data-driven

The Top 3 Things You Need to Do to Smooth Your CRM System Implementation

#3: Don’t overlook change management. What? Change management? That fluff? Come on, we’re all adults here. We’re all professionals. We don’t need change management. We can count on everyone to support the effort and do what they’re supposed to do. We hate our current system and cannot wait to start using the new one. Wrong. I recently trained a large number of users in preparation for a go live, and I had a number of students who could out-pout my 9-year-old daughter. It sounds funny, but it’s not. I’ve encountered this kind of behavior with every client I’ve ever worked with. Passive-aggressive behavior like that, which probably showed up at other points during the implementation project, can lower everyone’s morale and inhibit buy-in. Getting real buy-in is key to getting back up to full speed quickly and realizing the expected ROI that drove you to make a change in the first place. Such behavior slows and lowers the quality of decision making during the implementation as well. Address it proactively and continuously.

#2: Train Train Train. I can’t emphasize this point enough. I have yet to see an organization anywhere that provides enough training for its staff, and this applies generally – I’m not limiting this to training users on a new system. Typically the majority of users-to-be of the new system get a few training sessions right before going live, which is not nearly enough to have them ready to do their jobs only a week or two later! Hand-in-hand with involving staff strategically throughout the project (which is crucial for adoption) I recommend providing training early on (and again before going live, of course). What I most commonly see are staff who are pulled in sporadically to help with some piece of the project – process testing, validation of converted data, etc. – but who struggle and get frustrated because they don’t know nearly enough about the basics of how to use the new system. Providing the opportunity to get genuinely comfortable with the new tool early on leads to more engagement throughout the implementation process as well as higher confidence and competence when things get real.

#1: Dedicate people resources. The biggest thing that organizations do not anticipate and are not prepared for is the massive workload created by an implementation (and, often, by the ongoing demands the new, more powerful system creates once live; you’ll probably need to staff up permanently as well.). Expecting key staff to balance the demands of their day-to-day jobs with those of the project leads to a great deal of stress, and neither priority is fully served. Get help – dedicated project staff and consultants can not only balance the burden, but the right expertise will help your organization have a much more successful experience.

Be sure to join me and my Zuri Group colleagues at the 2015 AASP conference in Chicago next month. I’ll be speaking on this very topic – successful CRM system implementations. I hope to see you there.

Brandon Ferris
Senior Director of Strategic Services and Fundraising Counsel
Web:               Zuri Group
E-mail:             brandon@zurigroup.com
Twitter:            @datadrivenbf
Blog:                datadrivenfundraising.com

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Are You Getting Worthwhile ROI from Your Events?

This article from The Chronicle of Philanthropy is quite good. Although I was not primarily an event fundraiser, staffing cuts eventually left me directly in charge of a major annual gala (whereas I had previously been one level removed, having a direct report who supervised the event.). Even before I assumed direct responsibility I was painfully aware of one of the unpleasant aspects of events: Usually you only hear complaints, and lots of participants have lots of strong opinions which they are very happy to share, often with rather less sensitivity than they might normally bring to a conversation. I found events to be rather like publishing annual reports of donors: The best you could hope to do was not to tick too many people off.

One of the things I like about the author’s suggestion is that this framework can be applied proactively rather than reactively, which, for me, softens the blow of “feedback.” It also serves to (try to) keep participants focused on improvements and solutions, rather than blame.

Beyond this, the article got me to thinking once again about something that never sat well with me – the typical assumptions made about the value and impact of events beyond their direct financial impact. Everyone knows that events are an extremely “expensive” form of fundraising. At my old independent school, the “real” net income from our annual gala auction, after expenses and salaries (that’s right, I always included the cost of staff, which sometimes gets excluded from the calculation) ended up being only about $25,000 per year.

When this fact was pointed out to leaders (Head of School, board members, influential parent volunteers), the typical responses included well-known “axioms” about the importance of friend raising, getting parents involved as volunteers, etc. Another frequent claim, which relates to the point I want to raise here, was that getting people to give via the auction was a “gateway” to additional giving, particularly to the Annual Fund (which is extremely important in the independent school world, since at most schools it fills a planned hole in the annual budget – the so-called “gap” between tuition and the actual cost of educating a student).

Even though the auction itself was not very lucrative, how could anybody argue with getting new donors?

As it turned out, this anecdotal connection between the auction and other forms of giving turned out to be purely anecdotal.

As in 100% anecdotal. As in 0% true.

I had relatively limited data, but when I looked at the three-year period for which I had complete information, I discovered something quite shocking: The top 20 auction donors (a subset of whom were the lead volunteers) had given, over the same three-year period, a grand total of $0 to the Annual Fund.

That’s right, zero.

I am not making any universal claims about the connection or non-connection between event giving and other forms of giving. I should think this case was at least somewhat unusual. What is more, your organization’s event may produce relatively excellent net fundraising results. A cost of 30 cents per dollar raised (assuming it counts salaries) is pretty easy to swallow when your event grosses $1,000,000. However, what I am suggesting is that it would be worth a bit of time and effort to try to analyze the larger ROI of your events, especially if you are not seeing significant direct financial returns.

When I build custom predictive models for clients, I always look closely to see if there is a statistically and practically significant correlation between event attendance and overall giving. Even if you can’t carry your investigation that far, consider simply looking at your large event donors and their event giving vs. direct (non-event) giving, and see where the information leads you. What would you do if you found that your events provided minimal direct and indirect ROI?

Brandon Ferris
Senior Director of Strategic Services and Fundraising Counsel
Zuri Group
brandon@zurigroup.com
@datadrivenbf
datadrivenfundraising.com
www.zurigroup.com

Stop Tracking Events in Spreadsheets!

“Shadow databases” are a very common problem in the advancement industry. Whether data is stored in home-built MS Access databases, third-party CRM systems, or just Excel files, having some of your institution’s data stored anywhere other than the database of record poses a number of obvious challenges:

  1. Limited access to useful information
  2. Biographical data not being updated everywhere
  3. Incomplete picture of constituents.

It’s item #3 I’d like to address in particular, given my focus on data-driven fundraising. In order to use data most effectively to drive strategic advancement outcomes, the data must be accurate – that goes without saying! When data is spread out in multiple locations, it’s just about impossible to keep it up to date everywhere, and this compromises the overall quality.

When key data are not stored in the system of record, which reduces the “completeness of the picture,” your ability to do data-driven fundraising can be even further compromised. Consider one of the most rampant cases of “shadow data:” Events. A tremendous number of institutions fail to track some (or, sometimes, any whatsoever!) of their event data in the CRM system of record. There are various reasons. Some CRM systems offer limited capability, but in quite a few cases, it’s due to lack of training and/or a lack of commitment to ensuring that event data are properly captured. It takes some effort to get it all into the database, and instead it often languishes in spreadsheets.

From a data-driven fundraising perspective, event data are extremely useful. Event attendance almost always shows a strong statistical correlation with giving, so if you don’t have accurate, accessible event information, you cannot include that data in any efforts to predict giving.

So I say, stop tracking your events in spreadsheets, if you have the necessary tools to track them in your fundraising system. Get professional assistance, if necessary, to help you figure out how best to do it, to train your staff, and to develop consistent policies and business rules for managing event data.

Brandon Ferris, Senior Director of Strategic Services and Fundraising Counsel
Zuri Group
@datadrivenbf
brandon@zurigroup.com

Letting Go of Sacred Cows: The Danger of Being Data-Driven

So you want to become more data driven, right? Everyone does. Everyone is sold on the power of analytics to enable smart, data-driven decision making to improve organizational results. I don’t think it’s entirely unfair to say that terms like “big data,” “analytics,” and “data-driven” are so deeply ingrained by now as to approach buzzword status (not a good, thing, of course!).

But are you really ready to be data-driven, to go wherever the data leads you? It’s often not as easy as you might think it should be for people and organizations to allow data to guide their decisions, tactics, and strategy, especially when the data contradict something they just “know” to be true. Aren’t some things simply given? Simply and obviously true a priori? We all hold these kinds of “convictions” about something, and when we encounter data that contradict what we “innately” know we naturally resist and find ways to rationalize the data away.

There was a perception at an independent school for which I worked (in advancement) that the school’s culture and programs were not adequately “girl-friendly,” which was driving increasing attrition among female students, particularly at the key transition point between grades 8 and 9 (it was a K-12 institution). There was considerable speculation, particularly at the Board level, about what needed to be done to fix the problem. Not atypically, there were some loud voices on the board seeking to push various pet programs, which their advocates intuitively “knew” would improve results.

It happened that we were working on an institutional research project for admissions, and we had enough data to take a look at gender and attrition. We needed to quantify the problem of accelerating female attrition before we could look for correlations. What we found was that there was no particular female attrition problem. In fact, the retention rate for female students was slightly higher than that for our male counterparts. What was really happening was that way back at the start of the pipeline, in grades K, 1, and 2, the balance of students was 60% male, and that balance largely held all the way through. Not exactly something that should have been hard to notice or uncover, but the perceptions were established and this was overlooked.

Did this “revelation” put an end to the calls to add a cheerleading program to the upper school (one board member’s solution for making the school a better place for girls)? The title of this piece provides a hint. The certainty about the female attrition problem survived unscathed. We would like to think we are fundamentally rational beings, but it is hard to let go of closely-held beliefs, no matter how information points in another direction.

What does this kind of resistance to what the data are telling us look like in advancement? It takes many forms. Here are a few I’ve seen recently:

  1. Continuing to mail the same number of solicitations annually to a large pool of never-givers, despite models that suggest de-emphasizing a population and re-directing resources to more likely constituents.
  2. Spending significant gift officer time on statistically low likelihood prospects who have extremely high wealth ratings (yes, it’s fine to make a discovery call if the prospect will take an appointment; but at some point it’s time to move on).
  3. Allocating significant personnel time to maintaining some sort of “extremely important” constituent list, despite not knowing whether there is any correlation with giving (and sometimes, even knowing that no such correlation has been found).

Some people have very little difficulty accepting data-driven conclusions that run counter to accepted wisdom; in fact, some people enjoy the power of data to undermine unexamined assumptions. I know I find it quite exciting. But I’m sure if some Sabermetrician showed me advanced statistics indicating that up to this point in his career Novak Djokovic has been a better player than Roger Federer during a similar interval, my first reaction would be something along the lines of “that’s not what I’ve been watching.” But, as a data-driven fundraising practitioner and consultant, I would have to shrug that off quickly and listen to what the data have to say. In the end, our biases can be overcome, but it does take a degree of conscious effort and repetition. If you’ve made a commitment to becoming a more data-driven fundraising organization, you’ve taken the first step. Remind yourself to hold opinions lightly and to be open to the messages in your data.

Brandon Ferris
Senior Director of Strategic Services and Fundraising Counsel
Zuri Group
http://www.zurigroup.com
@datadrivenbf
brandon@zurigroup.com

Driven Mad by Over-Segmentation, Part 1: Key Questions

Segmentation is a given in any annual giving direct mail solicitation effort. Everyone knows you need to tailor the message to the audience? Right?

Maybe. Of course no one would dispute the value of tailored communications, but in my experience in the fundraising world I’ve seen a lot of untested assumptions and a lot of incredibly complicated (I would argue excessively complicated) segmentation, sometimes seemingly only for segmentation’s sake!

At the heart of the matter of annual giving/direct marketing in the fundraising business are three common (and fairly obvious) objectives:

  1. Raise as much money as possible.
  2. Minimize solicitation costs.
  3. Analyze results and refine tactics accordingly.

Splitting constituents into segments based on one or more shared characteristics (e.g. alumni vs. parents vs. staff, LYBUNT vs. SYBUNT vs. non-donor, school of law vs. college of arts and sciences, grateful patients, and myriad combinations of all of these) is the primary strategy for achieving these objectives. A tremendous amount of time, effort, and, often, frustration goes into producing these segments (not to mention money. The more variable the content, the greater the cost typically is to produce and deliver a mailing). You’re likely very familiar with how long it takes and how hard it is to produce segmented mailing lists such that each constituent lands in the correct segment within your defined hierarchy and lands in only one segment. Then there are issues with two constituents in the same household in different segments….. And so on. It can get a bit crazy.

I think we need to pause and ask two basic questions:

  1. Do we really know whether we’re getting meaningful ROI on our segmentation?
  2. Are we even set up to determine the answer to #1?

These are fundamental questions for any advancement operation that strives to become more data-driven, and I will explore them further in my next post on this subject.

Brandon Ferris, Senior Director of Strategic Services and Fundraising Counsel
http://www.zurigroup.com
@datadrivenbf
brandon@zurigroup.com

“Small Data:” The ONE Piece of Analytics Every Fundraiser Should Know

The phrase “big data” is everywhere now. Most of us are so well aware of the amazing things companies like Google and Amazon are doing with the oceans of data they collect about us that we’ve come to expect this level of sophistication to be the norm. Most nonprofit organizations aren’t able to collect the amount or kind of data the giants can, but they can still use analytics very effectively to achieve better fundraising results.

Because big data and everything associated with it has become such a part of popular consciousness, I believe that our industry has come to:

  • Expect too much from our data. We simply do not have the ability the collect the amount or type of data that Google does.
  • And yet, in opposition to the bullet above, overlook some very fundamental and useful data we have at our fingertips.

The latter bullet is the one to which I refer in my title. To find out whether you know the ONE thing I’m talking about, try to answer this simple question right now:

What percentage of the constituents in your database have NEVER made a gift to your organization?

That’s it! Simple enough.

You’re forgiven if you have to run a query to get the answer this time, but I would suggest this should be top-of-mind knowledge from this moment forward. Why? Because knowing this critical piece of information and using it to inform fundraising business decisions is the first step in becoming a data-driven fundraising operation.

Here are four things you can do with that simple piece of information that will save money, improve fundraising results, or simplify your operations:

  1. Reduce the number of times your long-term never givers are solicited each year.
  2. Rank long-time high capacity never givers lower than other high capacity prospects when making assignments. This is especially important when you wealth screen thousands or tens of thousands of records.
  3. Purge the oldest records of never givers from your database if you can (not alumni, for example).
  4. When you do send an occasional mass appeal to the oldest never givers, craft a message that emphasizes participation over high ask ladders.

You’ve probably already come up with more ideas. These may sound like obvious decisions to make, and yet I still commonly see a proclivity for “shotgun” tactics aimed at everyone in the database. If you cannot start with simple tactics such as these, it will be that much harder to achieve higher levels of sophistication and take full advantage of all the power your data has to offer.

Analytics-based fundraising, data-driven fundraising, call it whatever you like, is fundamentally about prioritizing your resources and efforts – targeting your dollars, time, and people toward the prospects most likely to make the biggest impact. Start with small data and build your way toward becoming a data-driven fundraising team.