Tag Archives: donor analytics

Can you Achieve Faster-Better-Cheaper Profiles?

4Fundraisers, 4Researchers, , , , , , , , , , , , ,

“I need a profile on this person today…can’t you just Google it?” It’s the kind of question that makes prospect research professionals cringe. But why shouldn’t a development officer want it faster, better, and cheaper? Why is your organization paying thousands of dollars a year for research tools if it still takes forever to get the information needed?

So what’s happening to cause this disconnect between development officer and prospect researcher? I suspect there a few causes, but first, let me tell you a story…

As a consultant I charge a flat fee for projects. I want my clients to be able to budget, and as a professional I should have a fair idea of how long it will take to do the research. Profile-type research falls into this category. And it’s this kind of pressure that keeps us razor sharp. It’s me and the team against the clock!

That’s how I “rediscovered” one of my favorite tools the other day – DonorSearch.net.

Faster-Better-Cheaper with DonorSearch.net

At Aspire Research Group we’ve taken on a few new clients that, in addition to standard profile research, needed some “situational” research done. Things like prioritizing, quick checks to be sure assigning for a visit is appropriate, or key items researched to prepare the president. So I asked myself, “How could we manage our time researching, keep up the high quality of information, and make it the right price?”

In my quest, I took a fresh look at our tools and settled on DonorSearch to start our projects. Of course, being able to upload a small batch of names for a prospect screening is a time-saver, but even when we entered only one name into the Integrated Search, suddenly everything was at our fingertips. DonorSearch had made so many updates to their product – the combined result meant we could be very competitive.

For example:

  • Time Management: The big name family business was clearly the source of wealth, but why was the prospect not listed on the website? Open Corporates in the Integrated Search demonstrated a long list of companies where he was a director – many with the same word in the name. From there a quick Google search revealed his specialty in the family business. Faster.
  • High Quality: There was a large, outlier gift to an organization with a strange name. I didn’t want to put it in the list without checking, but didn’t want to have to do a distracting search. A click on the source link gave me a searchable PDF – and lo and behold – it was an organization with a mission similar to the client! Better.
  • The Right Price: By letting the tool do all of the upfront “grunt” work finding relevant information we spent less time gathering and more time thinking, and that meant we could charge the right price. Cheaper.

Ask the Librarian: Can’t you just Google that?

But if you really want your research to achieve the business mantra of better-faster-cheaper, you need more than a great tool like DonorSearch. You need to start with a really good understanding of the need and continue with really good communication throughout.

So why do researchers get asked to Google it in seconds flat? Let’s go ask the librarians! Librarians are trained to interview the customer. When you go to the reference desk, the librarian has to figure out what you are trying to accomplish and then help you navigate your way to success.

While we don’t view the reference librarian as an expert on the subject matter that brings us to the library, we do view the librarian as someone who has received training in library science and is an expert on helping us find information. The librarian is a professional.

The “just Google it” request suggests that any amateur without training can perform quality prospect research, which can be insulting … but it also happens to be a great opening for a really good conversation to clarify the  problem to be solved.

Professionals are Always in Demand

The more that software tools are able to do, the more important prospect research professionals become. Librarians don’t worry that books will put them out of business!

And on the flip side, the more that software tools are able to do, the more we must use our communication and problem-solving skills to provide flexible, custom solutions.

If you manage a prospect researcher, if you are a prospect researcher, or if you want to be a prospect researcher, you can arrive at better-faster-cheaper profile research if you recognize the importance of great training (including communication skills) and tools. It’s what qualifies us as prospect research professionals!

More Resources

To Advocate or Not to Advocate – there is no question!

4Researchers, , , , , , , , ,
advocate
“Advocate” by Nick Youngson, is licensed under Creative Commons 3 – CC BY-SA 3.0

Something big and very exciting is happening in the field of prospect research. It is at once both thrilling and terrifying, but then again, the best things in life usually are! Do you know what I am talking about? Prospect research has become the center of attention concerning the use and abuse of data in nonprofit fundraising.

The Thrilling Aspect

For years prospect research languished in basements, yearning for that exclusive seat at the leadership table. Thrillingly, prospect research professionals in the U.K. have been thrust into that seat with all the anticipation of slowly ratcheting up the roller-coaster-mountain and the subsequent terror of being dropped with a 5.5 G-force speed down the other side.
. 
It’s official. Data is a big deal. And the guardians and operators of data in non-governmental organizations (NGOs) are prospect research professionals.
. 
So after working long and hard behind the scenes, after advocating to fundraising leadership for the use and respect of prospect research, we have arrived at the leadership table. And my, what an entrance we have made!

The Terrifying Aspect

In the U.K., the Information Commissioner’s Office (ICO) has been fining charities for violations of the Data Protection Act 1998. The fines have ranged from a low of £9,000 to a high of £25,000. The IOC has done a lot of interpretation of the Data Protection Act 1998, and has surprisingly used emotional language.
. 
The fines include best practices in prospect research such as the following:
Is this the end of prospect research in the U.K.? I doubt it. There will be changes as NGOs adapt their data and privacy policies to carefully reflect their fundraising practices. Some NGOs will even seize this as an opportunity to share their fundraising “data story” with the public.

New Perspective Fueled by Advocacy

After this terrifying plunge, the interpretation of the Data Protection Act 1998 by the ICO may shift as NGOs, fundraisers, prospect researchers, donors, and other constituents react and lend their voices to the conversation. For example, the Institute of Fundraising issued a report, Good Asking, exploring why charities research and process supporter information.
 .
On the other side of the Atlantic Ocean, instead of a tightening of data privacy, the U.S. has been experiencing a loosening of data privacy. On April 3, 2017, President Trump repealed a set of privacy regulations requiring “internet service providers to request authorization before selling sensitive customer data to advertisers, or using that same information for marketing campaigns.” (Click for article)

What Can You Do? Advocate!

Whether you are in the U.K., the U.S., or any other country, we prospect research professionals are most often the guardians and operators of fundraising data in our organizations. We may have little or no leadership authority (yet), but that doesn’t mean we can’t advocate for our profession and for solid data practices – before we find ourselves the subject of unflattering news headlines.
. 
It’s easy to say we should advocate, but what might that look like in real life? Following are three steps to help you advocate effectively:
  1. Define the change you desire. Just as in goal setting, clearly defining the change you want to effect is important. Are you advocating for the creation of a data privacy policy, or are you advocating for your prospect research position or department?
  2. Determine your strategy. Strategy comes before tactics. Who needs to be persuaded to make change happen? Where are the obstacles to the change you seek?
  3. Craft your tactics. Tactics are the kinds of actions you take to fulfill your strategy and effect change.
Consider the story of Suzanne Harris at the Philadelphia Museum of Art. It is a classic case of advocacy gone right! Suzanne wanted to introduce RFM scoring. She talked up RFM scoring and quoted gurus in the field. She built a relationship with IT to create an automated score that could be refreshed. Then the Development Department threw a party for all staff, on a day fundraisers were likely to be in the office, and used games to educate and demonstrate the value of the new scores.
. 
Advocacy isn’t just for associations or organizations with a cause. It’s something all of us do all the time. We advocate for a raise, to have dinner at a certain restaurant, or to visit somewhere special for vacation. Advocacy becomes more complex when there are more players and procedures in between the current status and the change we desire.
 .
Considering the level of strategic complexity we navigate when we provide insights in prospect profiles, analyze prospect portfolios, and perform data mining, we can handle advocacy!

More Resources You Might Like

Researching Public Company Wealth

4Researchers, , , , , , ,

golden-dollar-1703161_1280Public companies create an enormous amount of wealth in the United States. Having the designation as a public company insider is a neon-lit indicator for high net worth!

According to the McKinsey Global Institute, the consultancy’s research arm, 10% of the world’s public companies generate 80% of all profits. In 2013, the Fortune 100 biggest American companies were responsible for 46% of nominal U.S. Gross Domestic Product (GDP).

Where are the Public Company Insiders?

That is a lot of wealth! But the reality for most prospect research professionals is that the majority of our major gift prospects are going to generate their wealth through private companies. Why is this true? There are many reasons, but the chart below is a fun visual for one big reason!

 

 

Most nonprofit organizations are small relative to the heavy-weights at the top of the nonprofit sector. Universities also have the advantage of teaching the extremely successful to become that way, which frequently creates a strong affinity.

The combination of smaller operating budgets and a weaker path to affinity means that unless you research at a big organization or institution of higher education, you probably won’t come across too many public company insider prospects. There just aren’t that many of them to go around.

However, within this reality, public company prospects are a gold mine of learning opportunity!

The Old Way of Learning Donor Profile Research

Most of us entered the prospect research field as generalists. We have earned a wide variety of graduate degrees, have held jobs in a wide range of industries, and we often find financial filings to be incredibly opaque and confusing! To top it off, we have to learn how to do profile research on our own, with a hodgepodge of brief trainings if any at all.

The result is that we often face a topic as complex as public company executive and director compensation packages as a checklist task. We learn a series of actions to take to value and present the information and approach each prospect the same way, occasionally adding new learning when prospects differ.

Public companies provide us with the opportunity for a new approach.

The New Way of Learning Donor Profile Research

Public companies offer us an unfettered view of the compensation structures for their directors and executives. We can also make qualitative and quantitative comparisons of the company and its compensation packages. These two facts create a rich learning opportunity for the fundraising research professional.

When you take the time to learn and understand the reasons behind the compensation packages for public companies you can begin to apply this understanding to the ways private companies create wealth for their share owners. You can compare and contrast the public company with the private company.

Most of us in the prospect research field are not ultra-wealthy. It can be extremely difficult to imagine the wealth of a public or private company share owner. Learning how public companies create wealth for their executives through compensation packages, including company stock, gives you a strong foundation to improve and build upon your ability to value all company holdings and calculate capacity ratings.

Where Can I Learn This Kind of Information?

You can find all manner of free learning online. Khan Academy offers a free Finance and Capital Markets series. Coursera offers a free Business Finance series of courses. There is no shortage of ad hoc material on YouTube as well!

The downside to what is available for free is that it is not focused on fundraising. Because of this, the concepts being taught can feel mostly irrelevant. While you want more than cursory learning, you probably don’t need to learn everything there is to know about buying and selling stock and bonds.

There are fundraising-focused webinars, articles, and blog posts from the Association of Professional Researchers for Advancement and consultants in the field, but these often don’t explain the reasoning behind the compensation structures or how this kind of wealth can turn into a gift. They are by nature brief and not comprehensive.

Out of frustration with this situation, I helped create a comprehensive, 5-week course introducing prospect research professionals to the world of public company compensation. It was exciting to pull all the pieces together and create a safe space in an online classroom to have conversations about researching and fundraising with public company prospects.

Public company insiders may not show up on your prospect list terribly often, but I’m suggesting that if you view them as an opportunity to deepen your knowledge about wealth creation, they can be a rich learning experience that will deepen your research and fundraising skills generally. What are your thoughts? Do you agree?

More Resources You Might Like

Net Worth: Nasty, Nice, or Neutral?

4Researchers, , , , , , , , , , , ,

cash-1169650_1280There was a cry for help on the PRSPCT-L list-serv: “I’m a new researcher and my boss wants me to provide net worth on a prospect. He says it was the previous practice to do this and I can get what I need to calculate it from Dun & Bradstreet.” What would your response be?

To begin, a simple definition of net worth follows:

Assets – Liabilities = Net Worth

The Three Common Responses to Net Worth

If you mention “net worth” in the prospect research field, you will likely hear one of the following three responses:

  1. Don’t do it! Or you will be voted off the prospect research island!
    .
    The argument against estimating net worth is usually this: If we cannot find or know the values of all assets and liabilities (which of course we cannot), then we have no business estimating net worth. This is often a strong, unequivocally held opinion.
    .
  2. Hide that you are doing it by using another term or keep it behind the capacity rating calculation.
    .
    This is the most common practice in our field. Instead of using the words “estimated net worth”, researchers rephrase with a term such as “estimated wealth”. Even more common is to use the results of wealth surveys, such as the chart on page 19 of the Capgemini 2016 World Wealth Report, to estimate net worth based on a known asset such as real estate and then take a percentage of estimated net worth as the gift capacity.
    .
  3. Boldly present estimated net worth.
    .
    There are researchers who feel comfortable presenting estimated net worth. Some provide disclaimers or educational explanations to communicate better generally or to clarify outlier situations.

Easy Formula, Tricky Calculation

Assets – Liabilities = Net Worth

The formula looks so simple, but this is deceptive. As prospect research professionals we know that we can’t discover and value all of a prospect’s assets or liabilities. It is the reason we use the word “estimated.”

Among the challenges in estimating net worth, there are two that jump out quickly:

  1. Many assets (and liabilities) are troublesome to value – none more than private company ownership.
    .
    I have discussed the difficulty of private company valuation before. A common route to wealth is to start a private business, and many of these successful entrepreneurs want to “give back”, among other motivations for giving.
    .
    And it brings us back to our fellow researcher’s list-serv plea. Dun & Bradstreet (DNB) sells data, including estimated values of a private companies. Assuming we know how much of that company our prospect owns, we could use the DNB dollar amount to estimate the prospect’s ownership value. Or could we? DNB uses its own formulas to estimate and can be very far off the mark.
    .
  2. Are we talking about titled ownership such as a name on the deed, or influence over money, such as sitting on a grant-giving family foundation board?
    .
    Our prospect could be a child of a wealthy family with very few public assets identified. And yet, we may find she has influence over millions of dollars in a family foundation. Estimated net worth and gift capacity clearly diverge at this point. You might estimate a low net worth, but still consider her to have a million dollar gift capacity because of her influence over grant giving.

Logic and Emotion – Let them Collaborate!

There is nothing simple about money. Money is one of the most emotionally volatile topics you can discuss, and those emotions flow into the workplace. Addressing your own emotions and biases about money is the first step.

You might want to seriously consider whether your difficulty imagining the wealth of multi-billionaires is affecting your ability to logically estimate net worth or gift capacity – and whether you have negative emotions attached to great wealth accumulation. Emotions are not your enemy. Ignoring them is.

Now you are ready to balance how you and your gift officers “feel” about your prospect’s potential wealth with the logical, quantifiable assets and liabilities found in the public domain.

Following are the most frequently used tools or ratings:

  • Estimated Net Worth
  • Gift Capacity Range
  • Affinity (how close they feel to your organization)
  • Philanthropic Inclination (do they give at all?)
  • Linkage (how are they connected to your organization)

When used responsibly, estimated net worth is one more tool prospect research professionals can provide to assist frontline fundraisers in creating major gift solicitation strategies. Don’t be afraid to use it!

More Resources You Might Like

Capacity_Ratings_icon_v2

 

Join the Resource Collections online community to access this handout. Use it to facilitate discussion with your gift officers and leadership.

 

Fire your Prospect Researcher! Artificial Intelligence (AI) has arrived.

4Fundraisers, , , , , , , , , , , , , , ,

header-915122_1920

For years now we’ve been told that Artificial Intelligence was going to take over prospect research tasks. Truth is, it has. Well, some of them anyway.

Consider wealth screenings. What used to take month after month of tedious, routine, baseline capacity rating work now takes less than an hour. Upload your file, it processes, and presto! You have gift capacity ratings on your prospects based on external wealth matches.

Or how about the user-friendly lookup tools, such as iWave’s PRO, that remove the first step of searching that prospect research professionals used to perform?

Does all of this mean prospect research is on the fast track for complete takeover by the machines? Should you fire your researcher? No way!

Artificial Intelligence has had a lot of hype over the years and very little real action – until now. A few events have led to some breakthroughs:

  • The internet has made vast amounts of data available, which can be used to train computers.
  • Graphical Processing Units (GPUs), the specialized chips used in PCs and video-game consoles to generate graphics, have been applied to the algorithms used in deep learning, a type of Artificial Intelligence.
  • Capacity to run GPUs can be rented from cloud providers such as Amazon and Microsoft, allowing start-ups to innovate.

Self-driving cars may still be on the horizon, but the bots are on the road already! They can schedule appointments on your calendar, draft replies to emails, and even read radiology imaging studies more accurately than a radiologist. The Economist describes the opportunity and threat quite succinctly as follows:

 “What determines vulnerability to automation is not so much whether the work concerned is manual or white-collar, but whether or not it is routine.” (6/25/2016)

 

.

.

.

.

It’s easy to leap to the conclusion that prospect research professionals will lose their jobs to the machine – much of what we researchers do is routine – but that would be forgetting how machines have changed the world in the past.

Across the centuries, people have feared the march of the machines. In the late 1700’s to early 1800’s the Industrial Revolution rocked our world. As recently as the 1980’s, the rise of personal computers revolutionized the way we work. And with every introduction, much hand-wringing and predictions of unemployment were had.

How will prospect research professionals likely weather the advancing army of machine algorithms and programs?

Much the same as we adapted to wealth screenings and tools like iWave’s PRO. We learn new skills that wrap around the new technology. We leverage the new technology to work for us and for our fundraising team. We change the tasks we perform.

Prospect research professionals have a unique blend of skills. We can scan mountains of information and pull it together in a way that is meaningful for your specific need, whether that is creating a $5M gift strategy or a $5B campaign. We recognize the opportunities for our organizations in the data patterns the machine discovers.

If you want your organization to keep in step with the advances of machine learning, do NOT fire your researcher! Instead, reassure your prospect research professional of her value and insist that she take advantage of training that will give her the skills to use new technology. If you do this, she will be better able to guide you into new worlds, such as fundraising analytics … and beyond!

More Resources You Might Like

 

Prospect Profiles and Private Co. Valuation

4Researchers, , , , , , ,

customer-563967_1920How many times have you lamented: “Yet another prospect involved in the family business. The family’s privately-held business, that is. What valuation number am I going to pick out the air this time?!” We’ve all been there. Valuing private companies is a tricky business indeed (pun intended).

We know why so many of our prospects have ownership interest in private companies. According to a 2013 Forbes article:

  • Out of the 27 million firms in the U.S., nearly all are privately held.
  • Among the 5.7 million firms with employees, less than 1% have shares listed on a U.S. exchange.

So it’s no surprise that there are many firms specializing in valuing private companies. The need for a valuation could be a desire to buy or sell, investments looking to exit, or in anticipation of an initial public offering (IPO), among other reasons. Hoovers and Dun & Bradstreet may be among the best known search tools in our field, but there are many others. For example, Prospect Research Review did a product review report on PrivCo.

Law of Diminishing Returns

Before you dive deeply into any specialized research, consider the law of diminishing returns. At what point are the time and resources you spend going to outweigh the benefit? If your prospect qualification to gift ratio is 7:1, you could be spending twelve hours on a dud. Then again, if you are researching a prospect likely to give her largest gift ever to your organization, you want to be gung-ho!

You also want to consider the full wealth picture before you dive deeply into one piece of that wealth. If the prospect is listed on Forbes Richest People in America are you certain you need to spend hours valuing one or more companies owned by him or her?

Return on Education

You also want to consider your return on education. Why value one private company, when you could give yourself the foundation to value all kinds of companies in the future?

When you have a prospect that demands a deep dive into company valuation, do your research on how to make a valuation and keep notes so that you can apply what you learn to the next private-company-owner prospect.

Top 3 Private Company Valuation Resources

Following are some of my favorite resources for deciding how to create a valuation and a jump-start of links to get you finding the data:

  1. ARTICLE: Jarmuz, Bill. “Private Company Valuation for the Prospect Researcher” APRA Connections magazine, Jun 23, 2006, Membership Paywall
  2. WEBINAR: Lamb, David. “Refresh: How to Estimate Private Company Value – And Rate A Prospect With The Information” APRA on-demand, Members $49 | Non-members $79
  3. LINK LIST: Aspire Research Group LLC, Favorite Link List-Business, Free

 

More Resources You Might Like

3 Steps to Building a More Comprehensive Prospect Profile

4Researchers, , , , ,

By Jill McCarville, Marketing and Communication Manager, iWave Information Systems

head-746550_1920It’s almost lunchtime when a fundraiser comes to you with a new assignment:  They have a meeting with Suzie in two weeks and need to know who this person is – does she have a history of giving, does she have a connection to your cause, how much does she have to give?  Next stop, your prospect research tool.

The 3 fundamental steps to building a prospect profile remain the same: Create, customize, complete.  Okay, so those may not come as a surprise to you.  But from a software company’s point of view, there may be some profile building features within your tool that you haven’t been leveraging.  Use these features to gain deeper insight into your prospect and make your job easier. At iWave we recognize that there are many different research tools, each with different functionalities.  However, some of the features highlighted below may exist in your tool and you just didn’t know about them or haven’t had a chance to try them.  Try these steps to make your profile building easier and faster and -who knows- maybe even in time for lunch.

Creating

Our data tells us that the majority of users begin with a general integrated search (360search) across all datasets at one time.  In fact, in our tool, there were over 1.3 million 360searches done last year alone.  This broad search will help you identify which datasets/categories contain lots of information on your prospect and in which datasets you’ll need to dive deeper.  Now you can start painting the picture of your prospect’s employment, income, real estate holdings, board affiliations, net worth, stock holdings, history of charitable giving and political giving, etc.  Simply start selecting the records that you know, or are pretty confident, are your Suzie and add them to her profile.

Now, you might be saying, “But what if it’s a common name?”  No problem.  Once you’ve done a broad search across all of your tool’s datasets, you can narrow your search to find more information about your prospect, their spouse, and even their private companies or trusts. Exploring individual datasets with additional filters might even uncover key information you weren’t able to find using a broad, high-level search.

For example, if you’re trying to find Suzie’s real estate holdings, but your initial search didn’t turn up any property, that doesn’t mean she doesn’t own real estate.  As you know, it’s much more likely that she does.  After all, real estate accounted for about 20% of a HNWI’s total assets globally (CapGemini World Wealth Report 2013).  It’s possible that the property is listed in someone else’s name, a trust, or LLC.  Time to check the real estate database.  Try reverse searching by Suzie’s mailing address (rather than her name) because in many cases people link all of their properties to a primary residence for billing and other mail.  You can find additional search tips for other datasets here.

As you explore each of the datasets and “tease out” real matches to your prospect, select those records and add them to the profile you created in the broad search.  But first, ensure your tool automatically filters out duplicate records to maintain the accuracy of your scores and ratings.

Customizing

A common perception we hear in the industry is that profiles must be created externally because tools simply don’t deliver the quality of profile you need.  For some tools though, this isn’t the case.  In our tool alone, researchers create over 40,000 profiles each year containing over 1.8 million records.  One of the keys to creating so many profiles is customizing your research tool.

In the first step, you chose which records to add to Suzie’s profile.  Now, you need to add and delete records as you validate them.  This will eliminate false positives so you can be confident in the accuracy of the profile and the scores/ratings within it.  Depending on your tool’s features, you’ll also want to select your own capacity ranges (used to determine Suzie’s capacity rating), and the proper affinity ranges (so the score accurately reflects Suzie’s connection to your specific cause).

Completing

Almost there!  Once you’ve sketched out the prospect profile, it’s time to add the finishing touches.  Consider adding Suzie’s picture to the front for easy identification.  Then add any articles you may have found on her from other sources.

Jen Filla, along with other industry leaders, also suggests you add additional value to a profile by synthesizing the data you’ve gathered.  As a researcher, you are the expert on your prospects.  This is your chance to analyze the records and provide observations.  For example, what do Suzie’s SEC transactions tell you about her?  Do you see any patterns or trends in her charitable giving?  What clues can you find from her board affiliations?

Use the front page lead summary section to summarize your prospect’s current situation and provide recommendations.  In fact, in our tool, this lead summary was created based on the requests of researchers. A front and center spot to highlight the one thing the fundraiser needs to know about Suzie.  You can then use the built-in notes sections to tell the full story about Suzie as a prospect – who she likes to give to, when she likes to give, and how much she can give at one particular time.

Many people like to create and use the profile, score, and notes built within the tool.  However, this isn’t the only option.  Feel free to export the profile in a Word document for further treatment, or print a short summary profile to share right away.  And don’t forget to set an alert on the profile so you receive updates when there are any changes to Suzie’s records.

You are the expert at creating prospect profiles for your organization, and hopefully these tips will help you leverage your research tool to build better, smarter profiles.  Happy profiling!

Now, what’s for lunch?

About the Author
jill color

Jill McCarville is the marketing and communication manager at iWave Information Systems, a company that delivers software solutions to education, healthcare and nonprofit organizations to help them raise more major gifts.  iWave’s solutions are an asset to fundraising departments of any size. From Ivy league schools like Yale and Stanford, to healthcare and arts organizations like Doctors Without Borders and the Smithsonian Institution, iWave has assisted organizations in the United States, Canada, and overseas.

More Resources You Might Like

Score! takes the edge off analytics

4Fundraisers, 4Researchers, Data Mining, , , , , , , , , , , ,

I just read Score! cover to cover and here’s why I think you should too…

With Score! Peter Wylie and Kevin MacDonell have written a highly accessible book that works effectively as a beginner’s guide to driving your organization’s decision-making with fundraising analytics. It’s no surprise to those of us in the prospect development field. Peter has been writing entertaining and informative books and articles for years and Kevin’s CoolData blog is encouraging and full of easy-to-understand visuals. Both of them write about personal experiences that nicely demonstrate the ideas and concepts in the book.

This is not a do-it-yourself manual. Peter did that already with his book Data Mining for Fund Raisers. This book is for leadership and for aspiring analysts alike who want a guide to getting something great to happen. No-one feels like a fool for not knowing how analytics works (or even how to define it) and although Peter calls out leadership’s common foibles, an ambitious leader can easily swallow that pill because it helps him navigate past the pitfalls.

The book is conveniently grouped into three sections so you can decide what you want to read. Part one, Becoming a Data-Driven Organization, discusses how analytics can help you make decisions that lead to success. Part two, Your Data Driven Job, discusses what it’s like to pursue analytics in your prospect development career. Part three is devoted to case studies.

Part one launches with scenarios that are happening in advancement offices every day, but when highlighted in a short paragraph make one blush with embarrassment. You also get great information on obstacles you are likely to encounter as you seek to invest in analytics and a helpful discussion about whether to hire someone new or train an existing employee.

One of the salient points made in the book from start to finish is that fundraising analytics is all about valuing affinity – the relationship someone has with your organization. Wealth ratings and other external data is nice, but only works really well when paired with affinity. The wealth screening companies have drowned the marketplace with sales, advertising, and educational content that does not shine such a bright spotlight on using analytics to find and leverage the conversation your prospects and donors are having with your organization as recorded in your databases. Score! gets you back on track.

If you are facing the challenge of clueless leadership that does not value data, then this first section falls a bit short. Given Peter’s years of consulting I was hoping for a few guerrilla tactics and approaches to persuading leadership that analytics is the new, shiny object every leader has to use. Instead the authors give us brief vignettes of some of the good stories where leaders model the kind of behavior that encourages analytics efforts to succeed.

Part two is where the aspiring analyst gets some very thoughtful and perceptive advice about the skills needed to take on these kinds of tasks. By including a chapter on soft skills, and putting it first, there is a clear message. You can be awesome at analyzing data, but unless you can translate your results into information others can use and understand, you are not likely to achieve success. Kevin’s CoolData blog is a living example of good and useful presentation. As a bonus, Kevin and Peter share their personal stories on how they came to analyze nonprofit data for a living.

Part two also has some gems that surprised me and made me think more deeply. Although I have been using the term fundraising analytics as an umbrella term here, Kevin and Peter give you an education about the difference between data mining and analytics. You also get some terms and techniques defined – a few fundamentals. But don’t worry! The authors walk you through some step-by-step starter tasks. The highlighted quote is just one of many that should assure you that you won’t break anything by trying.

“Don’t let missing, incomplete, or suspect data stop you from jumping right in and trying to work with it just as it is.” (p.91)

Part three is a series of case studies. As the authors emphasize, these are not do-it-yourself instructions. They are case studies that illustrate the types of questions you might ask your data and some answers others have found. Kevin and Peter do a great job here of outlining the steps they took and then going into detail about what happened as a result. These case studies will give you big picture ideas to guide you as you craft your own projects. They are helpful to leadership too because they demonstrate winning applications.

In particular I was intrigued by the call center data case studies. And, of course, just a few days after reading the book a fundraising colleague described to me how she does not give to her alma mater and will not give to them, yet they have been calling, emailing and writing her repeatedly each year. She just rolls her eyes.

A huge shift is just beginning to happen as younger generations earn and accumulate income and wealth in an era of rapid changes in information technology that is creating new and changing expectations for communicating. The popular LifeHacker blog wrote a recent post with this title: How Can I Donate to Charity Without Getting Harrassed By Them Later?

It will be those organizations that listen to the conversations in their data and respond to them that will win those donors’ trust…and dollars. Score! is written about analytics in higher education, but the lessons apply equally to human services organizations. Don’t miss out. Buy, read and Score!

Don’t believe me? Read what Susan Bridgers of APRA Carolinas has to say about it!

Want to catch up on the most current buzz? Search the Twitter hashtag: #scorethebook

Data Mining Resources

Data Mining, Resource Links, , , , , , , ,

I was poking around to see what I might find on the internet and thought I would share my favorite finds related to data mining. I hope you enjoy them too!

Five ways to promote in-house data mining
by Kevin MacDonell

5 reasons every nonprofit should use analytics for fundraising
by Joshua Birkholz

From Stories to Evidence: How Mining Data Can Promote Innovation in the Nonprofit Sector
by Technology Innovation Management Review

Fundraising Analytics ABCs
by Helen Brown

The Do’s and Don’ts of Data Mining in Nonprofit Fundraising
by Daniel Neel

Getting Started in Data Mining (It's easier than you think!)

4Researchers, Data Mining, , , , , , ,

I have had a few requests for articles on simple data mining techniques and the related database maintenance necessary to make the results meaningful. Look for my upcoming companion blog post on data mining resources, too.

Before we get started, let’s talk a little bit about what might be holding us back.

  • Fear that it’s too complicated – Not much anyone can do about this one, except you. Jump in! The water is warm!
  • Assumptions that leadership will not invest and support it – Data mining and analytics are keyword candy to leadership. Leadership loves to get intelligent answers to questions like “What percent of donors rated at $100K+ gave at that level?”
  • No clear understanding of the pain/need/goal – What keeps your leadership awake at night? Is it prospect pools that don’t perform? Finding leadership donors for the upcoming campaign? If you don’t know, you can’t make a compelling case for data mining.

Donor Database Reports

Do you remember that scene in the Sound of Music where Maria is trying to teach the von Trapp children to sing? She stops singing “Do-Re-Mi” and says, “Oh, let’s see if I can make it easier”. We can do that in data mining too. (I haven’t come up with a song yet, but I’m working on it.) Here is an easy and fun way to get started in data mining – explore all the canned reports in your donor database. I’m not kidding! Even if you have no idea what deep, insightful questions you want to answer, you can begin with reports.

Consider these common reports:

  • Consecutive years giving – When donors give many years, especially consecutively, it usually means they really like us. Who are these people? Do they have high wealth ratings? Could they be good planned gift prospects?
  • Top donors – Are all of your top-giving donors getting regular attention?
  • LYBUNT, SYBUNT, & new donors – Within these reports you might find donors capable of increasing their gift, some major gift sleepers, and some new donors with wealth.
  • Lifetime giving and number of years giving – So many forgotten donors can be found in this list as well as some very good planned gift prospects.

Digging a Little Deeper

MS Excel is on most of your desktops. If you take a little time to learn to use it – I’m not talking complicated formulas, just tips and tricks – it will truly open the world of data mining to you. Imagine that you pull a report into Excel with all of the key fields in the above reports (last gift date and amount, largest gift date and amount, lifetime giving, etc.). Add in wealth ratings if you have them.

Now consider this scenario:

Custom sort:  First by largest gift amount (descending), second by lifetime giving (descending), third by last gift date (descending)

Analysis:  By scrolling down the list you can see if any donors who have made larger gifts (largest gift amount) and have lapsed (last gift date). Is there some high lifetime giving low on the list? Why?

Imagine sorting first by wealth rating and then largest gift. How about lifetime giving and wealth rating? This is fun! (I told you the water was warm.) Just be sure to watch your time. Prospect researchers have gotten lost in the data mining game.

The Secret Data Mining Trick

The secret trick to analyzing your donor information is to understand your fundraising fundamentals. Remember the fundraising pyramid?

The pyramid illustrates your areas of opportunity:

  • Occasional: Did that first-time $1,000 donor get personal attention?
  • Annual: Are there small annual gift planned giving prospects in there?
  • Annual: Can we motivate annual donors to move up a giving level?
  • Major: Do any of your major gift donors have unexplored planned gift potential?
  • Planned: Are there any planned gift donors who could make a cash gift?

Common Data Errors that Under-Mine Your Efforts (pun intended)

Now that you have the idea that you can sort on specific fields in your donor database, you will very soon realize that even sorting becomes problematic if the data is full of errors and omissions. Use your blossoming interest in data mining to clean up the database! Then when you are ready for more complicated data mining challenges, your data will be ready for you.

  • Data errors in any of the fields you pull – e.g., incorrect or missing dates or dollar values
  • Duplicate records – often happens in gift entry or multiple hands in the database
  • Deceased or bad address – if you don’t mail to your list, you probably aren’t getting your list cleaned; if you are mailing, you might not be getting a file back from the printer to update the records

What can you do about problems like these? People don’t usually like to hear this, but you need some documentation.

  • Your database probably has some maintenance reports. Set up a schedule to run them and fix the errors.
  • Do you need to run a report of all changed records daily or weekly?
  • Gift entry staff should be trained to search for the donor name first, instead of entering a new record. As in, create your own training manual for how gift entry is performed in your organization.
  • Someone should review all gifts entered, probably daily.

Robert Weiner is a consultant with some excellent free articles about keeping your database up to snuff. You can find his articles here: http://www.rlweiner.com/articles

Taking Data Mining to the Next Level

Once you have your data in order, some understanding about how the information is stored, how you can retrieve it, and what kinds of things it can tell you about your donors and prospects, I suspect you will be a lot more likely to sign up for that data mining webinar or take advantage of the APRA Analytics Symposium. It feels good to be ready, doesn’t it?