Analyst Heaven

Analyst Heaven

I was imagining what heaven might look like for us fundraising analysts. By and large, fundraising analysts lead good lives here on planet earth. We help causes that really matter. We get to work indoors. Often, we can even work from home. We get to use our brains a lot, and fun tools like laptop computers and cool software like SPSS. However, the absolute bane of our existence is the abundance of really crappy data. The unglamorous fact of life for a fundraising analyst is that we spend most of our time trying to figure out whether the data we are working with is fit to analyze. The Great Lie is that a new CRM system or data warehouse will fix your crappy data problems. Short of a transcendent visit from the Data Angels, the only thing on this side of heaven that can fix crappy data are smart people who are willing to dive into messy databases and make sense of it all. My hope is that if and when I get to heaven, all the donor data will be spotless, and the channel coding will be standardized. What sweet hope this sentence...
The Bi-Polar Future of Fundraising

The Bi-Polar Future of Fundraising

There are two fundraising models that are heading in opposite directions. The traditional model is that you invest in new donor acquisition and then work to build a long-term relationship with those donors who, in turn, will faithfully support your cause. The emerging paradigm is a point-of-sale model, where an organization realizes all of its LTV with the donor’s first gift and no possibility of an ongoing relationship. One model is relational. One model is transactional. I see the industry struggling to “convert” transactional donors into the relational model. My sense is that this could be an expensive and futile effort. Rather, I believe the better approach may be to create distinct strategies optimizing each of these two very different fundraising...

Make Statistics Understandable

Kent (the resident numbers/strategy guy on Veep): [on the news coverage of a salmonella outbreak] “The number of people taken ill is orders of magnitude below statistical significance. Do people not understand basic nonparametric statistics?” While those numbers folks – and aren’t ALL marketers numbers folks? – among us may laugh at the quote above from the show Veep, I’m reminded constantly how true it is – People do NOT understand basic nonparametric statistics. And we shouldn’t expect them to. As we look back on 2016 and start 2017, I’m reminded constantly that our clients, our board members and our executive directors are not all numbers people. So, our job is not just to do the analysis but to make the numbers make sense. To find what’s hidden within the numbers and to use that to drive the strategy. Then we need to explain clearly to everyone The What and The Why. It’s interesting that Kent’s title in the White House is “Senior Strategist”. Perhaps political strategy focuses too much on polls and on numbers to drive every decision. But often the rest of us focus too little on those things. We marketers can help to fix that by making the numbers make sense. Then they can drive the...

Let’s Get Small?

As we kick off 2016, I have a question for you. Let me set the context. In the past decade, we’ve witnessed many of our clients migrate from micro-computer based fundraising databases to CRM (Constituent Relationship Management) cloud-based databases. And for 10-years we’ve seen many of these organizations’ ability to leverage their data for insights decline. Rather than the CRM serving the nonprofit, it seems like the nonprofit now must serve the CRM. I still find this so ironic and frustrating. I know it’s not any one CRM or any one client. I think most every organization underestimates the commitment of undertaking migrating to a CRM. They also underestimate the cultural change required to harness the power of CRM – which includes adding highly trained (and highly salaried) fundraising professionals to run it. Most organizations understand the need for CRM and are willing to swallow the expense of the database infrastructure, but in my experience, too few organizations have been willing to cover the cost to train their people adequately or add CRM professionals who know fundraising to their payrolls. It’s like building a fancy new library, filling the library with books, magazines and periodicals, and then not hiring any librarians. OK, that’s my long-winded setting of the context. Here’s my question: Do you think organizations will one day abandon their failed CRM adventures and return to micro-computer fundraising databases? Love to hear your...

A Data-Driven Life

I recently heard a commercial about a mattress that gathers data on how you sleep. The commercial says: “What if you could really know? Know how you sleep at night? Know how your day affects your sleep? Know how to get the best sleep of your life every night? Now you can.” The commercial goes on to say that its Sleep IQ technology tracks how you sleep. When you wake you’ll know exactly how you slept – how long, how restful your sleep was, whether you moved or got up. The assumption is that you’ll use this data to make changes in your life – how and when you exercise, what time you go to bed or get up, even whether you go out or stay in for the evening. We see this more and more in our lives with the popularity of Fitbits and other wearable technology – we’re now using data to make better and healthier decisions about our lives. Are we doing the same with our nonprofit fundraising programs? Are we using data to see how small or large changes in our fundraising strategy affect the overall “health” of our revenue and our donor files? Are we using statistics to drive what we’re doing? If not, since now even our mattress can track data so we can make lifestyle changes … Why...
What is a model? (Part I)

What is a model? (Part I)

Since I started with Analytical Ones 6 months ago, several very smart people have asked me “What exactly IS a model?” It’s a word that gets used a lot in fundraising – for Major Donor, Planned Giving or Direct Mail Response Models – but a lot of people understandably don’t really “get” how modeling works. Let’s say that you want to predict who your next Major Donors will be. So you do a wealth append to your file and you make a list of everyone with a Net Worth of $5 million+. Those are your Major Donor prospects. That’s really a model with one variable – Net Worth. You’re using the one variable of Net Worth to predict your next major donors. But, there are a lot of issues with just using that one variable. What if that donor has only given to special events or what if their last gift was a really long time ago? What if there are other factors that mean they don’t have much expendable income despite their high net worth? How can you find that out without a lot of extra digging? Instead, to get a more accurate tool for predicting your Major Donors, let’s say that you want to look at a large list of possible variables (or characteristics) to see which of those variables are most important and how all of those together predict who will be your next Major Donors. That’s where a statistical model comes in. By using statistical modeling you can look at a number of different variables – for example: length of time on the donor file,...