentive to go on this path of cleaning up our data, we need to identify the problems that we have when we’ve noticed problems. Yes, we’re going to be thinking about how we can clean that up, how we can erase these problems, solve them, get them out of the way, so that we can actually work forward and see reports, get results that actually make sense. Everything is in the right order. Work the data is helping us to move forward. We need to work on working on our solution, knowing how we’re going to solve our data problems, right? In other words, how am I going to clean up my data? What are the steps necessary in order to clean it up, all different kinds of problems. And yes, we have solutions and we have best practices in order to help you clean up the data you identify the problem. Yes, we’re going to find the right solution to help you out, and, of course, implementing best practices along the way, because it all works hand in hand, we’re going to clean up our data at the same time as we already have a rule set up on how we’re going to move forward, so they’re always going to be working together. Cleaning up is not going to be a temporary fix. If we’re going to be already implementing our best practices, right, we’re going to put that all those standard operating procedures into place so that while you’re cleaning up the data. We’re using all those same rules, and we’re going to have the best match possible to move forward together, right? So while we’re ensuring all of this is going on at the same time, we’re really saying we’re not working in a vacuum. We’re having both sides. We’re cleaning up what’s there. We’re moving ahead with all the rules, the best practices. Going forward, let’s start with that first bullet point, the value for clean data. We know we need reliable data in order to say, be confident in all the reports that we do, the communications that we’re going for in order to have reliable data. We have to kind of work our way start from the beginning, work our way back and say, How are we going to get reliable data? Well, think about it, we’re making sure that we have the right rules set up when you’re manually entering data, when you’re setting up your online forms. We want to make sure that everything behind the scenes is set up right so it’s going to fill in the data that you have set up. We don’t want to be missing any data points here. We set it up fully and accurately and within context. Behind the scenes, those online forms are not only going to collect the information from dollars to registrations to volunteering everything when we pull it into DonorPerfect is going to be there for you because you’ve done the job setting it up behind the scenes, right? So if you might also be importing data. So when we’re importing data, right? We set it up just like from manual entry or from online forms. We set up the import file so you know what’s there, you’re setting it up just as with the other methods. And because you know that it’s there, it’s accurate, we can rely on that the integrity of your data. We need to not only make sure that it’s complete, like we were just talking about, we are. We need to make sure that it’s accurate, that it’s within a context, as we just mentioned, we know that it will be useful to everybody, because we’ve had this control from the beginning to the end. And yes, the integrity does absolutely overlap with reliability. They really do work hand in hand with each other. And the growth the value of our data, it’s getting us into position to grow right clean data. Provides the data how you need it, how you can interpret it, and when we have all the data together in the right format, we can make interpretations. We can see what’s going well, what needs tweaking, all of that. We can see that. And because of that, we’re putting our sorry, we’re putting ourselves in a position for growth, and I think that’s what’s going to help us going along the way. Second in line of our plan is identifying problems. Unfortunately, this is some of the nature of the beast. When we are collecting data, we don’t always get information, and so we sometimes, if a new person is helping us out, we need to make sure that we communicate. So sometimes we are missing some data. So think about that. We need to make sure that we identify what’s missing so we can then go back and clean it up. I mean, think about our communications. All of our merges. Are you missing addresses, or any parts of an address that would make it undeliverable? We need to identify those. Make sure that wherever we can fill it in. But right now we’re talking about simply identifying the problem, because the next step, of course, is fill it, filling it in as best we can. If we can’t, we’re going to market so that we can then work on that later on. Are we running a report, let’s say the solicitation analysis. And maybe you’re looking, you’re looking at all of the results, and that every row has how many donations, for the total dollars, how many unique donors? And we’re looking at all the solicitations, but wait a second, the top line is blank, or it says no. It says no code. Well, that means that we have all this money, and we don’t know what effort we made that was successful to bring in these TR this the money. So we need to identify this is, again, as part of identifying a problem. So we might be noticing it when we’re doing our data entry, unfortunately, not knowing it. Other times, we’re literally running a report in order to identify and see that there’s a problem that we now need to learn how to fix. How many of you can say that you have duplicate records in your database? My guess is most of you, if not all of you. How many of you watch that and and look to fix it on a regular basis? Right? If we’re finding multiple records for the same person or organization, we do need to add the the need to identify these duplicates and then learn how to merge them together as part of a regular process. So again, one of our problems, what about having inconsistent codes? I don’t know about you, but I’ve worked with many of you for many, many years, and I’ve seen a lot of situations such as having gala 2025 and 2025 Gala. I. I’ve looked at the donor types on some records, and I see individual more than one time. Okay, I’ve seen different a slightly different wording, all meaning the same thing. So we have to be conscious of how we’re doing it. What are our choices? And as they say, We don’t want to have too many cooks in the kitchen creating all these codes, unless you’re already familiar with the code. So we end up with a lot of inconsistent codes throughout a long time of your database passing the baton from one user to another, everybody means well, but we’re not always on the lookout to see if something’s already there or if it was created a slightly different way. What about inactive constituents? Yes, think about this. Does your database contain only active records that are going to be used going forward? Think about your active donors, your active volunteers, your Okay? Likely not. We all have databases that have records that we’re hoping that are prospects right. So we want to make sure that there’s a value to keeping the record right, even if there’s no, quote, unquote, current activity. Have you ever thought about why the records are in there in the first place? You may have a source field being used. You may have some flags that are marked of why they were entered to begin with, okay, maybe they’re related, or they’ve shown interest in participating and supporting. Maybe they’ve been interested in becoming a volunteer or becoming a sponsor. And now’s your opportunity, if we think about why they’re inactive, let’s run a report on some of those that are inactive, learn about it, and take this as an opportunity to bring them into the fold, to make them, help them become active. Fixing these kinds of all of these kinds of problems, will give you the biggest picture that we have here, and to be honest, this going to help us with the growth that was just identified. It’s going to clean up your data, and you’re going to have more active and you’re going to have the retention, you’re going to have the new donors, you’re going to have all of that. Going forward, we just identified problems now we need to think about, how are we going to solve them? Right? Let’s take each problem we’ve identified, let’s try to find a way to fix it. Code maintenance. How many of you have problematic codes? I bet if we asked everybody to raise their hands, you would likely find that there are many of you that have you may have been cleaning them up along the way. Maybe you still have a problem with some of your codes, right, inconsistent codes. Maybe you have those duplicate codes that I was just mentioning before that you really do need to merge into one. So think about what your codes look like, because indeed, we need to find a way to fix it. I’m going to demonstrate that in just a little while,
merging duplicates, right? You may notice duplicates directly while you’re doing your work. You You search the word Smith, and you see a lot of Smith, and you realize that, wait a second, I see a Smith there, and I see something here, and I know that there I don’t see a spouse or a partner. I see something that I’m not seeing correctly, and you find out that there’s two different records that were entered slightly differently. They need to be merged when you are doing your work. And you notice this in your work, please jot down those names along with their donor IDs. Very helpful for you. We’re going to talk later about how helpful that can be. DonorPerfect also has a merge duplicate utility. Yes, we’re going to demonstrate this, but that’s going to show us a report. So merging duplicates is going to be a combination of running a report and having the database help you merge that. It’s also going to be finding those duplicates because you have found them and enter them and help you merge those that might not have been found from running a report, because people have different last names, there might have been a typo, there might have been nicknames, and on top of which somebody could have moved, or even a business may have moved, you know. So there’s all different reasons why we need a few different ways to solve the problems. Here’s my database tip regarding merging duplicates. How about if we say that we know that we should be merging duplicates on a regular basis throughout the year. I know a lot of you likely say we’re overwhelmed. We have a lot to do, and we wait. We reserve the time to merge duplicates when it gets towards our large mailings, okay, our large whether it’s a postal mailing or a group email, we wait to do it until then. It then becomes a huge job. And we, we look we do not look forward to the amount of time that’s needed to get everything ready. So imagine that you’re doing it in smaller chunks and solving the problems during the course of the year with the duplicates. So when it comes time to those really big mailings, you know, you don’t need to set us. We need to set aside time, but we we don’t need to set aside as much time, because if we’re doing this on a regular basis, for some people, it’s going to be honestly, I actually heard somebody say that they do it every day. That was one of those once in a lifetime for me to hear from in one of my training sessions last week. But I know that on a regular basis, it could be weekly, it could be bi weekly, it could be monthly. Don’t put it out too long. Have it always on your calendar on a regular basis, because if you get behind on one time frame, you’re just going to it’s not your next one’s not going to be very far behind. So it’s going to help keep you in check, which is really nice. So add that to your calendar. We know that that’s going to be very helpful to you. Running reports. We know that reports are always going to be helpful to us. We, as this is saying here, we might be running into a report where we have some that 2025 gala and gala 2025 we might see that on the report, we might see other issues. The data even might be even out of order simply because of how you have entered your your codes in the first place. How many of you have used, let’s say for the year 2025 you might use 2025 in your codes, and you might say, Well, wait a second. Last year I just used 24 Should I just use 25 here? Or should I make them both 2025 looking at your codes in the big picture, is going to make a big difference in when you’re looking at your report, the consistency is going to put it in the right order for you. So when you’re looking at results, it’s going to make a lot of sense, and you’re not going to be trying to rearrange the results in in order from time period to time period. So we know how important the set of codes that you use. Think about it. Our discussion of codes is part of our data entry discussion in many webinars and in our learning center resources. And I just wanted to also point out with our emerging duplicates, yes, there is a recording in our on demand webinars, and indeed, on merging duplicates. So I want to give a shout out to that as well. What I’d like to do right now is actually jump into the database, and let’s see some of these in action. So let’s come here into our database, and the first place that I’m going to look at is some codes. So I’m going to come up here into settings and code maintenance, and in my show only here, I am going to find my solicitation codes. Been talking about that already, so let me let’s come down in here and let’s look at solicitation. And let me see here we’ve got a total of 69 whoops, 69 solicitation codes. So you know what. Let’s look at all of these at the same time. So now we can scroll back and forth. When my first glance, I see all of these four digit years, which is fantastic. So I see some consistency as I’m scrolling through here, but look at the top. This is displayed right now in description order, as it always is when you come into code maintenance here, and I see two of them right at the beginning with the year at the beginning. I know this is a problem, because I’m right near the beginning alphabetically from alphanumeric part here, annual appeal here, it has 2024 and you know what? I have, 2024 annual appeal here as well. Certainly this is a problem. What do we do? Well, when I’m thinking about it, I have two active codes. Keep in mind that one of them may not have been active. In this case, I see them both active. Even if one of them is inactive, there’s still a chance that somebody entered real data in there. And so we can’t just delete it. We have to check our database to make sure that that if there is data, we are consolidating it into one code, and once it’s all consolidated into one code, then we could validate it, verify it. And once that’s we see that, and then we see one of the codes is used and the other one is not used anymore. Then we feel confident in order to remove that other one. But wait a second, we’re here talking about data cleanup. What do we do? How do we do this? The best way to go about this particular scenario of having these two annual appeal 2020 fours is to use glove, the global update function. So when you learn about that, yes, we always run a backup of our database. First best practice before we do certain kinds of changes in our database, you will get a reminder. Of it. Global update is going to allow us to say, Hey, DonorPerfect, find the data in what a certain group of records. In this case, I would ask for all the transactions, gifts, pledges at all, with a solicitation code of right here, 2024, aaa, what do I want to change it to? I want to change it to just the reverse. Aa, 2024, because I like the consistency of all of these other annual appeals. So I’m going to find all of these, right? I’m going to find all of those and change it to be this one instead. After that’s done, I want to run a report make sure that there’s no use of the original one, just to validate that yes, I did it correctly, right? And then I’ll be comfortable and confident that I could then use the trash can and literally get rid of the other one that should not have existed in the first place. So I hope that if that, if you need help with that, we’re actually as part of their data cleanup series, July 8 to 10. So come join us for the live webinar just of just over a month from now, and you’re going to learn all about global updates, which is really fantastic. I want to also come over to here. We’ve got Look at this. We’ve got our fall Gala. We’ve got our fall Gala, 2024 but look at this. I know that I know that I don’t like the 2024 at the very beginning. Let me scroll down and see the rest of my galas. Okay, so look at this. I have all my four gala they all all the codes start with fog, full Gala, and a four digit year, which is great. And you know what this last one here is for full Gala, 2023 right? So be careful, because here is a full mailing. It’s not the gala. So here I have my full gala 2023 and at the top I have my full gala 2024 so this looks like I need to fix it. So I’m going to click my blue pencil here, and I’m going to change this around the others. Have the year at the very end. So I’m going to do that same thing here. We have our full gala 2024 so I’m going to do a little bit of typing here. So we’ll have our full gala 2024 and we’re going to remove that and make now our 10th anniversary is more of a description of the gala, so I’m going to click Save
look at this message. It’s saying that we have existing records with the original code. And because of that, it’s asking us that if we want to continue, then it’s going to update the old value to the new values. What’s going to do my data cleanup for me, which I am thrilled about, because that’s a huge time saver. If you don’t want that, if, for some reason, you had one of those moments and you’re saying, wait a second, let me check with something, then you can cancel out here. But I know this is what I want to do, so I’m going to click continue right here. My data was just fixed at the same time as I changed my code, which I am thrilled about. So look at what I have here. I’ve got my full gala 2020, and look at what I have here. I’ve got the virtual remember, that was the year with COVID. So everything went virtual, and now I added the same coding scheme for 2024 here, so I have my 10th anniversary as an extra description, if I would like now to use that parentheses like was used before for virtual. I could come in here and edit this, and I could put parentheses around it, and we’re going to now see that when I save it, there we go. When I save it, there was no prompt, because all I did now was simply change the description. If I change the code, then it would have asked me, Do you want to change the code in all of these records? So the description is that translation of the of the code and into that user friendly description. Let’s take a little bit more of a look down the line here and see if there’s anything that kind of jumps out at us. So we already talked about the annual appeal. We fixed the full Gala, and I’m just scrolling down see if anything just kind of, I’m going to say, pops out, and look at the end. I’ve got all these unsolicited and I’ve got a mixture of two digit years and four digit years, and because of that, they ended up out of order. I mean, take a look at this, this list right here with all of the unsolicited right? It doesn’t make any sense if I were to edit the descriptions, that would put the descriptions in order if I made them all four digit years, which would be great. But I’m going to ask you to go one step further, and when you are editing. The descriptions, Please edit the codes at the same time, because some there are some reports and there’s some needs that you’re going to have when you’re going to ask for the codes in order, and not the descriptions. Okay, there’s going to be different times for different scenarios, so I like to always say, have them always match. So if I’m going to edit here, okay, I’m going to add, I’m just going to edit this for just this one, and I’m going to say, here we have the year 2020, so this one’s actually an easy one for me to fix because of the the year there. I’m going to save this. Yes, I’m going to change my data to, oh, there we go. So look what just happened. My 2020 is now where it needs to be, right where it in line with everything else. But you know what? I need to edit these other three on the bottom so they will then fall in line between the unsolicited 2020 and the unsolicited 2024 so, so important to make sure that we’re doing all of this on a consistent basis. And then, of course, if you’ve made any changes here, please make sure that your online forms are also updated. We don’t want them to come in and have it be a problem. Okay, they need to be recognized because they no longer once you make a change. We don’t want any of those references to be with the old codes. We want them to be with the new codes. We want them to be validated. You cannot bring in import codes that are that do not exist. So this is pretty important to do, right? So let’s now take the next step, and let’s look at merging duplicates. I’m going to come into utilities, and I see merge duplicates here. But what’s best practice? Best practice when we’re doing this kind of data cleanup, just like with global update, is to run a backup first. So I’m going to come into backup and restore, and I’m going to create a new backup. And yes, I’m going to say it’s okay to remove my oldest one from May 13. I now have today’s backup, and now I’m going to stay in utilities and click on merge duplicates. So if any of you have been on the screen, you might already be aware we choose the fields that we’re going to compare, and if you’re not yet familiar, please notice that we have our choice of fields with our check boxes here, and we have the number of characters starting from the left, which which cat number of how many characters from the left that we want to use in the comparison. So you get to pick and choose how many fields you would like to use in the comparison. So right now, it’s the first 10 characters of last name, the first eight of the first name, the first eight of the address, the first five of the zip code. Keep in mind for all of our Canadian friends and elsewhere where we it’s not just the beginning of that zip code, right? We have a space so I remember when I’ve worked with many Canadians, we have three characters in a space. That space counts. So you might decide, do I want to check with three? You know, again, we’re looking for problems. We want to find the matches. So you might say, let’s look at the match with three characters instead of five, because just in case there was one enter that didn’t leave this space. Okay, different things to think about. A lot of there’s a lot of things to think about when we are merging duplicates. So people with different last names, people with nicknames, right, or spouse or partners, even with the same last name, we might have one entering it and, you know, and another time the other person enters it. So again, different scenarios. Somebody moves. We have got different addresses for my test here. I’m going to remove the first name from the list. So I’m actually going to say, let’s compare last name, address and ZIP code. So I have 10 characters, plus eight characters plus five characters. It’s going to now look for 23 characters in the database. Where do these 23 characters match identically the same group of 23 characters in any other record? I’m going to come down on the bottom and click Show Report. I have two that came up. Here’s differences that we just talked about. So I have John here and Marjorie. So the names would not have come up any other way, unless you found it in your searches. If I search on Hopkins, I would have had two Hopkins at the same address. Yes, I would jot them down to make sure that they get merged at some point. And look at this. I’ve got Bob Lukens and I have Robert same scenarios. You know you’re typing Lukens, you get multiple records. So here we are. Let’s practice and take a look at what it means to merge duplicates. I’m going to click on simple here, and this simple option gives us a few fields to work with at a time make our decisions. Which one are we going to save? Believe which record are we going to be merging into or combining into the other record?
When we click on Advanced right we’ve got simple advanced and not duplicates. So I’m going to click on Advanced right now. Here. We’ve got a different presentation. We’ve got our fields on Main and bio listed out. Okay, we need to make decisions. What are we keeping? What are we going to keep? What do we like in the other record? So look at what’s here. We’ve got, by default here. I’ve got one column here with all the radio buttons marked off, and this is right now my destination record. Okay, so by default here. So and look at this. On the right hand side, it says results. This is like looking at my combined result before I even tell the database to combine the records. Let’s take a little look further my fields. In the middle is right now the default of what I’m saving. So what I’m going to do is I’m going to look to look to the left and see if there’s anything that I want. I’m taking a glance down here, and I’m looking at my side, whoops. I’m looking at my salutation here, and I have my salutation is informal, and I have my informal first name, and it’s just the opposite on the other record. And I think I would like to use Robert on my address block and keep my informal salutation here. So I’ve got my Mr. Robert Lukens on the address block, label, letter, envelope and inside my personalization. That’s so important, I’m going to have that here with my informal Bob. If you happen to know that Bob is really Bobby to a lot of people, you can literally just make it that way right here. And as I just did so this right hand column, you could edit. You could any way that you need. Let’s continue down the screen. I’m looking for differences. I’m also looking where I might know the information. I don’t have any phone numbers. Whoops, I don’t have any phone numbers here. They’re all missing. If I happen to know them, please feel free and put them in. I see there’s an email address, but I don’t have one in the middle, so let’s click it here. I said of typing it in or copy paste, all I did was select it. Let’s pause for just one moment, for a second, if this was really if, if, while I’m going through this, if I happen to actually notice that there was actually suffixes filled in. What if this was a junior and a senior, or something like that, two different suffixes that would tell us that there’s actually two different people at the same address, not unheard of, right? People sometimes live in the same same home as an adult children. If that was the case, I would leave the screen and select on the prior screen, not duplicates. I don’t want immersion, and when we click not duplicates, they’ll never be paired together again. So that’s one of the good pointers to remember. I’m going to scroll down again. I’m just looking for different information that might be different, that I want to change. I have number of gifts and lifetime gift total. There are no radio buttons here, because no matter what you do, the data is always going to be combined. Pretty nice. All right, I’m going to scroll down here. I’m just looking for different kinds of data that I might want to combine or select from. The other record on the left. And once we finish our main fields, it goes to the bio fields. Right now we’re on the bio fields, same thing, select from one or from the other, and on the very bottom of the screen, we have a combine. Does the same thing as what’s on the top here. I’m going to combine. Remember, I do have my backup. I now have my opportunity to go back to the merge duplicate screen, or go back to the previously generated list, where I know I have the Hopkins. I want to come down to the merge duplicate screen. I unfortunately don’t have time right now to show you that merge record. But believe me, it is merged. Okay, if we have time, I could always go back. So what I want to do right now is to oops. I want to come in and mention the advanced combine here. Do you remember before, when I gave you a little bit of information about making sure that we have that we when you run across names that are duplicates, jot down the names. Jot down the donor IDs. We want to make sure we when we do that, this is what we take advantage of. It we come into advanced combine right here. Click on combine manually, and once you click on each of these links, you’re going to be able to indeed go through that same process once more, one more time. All right, I’m going to come down now. I’m just looking at the time right here, and I want to be respectful of that, so I want to give myself just a few minutes. Let’s do a quick report here before we come back. And I’m going to run my general ledger analysis report, and I’m just going to use it for my current fiscal year. Make sure there’s no other restrictions going on. And look at this. There’s no general ledger code on this top row. So what I need to do is click on here and try to figure out what’s going on. I have all of my data here, I’ve got 24 gifts that need to be edited to be able to fill in general ledger codes. If you know that, notice there’s a trend that’s great, wonderful. Decide on which method you want to use. One of the methods that I like to recommend when it’s all different kinds of data, fixes, okay, different designations. That is, I like to use the process of exporting data, fix it up offline, and then import the data back in. And we have just the webinar for that in that database maintenance series The week of July, 8 to 10th. So please join us for that. And remember, all of this is also in our learning center. So it’s all here ready to help you out. All right, let’s come I’m going to come back onto the home screen for later. Let’s come back in here. Is, I know that running a little bit late here. So we while everything is going on, we’re fixing our problems. We need to implement all of our best practices, all of these standard operating procedures for you and your colleagues. One way to do it is to set defaults so it literally saves time. We set it and forget it while you’re entering checks, if it was defaulting to checks, if you have something else like you’re having hunt, you’re entering your own tasks. You need to call somebody, you need to send out some emails, you could put in your own tasks and default the assigned to right to you, which is really nice as well. So defaults are fantastic, right? Our goal here is that really, while our data, as I mentioned earlier, is being cleaned up, we need to really put our best practices into place at the same time. So we’re putting our best foot forward all at the same time. All right, the next one that I wanted to point out here is about requiring fields. If we know that something absolutely has to be filled in. I know that a lot of you that are doing the financial, the entering the gifts, we know that our accounting team, our finance needs to have data. Maybe you’re doing some integrations with with QuickBooks or with sage. We need to make sure that likely our general ledger may be other fields too. QuickBooks class and other fields are filled in as well. Require them. It means that you cannot click Save without filling it in really, really nice. And you’re going to notice that with the red asterisks on the screen itself. Smart Actions. It has been talked about by many, several, I should say, of my colleagues already today, and this time, however, we’re talking about data cleanup. So yes, there are additional smart actions that are geared to the shape of your data. So if somebody has to be notified when you delete a transaction or delete a record, we can have that happen. We can automatically send out that email. What about not having the supporting information? Like, I mark a record, do not send mail, but I forget to put in the reason for it, I can have a pop up message on the screen that says, Wait a second, you’re missing a reason. You just designated somebody do not send mail, but you need to put a reason for it in there. I love those particular pop ups. I’m going to take a slight deviation right now, a quick, quick stop just because of the time. Let me come into settings and defaults. I’m just going to do a real quick one here, I’m now consent to false whether it’s just for me or even everybody. I’m just going to do it for me. If I am putting in checks, I’m going to have my type of gift is checked, and if whatever my the other details are that are going to go along with, let’s say, a pile of checks that are all coming in from an annual appeal, or whatever it might be that people are sending in checks, fill it in for all of that. Okay, I’m just going to click save here and now all of my defaults are going when I only me, because it was set up just for me. It’s going to default to check. It’s not set in stone. It’s simply my default.
So in summary, with everything that we’ve been doing here, we need to create a plan. What reports are we going to use? Right? What are what’s going to help us most with our data cleanup? Think about what you what you are your favorite reports. Mark them as your favorites in the Report Center. Here’s my tip. In all of the summary here, create a filter folder, like in your settings and filters, create a filter folder for data cleanup purposes that’s going to help you save what you’ve been using for the future, because we know that this is a repeated process. What about tools to help you along? Well, we have a lot of resources here at DonorPerfect, the knowledge base, the. Learning Center, the support team, working with your trainers. We’re here to help you in all different ways, shapes and forms. So please reach out. We’re here to help you get to that next step. Think about what best practices you’re going to use, all of those standard operating procedures, the completeness, the consistency, checking for duplicates. We know that the list goes on. But in summary, right now, I know I want to take some questions, if possible. I need to just circle back to clean data we talked about at the very beginning. All of this data cleanup is going to help us with our merges. They’re going to be deliverable. The reports are going to complete, be complete. We’re not going to have those blank areas on the top line of some of those reports, everyone’s going to get only one mailing because of your merging of duplicates, we’re going to have everything combined so we’re going to know who is really current, who is a lapsed donor. I’m happy to take help answer any questions you have. I can see that I’ve got just about three minutes left, but first, I really want to thank everybody for all of their hard work making the world a better place. I know that without you, we wouldn’t be where we are right now. So we look forward to helping you out with all of your data data cleanup efforts. So please reach out to us when needed. I am going to stay in the database here. Lori, can you can I hear you? Now,
let’s check, can you hear me? Yes, I can
do. I have any questions to answer. You
do, but we only have probably time for one of them, but I’m going to grab the one that had the most up votes. It seems like a lot of people have the same question. So the question is, do you have any suggestions to avoid a faux pas with households where both spouses become members at one time, but there might be an update for their record. I always get nervous about whether they might have been a divorce, as I don’t want to assume they’re still married if they’re not. So do you have any suggestions? Let
me try to make sure I understand the question. We’ve got two records. We have two memberships in one record. Can we repeat the beginning of that? Well, they
didn’t say mem. They didn’t say membership. They just said members. It says there might be an update to their record. It sounds like they don’t know which one is getting the update, or which one has been updated. It says I always get nervous about whether they might have been a divorce, as I don’t want to assume they’re still married if they’re not. So it sounds like they have a faux pas with the households, meaning both are in there, but they’re not updated at the same time. So I’m
just going to come back into the Hopkins record. So I’m hoping that I’m hearing this right, so please correct me, Lori, if I’m not getting it
so well, I have to admit I’m not as I’m reading it. I’m thinking, okay, they might have gone in separately, but they’re not sure if they should be combined or not.
So I’m not sure which when we’re talking about updating a record. Also, I’m I’m thinking about, do we have a gift come in? Do we have an update on an address? I’m not sure what’s going on. So I’m also thinking about this search screen I just searched for Hopkins. And the question is, do we have, do we have an email address? Did we just get a gift. If there’s any questions, I’m looking here, and I’ve got two Hopkins at the same address. But wait a second, you know, what’s the situation? You know, as you were saying, What if they these were actually, you know, different addresses? I think this might be one of those scenarios where I’m going to put it on a record, and I might indeed reach out to somebody to make sure that I’ve done the right done the taken the right action. I know that many years ago, I worked with somebody, and they, there was that parent with the adult child scenario, and they literally the gift was put on the wrong record unknowingly, because it was literally the same name at the same address, at least from a search result they didn’t see at the time. Or maybe it might not have been noted for the, you know, with the suffix. And fortunately, the donors were very nice, and they they basically said, we need the the thank you letter sent to the right person. So they helped us, they helped the DonorPerfect client that I was working with at the time, clean up the data. So I’m looking at this as an opportunity to clean up the data. So I might put a gift, let’s say, under John, and I might then reach out and say, I’m just wanted to check because I have some data here that might not be exactly, you know, working together, coinciding. So I might, I might look at this as an opportunity to clean up my data. And again, I’m not sure if I’m I wish I was able to have a conversation right now. So I’m also going to give a shout out to whoever asked the question. Please reach out to the support team, or if you’re working with the trainer, please reach out to one of us to be more explicit with what your scenario is. We know that we right now, DonorPerfect is not. Do households, but we know how important it is to have all the data in, literally in the right place. So we’re here to help you. We’re here to help you analyze and figure out what the situation is, what the issue is, so we can help guide you on the right path. Because I don’t know if I should put Marjorie and John in the same record, one on a me first name and whatnot, first and last name and the other one on the optional line. I don’t know, unless I know more about this scenario, about the records,
well, we can have them contact support. I just I have to jump in here because we’re running over. But I want to thank you, Janet, for for presenting this afternoon, and for those who attended the sessions today. We hope you had a fantastic conference experience and some great takeaways from the sessions that you were able to attend. Please join us for closing remarks, though they’re going to be hosted by Mallory Erickson, so you don’t want to miss those you’ll want to hop over there and we’ll see you in a few minutes.
Take care, everybody. Good luck with all of your data. Thank you again. You.