Improving Donor Data: A Real-Life Story (Video, Podcast, Transcript)

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Recording of a webinar presented in partnership with Community IT Innovators.

Improving Donor Data: A Real-Life Story

Organizations often have years of donor data that doesn’t inform action. Information about donors and prospects contained in CRM for nonprofits—when properly managed and analyzed—can have a dramatic impact! Luckily, there are techniques to transform data into information—improving donor data to drive outcomes.

In this video, we share a story of how one nonprofit organization improved their donor data. This story is organized into three parts:

Clearing for Action

  • Decreasing the “noise” in the database
  • Getting to know the constituents
  • Learning about best practices and engagement/giving trends
  • Developing a plan and building consensus

Taking Action

  • Reducing friction in the subscription and donation processes
  • Improving handling of potentially fraudulent transactions
  • Pushing the right Call to Action
  • Improving donor data analysis and segmentation
  • Increasing integration and process automation
  • Applying greater discipline in constituent data management

Assessing the Outcomes

  • Increased revenue
  • Increased “sustainer” monthly giving; smoothed out cash flow
  • Increased donor and organizational happiness

This story includes key lessons that can be leveraged by any nonprofit to increase organizational knowledge of its constituents while turning that information into outcomes. You’ll learn a variety of helpful strategies and tactics to create better donor data. You can apply these lessons to improve your own donor data and create your own success story!


  • The story: (2:16)
    • Clearing for action and cleaning existing data (4:52)
    • Learning more about the constituents (7:49)
    • Using best practices moving forward (9:15)
  • How do we get the organization to prioritize this data work, which probably took quite a bit of their time to implement? (22:45)
  • Asking the target audience for personal information first before extending an ask for money, increases the chances of them donating. Could you elaborate on that, what does that look like in a given campaign run via social media for example? (24:10)
  • How do you convince executives to pay attention to this kind of stuff? (26:03)
  • Is improving donor data expensive? (26:50)


Peter Mirus [friend of the podcast, co-founding Partner, previously with Build]: Good afternoon everyone and welcome to the November webinar for Community IT Innovators. It’s titled, “Improving Donor Data – a real life story” and this month’s webinar is presented in partnership with Build Consulting. A couple of housekeeping notes before we get started. Feel free to ask questions via chat. We’ll leave some time for Q&A at the end of the presentation. Try to avoid multi-tasking, you may just miss the best part of the presentation. And finally the webinar recording and slides will be available after the webinar and we will share them with all registrants.

A little bit about Build Consulting and Community IT. We both work exclusively with non-profit organizations to help them make information technology and information systems decisions that support their mission. We have a collaborative approach and our goal is to empower our clients to make informed choices for their organizations.

My name is Peter Mirus and [I was] a partner at Build Consulting. At Build, I [served] non-profit organizations as a part-time chief information officer and a project leader for data and technology initiatives. Clients I have worked with include such as the Humane Society of the United States, Neighbor Works America.

Build Consulting leads in the social good sector by providing different types of services. The first is the Build Interim and Part-time CIO offering where we serve as part-time or interim chief information officers for non-profits. The second is projects, including Assessments and Roadmaps, Software Selection, and Implementation Support where we perform business process, technology and data projects ranging from strategic assessments and tech road maps to system selections and implementations. And finally, with Build Outsourced CRM Data Management Teams, we provide outsourced data managers that have deep development operations experience as well as non-profit CRM expertise.

And it’s from these services and providing them over for a long period of time with a wide range of non-profit organizations, that we derive the insight to fund, so to speak, a presentation such as this.

And now, let’s get into today’s story which is about improving donor data. It’s a real life story. And let’s tell you a little bit about the organization itself. As a 15 year old non-profit with a niche of providing news and analysis related to a range of cultural issues. They are chosen for the story because the challenges that they face and the solutions they applied are relevant to all sizes of non-profits. And the solutions applied are transferable to small and large environments. To give you some sense of what they were looking at in terms of constituent base, 4.5 million potential constituents, which was a figure that was determined based on the number of recurring information consumers across all of their channels both traditional and digital, 55,000 known constituents and by known, I mean we had at least the full name and at least one method of direct communication with them. 45,000 of those 55,000 were subscribers to a free email delivered information service and roughly 4,000 donors, 2,000 of which have been active within the past year as we started this initiative and what they wanted to accomplish.

Well, it wasn’t that they are similar from what a lot of non-profits want to accomplish in bottom line when they were approaching donor data improvement project.

  • They wanted to increase overall revenue as we all do.
  • They wanted to smooth out cash flow peaks and valleys meaning that there were certain times of the year when they were feeling a lot of stress because of the major time intervals between their fundraising campaigns. So, they wanted to try to ease that a little bit. And in doing these kinds of things,
  • They also wanted to reduce stress on donors and fundraisers. A lot of donor fatigue and a lot of fundraising fatigue. So, how do we go about doing that?

There are three parts to the story.

First, so sort of clearing for action. What we thought was necessary to do an assessment and get everybody on the same page.

Second part was actually taking action and we’ll go through all of the, some of the different things that they did to improve their donor data and some of the things that they were able to do as a result of that.

And then assessing impact, I mean, from a bottom line stand point – what did they get out of it? So, their story include all of those things. Shouldn’t take too long to get through and hopefully, you’ll find it compelling and interesting and related to your challenges.

So, in the first part clearing for action, what do we do, what was important here? The first thing we needed to do was decrease the noise in the database. A lot of information in the database, not all of which was relevant. Cleaning it up, getting into shape was necessary in order to determine what was really there and what wasn’t. They needed to better know their constituents, they needed to learn about best practices and engagement and getting trends and develop a plan and build consensus internally. So, let’s step through each of those a little bit in detail.

Starting with decreasing the noise in the database.  The first thing that they did was use queries to pull the data out of the constituent database. And that constituent activity and transaction records and they pulled it out into CSV files and then they did the analysis in Excel and Power BI. This offered them a better view into the data that they had in their current system allowed. And so, it was necessary to move the data outside of the system to get a real clear view of it. Particularly when it came to quality. So, that data was analyzed using a range of criteria and then we use the findings from that analysis to do a number of different things.

The first thing was just eliminate or consolidate duplicate records. That was a process in of itself. It was step through and prioritize fashion based on level of certainty that we had duplicate record and the importance of that constituent to the organization.

We eliminated outdated constituent gift coding, custom attributes, notes, anything that was no longer gonna be relevant, didn’t hold any value. And to that point, it was just about eliminating non-necessary data that was so inconsistent and collected in the past so that served as no better than what we sometimes call anecdata moving forward. The data was purged from the system and preserved only in a written narrative which was outside of the database. And that narrative just spoke to, might or might not be reasonably inferred from that data if anything. And all the data that was eliminated from the database was archived in CSV files.

So, what did that result in? Well, it resulted in a clean set of constituent data from which to generate accurate reports. Reports that were not needing to be filtered, merged or otherwise adjusted to account for the junk in the database. And that resulted in an honest view of what could be reasonably known about the constituents individually and as a whole from the data that was available.

The second step is learning more about the constituents. So, once you have a good idea of what was in the database, you kind of knew what you knew and didn’t know about the constituents. And previously, the organization had been frustrated trying to learn more about their constituents because they thought that they needed to store, gather all of that information directly from the full constituent group and store it all on the constituent records. What we end up doing was taking a different approach where we survey constituents to determine engagement behaviors, given behaviors, value proposition that the organization presented to its constituents. Everything from that ranging to their emotional needs to how likely they were to refer the organization to another potential constituent, all those different kinds of things.

And then we informed that information with demographic in constituent behavior data from sources that are readily available such as Google analytics and Quantcast and in addition to that, we helped develop a group of 30 key constituent stakeholders which included top donors and other high engagement and/or well connected constituents to provide additional input and achieve buy in from them on future direction. So, again, these are things that any organization could do. It doesn’t necessarily have to be costly or time consuming. It just takes a little know how. And you can learn these things and use them to drive your strategic and determine where to better improve your donor data as a result.

And then of course, in addition to learning what you can directly from your constituents and their behaviors, you kind of want to combine that with what the best practices are from the industry. Focused on such things as moving non-donors to donate, turning one time annual donors into monthly sustainers, increasing giving commitments etc.

And so there is a combination of again learning directly from the constituents themselves, but not in a way that required storing more data on the constituent record and then sort of informing that with best practices. And finally, you know, we socialize the findings internally. The outputs from the previous steps took much of the guess work out of what the organization needed to be doing forward in terms of its marketing strategy, in terms of its program alignment to constituent needs and in terms of its development strategy. In ways both obvious and subtle going through a discovery process like that increased accountablity because highlighted where ego, personal preferences, hunches or convenience were driving donor data decisions rather than best practices and the data itself. And because the finding is from the analysis were well documented and socialized, the result was the board members, executives, staff and even key constituents stakeholders were all on board. And that’s what really necessary to have good donor data within an organization. It’s cultural, to a large extent, and without the culture being right, it’s hard to implement the processes and the discipline and the systems that are necessary to do these kinds of things.

So, let me get to the action part. So, that whole first part was just about clearing the decks and making sure everybody was on board with direction. And as I said, we rely on marketing, development and programs to better serve the constituents, but today because this is about improving donor data, we are just gonna be focused on development specific examples. So, you can see here on the screen some of the things that we focused on. The many things and these are just highlights and we are gonna step through each of them in turn so, I’m not gonna read through what’s on the screen here.

So, the first thing that we really needed to do was reduce friction in the sort of subscription or registration and donation processes. So, a couple of things that we did there. One, we stripped the donation forms and the online registration forms down to their bare essentials and aligned them to industry best practices to achieve better conversion percentages. That was informed in part by what we learnt about the demographics of our audience, how they were engaging  online etc. So as best practice based but also attuned to this particular organization and its constituency. Previously, in the organization history, computing interest for marketing and development that weren’t grounded enough in industry best practices had resulted in a lot of fields being added to subscription and donation forms because that was viewed as a primary way that you could get information about constituents. That just way increased the friction and decreased conversion rates. The good news was that the survey data, that we didn’t previous, that we gathered in the previous phase provided enough direction and made gathering most of this information on a per constituent basis completely unnecessary. Or there would be opportunities later on to get that information from the most critical relationships. So, those were critical things that we did to reduce friction.

The second thing, and this was actually a big thing, was better handling of potential fraudulent transactions There is a lot of attempted fraud online these days, a lot of bots trying to hit your donation forms and so, that not only presents some technical challenges but it also can result in a lot of additional account management work for developers and fundraisers as well as a lot of need to do, handle charge backs and things of that nature for when fraudulent transactions are successful. So, we changed the payment gateway and that was key because the one the organization had before, it didn’t have good fraud reduction prevention controls. Better payment gateway with better and more configurable antifraud mechanisms. We also integrated some predictive analytics into the donation form and that, those two steps resulted in a couple of benefits. One was fewer false positives and fraud detection. One of the things that we learnt from surveying the constituents was that we had some foreign donors in Asia that were, had a strong preference for being able to make large donations on credit cards. And they had not been able to do so previously because the payment gateway was falsely identifying them as fraudulent attempts. So, we eliminated friction for some major donors who were trying to put some sizable multi-thousand dollar individual gifts on the credit cards. And so, we reduced the amount of false positives but also reduced the number of fraudulent transactions allowed and that dramatically increased the number of charge backs and refunds, excuse me, decreased the number of charge backs and refunds and also eliminated the number of junk transaction records that were getting into the database or dramatically reduce them.

The third example is just pushing the right call to action. On digital properties, we shifted the priority to getting people to register for a free information service rather than getting them to donate. Data indicated that with certain changes to use of promotional real estate or call to action available spaces on the website and social media channels, the subscription conversion rates would increase. You might of think as newsletter registration. So, why did we do that? Well, the data also indicated that the organization was much more likely to get donation from an information services subscriber than a non-subscriber. And that was because it entered the person into a value based dialogue or exchange of information with the organization. Having a minimum amount of personal information combined with some behavior data from other sources allowed for more personal fundraising messaging.

So, the key was not to get people to donate as the first action but to get them to provide some information and engage in a relationship and then they were much more likely to donate.

We also did better data, donor data analysis and segmentation. This was only possible to do reliably because of the way that the donor data had been cleaned up. And some of the tools that were implemented. It helped to identify one time or annual donors that might be converted to monthly sustainer donors. Allowed to us direct more personal messages encouraging donors to pledge recurring monthly amount representing a slight increase over their previous giving levels. Helped to ID major donors that might be willing to provide funds for matching campaigns and also identified high engagement non-donor constituents and help engage them in personal dialogue about becoming donors. And overall, we used the analysis of what the constituents wanted plus improved segmentation and analysis of the donor data that we had to make fundraising communications less frequent, more targeted and more value oriented.

So, we did work on improving integration and process automation part of that was about tightening the integration between the CRM and online marketing tools for better end to end tracking and analysis of online engagement. We also streamlined the process for constituent records management for data managers and improved the donors and that constituent’s ability to self-service their accounts or profiles online. And we also used automation to predict constituent and donor readiness to deepen the relationship based on their actions and then elevate that indication where development were for further cultivation and we simplified the process for processing refunds and making gift adjustments. So, those were all under the integration and automation heading. So much more that could be said there, but those are some of the highlights.

And then finally and this is sometimes the most difficult thing to accomplish at an organization is what the data management was like moving forward over a long period of time. So, you want to come up with processes and then consistently apply them. So, why was it easier to do? For one thing everybody in the organization was onboard whereas they hadn’t been previously. We had consistent application of fewer and better defined constituent gifting campaign codes which helped to simplify things for folks and improve reporting accuracy. More consistent use of action inside of the system and less frequent use of notes on constituent records. And the benefit of that was that people are now taking the time to record that data in more appropriate and more reportable fields on the constituent record rather than in notes. And in general more careful and consisting use of tools to keep the constituent data clean. To minimize the amount of incorrect data in the system, to keep duplicate free or at least as duplicate free as reasonable.

And now, we are gonna talk a little bit about outcomes before we move forward to questions. So, what did this get us? What did all of this work, these months of labor and this process get us? Well, the first thing was that one of the goals was to increase revenue, we did that. Average revenue increased in each of the next three years with by 10.5% with the biggest boost, 15% ,occurring in the first year post implementation of this plan. So, those are good results. Again that’s 10.5% on average year over year across the three year time span.

The second goal was to smooth out the cash flow, certain months of the year as everybody knows in fundraising, are harder to fundraise than others. You can have some months that pale in comparison to your peaks. July is just such a month. So, I’m using that as an example here. We are able to increase monthly revenue in other months as well, but July as an example. Where as the first year had an increase of 30% over previous years and that was sustained with additional slight increases over a couple of percent over the next each of the next two years.

And this probably was the biggest thing, increase in organizational happiness. Streamlining the fundraising messages, making them more confident of value oriented etc. was a really relief to the donors. They wanted to hear from the organization but they didn’t want to be on the receiving end of a beg quite so much. Didn’t want to be quite as pounded as much of fundraising messages. So, a lot of stuff that we could do there to improve their happiness and the results in follow-up surveys prove that we were successful in that.

And increasing revenue and improved cash flow and creating clear trust in the strategy and the process and the data resulted in development being able to spend more time in productive dialogue with donors and less time on customer service and records management and trying to tease accuracy out of the data and reports.

So, all of these things led to a more cheery, bright outlook, greater staff energy and the creativity and energy that came from that led to continued innovations to continue to advancing standards for donor data movement forward.

So, this is just a brief story obviously. There is a lot more that could be said about what was done with this client, what they achieved and the outcomes. But that’s as much as we can cover productively for this day. If you have any, if you would like to hear more about the story, feel free to reach out to us.

I’ll just go ahead and answer any questions that you might have. So, let me see, what’s been posted so far.


  • So, the question is, how did we get the organization to prioritize this work which probably took quite a bit of their time to implement? (22:45) That is a great question. I think that there was just a mounting frustration inside of the organization that the situation was broken and they needed to fix it and a general sense, partly from new people coming in to the organization, that they could be doing better. That pain was so acute that it resulted in an increased turnover, finally got to such a problem that the executives in the organization could no longer afford to ignore the situation. And it’s not that they were disinterested. Before they were just focused on other things. Mostly on program delivery. So, it was, took some time and education and to get the buy in. But again, doing some of these assessment or analysis projects up front, if the organization is open to doing that, can do a lot to get everybody on the same page because doing the survey of constituents for example and then asking similar questions of internal team members is a good opportunity to find out whether the internal team’s perceptions of the constituents and the landscape is the same or equivalent to the external constituents’ perspectives. So, that creates a lot of “aha moments” and helps to create buy ins for the additional energy.
  • Another question here is, (24:10) I believe, you said asking the target audience for personal information first before extending an ask for money, increasing the chances of them donating. Could you elaborate on that, what does that look like in a given campaign run via social media for example? I think I could elaborate a little bit on it by saying that a lot of organizations particularly that run a little bit more hand to mouth from a financial standpoint, are generally focused on the imperative of making the initial ask, money ask, and that’s just not the reality of how much of us engage in relationships. If somebody came up to you on the street and presented you with a very minimal amount of information and said, “Hey, would you like to hand me $5?” The answer is probably gonna be, you know, thanks but I just met you and that would probably be the polite version of the answer. So, generally speaking, putting the constituents in the situation where you’re exchanging something of value, getting them into a sort of a conversation with you, even if that’s mostly them being on the receiving end of the broadcast, gives them an opportunity to take an action and then you can follow-up after having provided that value with an additional request. So, it’s just about sequencing and moving the constituents through a journey that they can appreciate, that provides them with value of some sort, whatever that might be. And you can pursue the same step through social media. Making sure that you initiate the conversation based on a mutual exchange of value before taking into the ask phase.
  • Yeah, another questions that we got before the start of the webinar was (26:03) How do you convince executives to pay attention to this kind of stuff? And I’ve already spoke to that question a little bit but specifically what can you do to help convince executives or higher ups inside the organization. Well, you could share this story with them. You could find other stories that demonstrate how better donor data can lead to improve outcomes. Where possible, identify clear relatable industry benchmarks that help support the case for change or statistics from case stories such as those that I’ve shared today that could help to make the case for change.
  • Another question that we received early on Is improving donor data expensive? (26:50) That’s a great question. The answer is that it can be very expensive. But a lot of good donor data relies on culture. The willingness to be informed by best practices and the discipline to apply them internally. So, technology is rarely the only problem and sometimes it isn’t a problem at all. It starts with leadership and organizational culture and getting that right can dramatically reduce the cost that come downstream. So, there are a lot of ways that you can control costs and data improvement processes. But there are solutions even if they won’t get you all the way there for all sizes of organizations and all different kinds of budgets. There is always something that can be done to improve the donor data and I think that this case story was an example.

This client was using sophisticated systems. They were using custom homegrown solutions with limited functionality. Then that presented some challenges in terms of limiting the number of features available to do the data clean up. The compensation for that was it gave more direct access to the constituent data in the database. In general, this case story is indicative of what an organization can do without spending a lot of money. There was very little expense spent relative to the benefit. And we have seen similar projects done without a lot of expense, you know, cash out lay so to speak in the Raiser’s Edge, Donor Perfect, Salesforce and other CRM systems. So, yes these projects can be expensive but that was not the case for this particular case story. Although, it did require some internal time and a little help from outside consultants. But it was not critical expense for the organization. It was usually absorbed into their budget.

So, those were all the questions that were posted and we are currently at time for this webinar. We have been trying to keep them shorter, at least once per quarter  to make it easier for you to work it into your schedule.

Again, if you have any follow-up questions or anything that you would like to discuss, please reach out to us. You can reach us on Twitter at Buildconsulting. You can also go to the website, or this is ( and use the contact forms.

So, thanks everybody for participating today. It was great to spend the time with you, I hope you got value out of it and have a great day.

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