The five best free prospect research resources

I have the luxury of working in a well-supported prospect research shop, which means that I typically don’t have to worry about finding free prospect research resources. But a couple years ago, I started doing a lot more freelance consulting and research work on the side on a shoestring budget and I realized I needed to brush up on free prospect research resources. There are a lot out there, but I’ve found that there are just five that I really, really rely on. If I were stuck on a desert island and could access just five resources, these are the sites I’d access:

1. FEC.gov (specifically, the campaign finance disclosure portal advanced search page http://www.fec.gov/finance/disclosure/advindsea.shtml)

The FEC’s advanced search page is a pretty powerful search tool that lets a person search on a number of different criteria so you can query as broadly or as narrowly as you’d like. They’ll even let you drill down in the search results to see the actual original filing. Even when I’m using a paid resource, like a vendor that will aggregate FEC contributions attributed to a particular donor, I will still go directly to the FEC site to verify that the vendor got it right.

One of the things I really like about the FEC filings is that you can often get employment information and home addresses from their filings.

And here’s a tip for searching the filings: use just the donor’s name and their city and state, and when you do, try using the city for their home address AND their work address (assuming you have them).

2. SEC.gov (specifically, the full-text EDGAR filings search page http://searchwww.sec.gov/EDGARFSClient/jsp/EDGAR_MainAccess.jsp)

I do use a vendor for my SEC filing searches in my day job, mostly because their search interface is really, really powerful. However, the SEC’s search interface for their EDGAR database actually isn’t far behind in terms of its robustness. The four-years full-text search can be used in advanced mode, which allows for a lot of flexibility.

3. County assessors’ offices (or more helpfully, pulawski.net, which lists many of the assessors’ office websites from around the United States http://www.pulawski.net/)

Each county assessor’s office is different: some let you search online on a whole bunch of different datapoints; some only let you search on a few; some don’t let you see the property owner’s name; some don’t even let you query their property rolls online. Thankfully, there are enough that provide reasonably good access to make it worth my while to check them out.

There are several benefits to looking up an individual’s property records, two of which I find particularly helpful: (1) you can often confirm that your person owns the property in question (and potentially when they bought it and what they paid for it) and (2) you can often get the name of their spouse. The spouse name goes a long way in confirming info found in other places (appearances in donor lists, for example); the property valuation and ownership info helps shed some light on how wealthy a prospect might be. However, to get a better sense of a property’s value, I avoid relying on the assessor’s market value, and instead prefer my fourth most-valuable resource.

4. eppraisal.com

County assessor’s offices are all over the map in terms of how they assign a market value to a property. Some stay pretty close to actual market value (Minnesota is decent) others have specific laws and regulations in place that make it really hard for them to do so (California comes to mind). For this reason, I much prefer to get an estimate of the current property value, and eppraisal is my favorite source for doing so. Not only does eppraisal provide their own property value estimate, but they also show you what value Zillow assigns to the property!

5. The National Center for Charitable Statistics (http://nccsweb.urban.org/PubApps/search.php)

I used to be big on Guidestar and the Foundation Center. They were the only games in town for an easy way of getting to 990 forms.

No more.

The National Center for Charitable Statistics has a free, slick search tool that lets you look up information on pretty much any nonprofit organization in the United States. (And you don’t have to register to use it.) Their query tool is very easy to use but flexible enough to do very specific searches, and the results include lots of summary information about nonprofits. The BEST part though is their collection of 990 filings: NCCS provides filings going back seven years (in many cases).

Those are my five! What free prospect research resources do you like?

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The problem with data visualizations

You’ve probably heard the skeptical aphorism about statistics: “There are three kinds of lies: lies, damned lies, and statistics.” Unfortunately, I worry that we may soon hear “data visualization” tacked on to that list as the fourth and most deceiving way of communicating information. This is a problem.

A couple months ago, I was reading through some materials about a company’s financial health, and they included a dual axis chart showing the company’s Revenue and EBITDA from 2008 to 2014 (projected).  (See below.)

Dual Axes exampleLooking at the chart, it appears that the two measures increase in a near parallel fashion. The slope of their lines is pretty comparable, particularly in the later years on the chart. Problem is, this misrepresents what is actually happening. The axis on the left increases in increments of 20 while the one on the right does so in increments of 10, which means the relationship that appears between the lines is a misrepresentation.

When we chart the same data on a single axis we see that EBITDA fails to increase nearly as dramatically between 2012 and 2014 as revenue does. (See below.) If I’m evaluating the health of this company and its future prospects, that difference may be important!

Single Axis example

Adding a second axis seems like such a simple, innocuous thing, but it changes how the data might be interpreted and understood. This is just one example of the substantial impact a seemingly small design decision can have.

Why should we care about this? There are two main reasons:

  1. As consumers of more and more visual data, we need to be aware of situations like this where visualization design decisions may obscure (or at least distract from) certain critical pieces of information. Just because it’s data (data never lies!) and you can see it (my eyes would never deceive me!), doesn’t mean it is presented in an objective way.
  2. As more of us are in roles where we create data visualizations, we need to be aware that if we are careless, we run the risk of misleading our audience or imposing (hopefully unintentionally) our own viewpoint on the information we present.

Data visualization likely will be one of those things many of us try to do without any formal training, and I worry that, as a result, a lot of folks will do it badly. Am I being overly paranoid? I hope so. But this particular example doesn’t do much to allay that paranoia.

Make it pretty: Why you need to spend time making things look good

Last week I wrote a post about design and how important it is in everything we do – simply acknowledging this and being more thoughtful about design is likely to improve the quality of whatever you’re working on. In that post I downplayed the “form” piece of the design equation, and today I was reminded that that part is actually pretty critical as well.

Why does it matter if something looks good? If my doo-dad or product or whatever works well, that should be enough, right?

You would think so, and in a perfect world it would be so.

But the fact is, it is not so! And we can use this to our advantage.

In 1995 Masaaki Kurosu and Kaori Kashimura published a paper entitled “Apparent Usability vs. Inherent Usability: Experimental Analysis on the Determinants of the Apparent Usability.” In it, they reported that, basically, when people find something to be more attractive or aesthetically pleasing, they consider it to be easier to use. The paper is considered to be the seminal work on this notion, and has been followed up by other experiments and papers confirming the idea.

Why does this matter?

Well, if you’ve created something for other users – be it a dashboard, or a prospect profile, or a single data visualization – and it’s kind of ugly, your users are more likely to perceive it to be less usable. They’ll be less inclined to engage with it. And if they disengage, the product is no longer serving the purpose you intended (if any purpose at all!)

If you take the time to “make it pretty” and improve the aesthetic appeal of whatever you’re creating, you increase the perception of its usefulness and impact and, as a result, its actual usefulness and impact.

MakeItPretty

Design Matters

I used to think that design was all about artsy, visual things: fashion, graphic layouts, modern architecture, fancy furniture. You know — all the “form” stuff. It’s true that design is central to all of these, but design permeates FAR more of what we do than we all probably realize, particularly when you start thinking about the “function” piece.

Crafting an email and paying attention to how you organize it? That is design. Deciding what order your slides should go in for a presentation? Design. Trying to figure out how to most effectively lay out a prospect profile? More design. Strategizing about possible ways of engaging a prospect? Development. (And still design.)

Basically, any time you are controlling how something is constructed, that is design. Pretty sure that all of us, as human beings, are then constantly designing in one way or another, whether we know it or not.

And that last piece is wherein the most opportunity lies: most of us probably don’t realize how much we are designing things as we go along, and by simply acknowledging this and keeping it in mind, I imagine we get better and more thoughtful about everything we do.

What are some design questions that Researchers can consider to help them do their work better? Here are a few examples:

  • What details should I include in this event bio?
  • How should I use formatting and fonts to highlight the most important information in this prospect profile?
  • What questions should I ask this gift officer so they’ll tell me the most valuable things about the donor visit they just returned from?
  • What information should I focus on finding about a prospect at any particular point in the cultivation/solicitation cycle?
  • How much do I go into detail about this prospect’s stock holdings?
  • Which of these stats should I display in a chart? In an infographic? In a table? Just as plain ol’ numbers?

For more reading on myriad concepts related to design, check out Universal Principles of Design. It’s a really excellent book that is PACKED with all sorts of information about concepts in design. I can about guarantee that it will inform or inspire at least a part of what you do in your work.

Design

The ‘analytic’ investment: A Response

One of my favorite bloggers/data-geniuses, Kevin MacDonell, wrote a nice post on which I wanted to comment. Unfortunately he turned off comments on his blog (I can’t say I blame him), so I’ll write a post of my own in response.

There are two concepts in Kevin’s post I wanted to respond to:

  1. Becoming a data driven organization is a journey, not a destination
  2. Those of us who are already bought in to the data-driven mentality need to speak the language our bosses respond to.

Point 1: Becoming a data-driven organization is a journey, not a destination

I couldn’t agree more with this concept. It’s not enough to just hire a smart data analyst; start generating more reports; create new ways of scoring and analyzing our prospects; send out charts and graphs; etc. These are all tools that help move us in the right direction, but the real impact of a data-driven way of operating is in how we use all of that information to change behavior. What do those reports and charts and graphs show us that presents new opportunities? How do they inform us about our progress and what adjustments we might need to make in light of that progress?

In fact, I would say that being a data-driven organization is not so much about journeying as it is about completely changing how you think about, manage, and do your work. Moving in that direction is indeed a continual journey, and the end result is a rich, pervasive integration of a data-driven mentality.

Point 2: We need to speak the language that others respond to.

Again – agreed. Kevin’s big point is that if we want to convince others of the value of a data-driven mentality, we need to stop trying to get others to learn the language of data and analytics, and start putting data and analytics into their language, particularly for “bosses” and those leading the organization. I would say we need to make this shift in all settings where we are talking about (and using) data.

It seems that every organization has that brilliant data analyst who can go miles deep with his or her knowledge and analyses, and quickly lose the end users in highly technical language. This person is a huge asset with the potential to add tremendous value, but there’s a missed opportunity if we can’t take their good work and make it understandable and immediately relevant.

To be clear, this absolutely is not an issue of end-users being dumb or needing additional education. People simply think in different ways and they value different things. If I’m presenting new information or analysis to someone, and I don’t tailor my message to fit in with how they think and what they think about, far less of my message will resonate. If I’m lucky they’ll ask good questions that force me to reconfigure what I’m saying so they can take in more of it. But more likely a large portion of what I have to say will simply be ignored.

If we want smart data usage to become a regular part of how we do business, it needs to fit with how we all talk about our work, from the top of the organization to the bottom.

Run your Prospect Research shop like the Google Search page or a Swiss Army knife

Google search, for better or worse, plays a pretty central role in the Research profession. Lots of people use it; the best researchers know how to get a lot out of it; lots of development staff mistakenly think researchers spend all their time just “googling” things; it’s loved for its power and ease of use and sometimes dissed for its search personalization. When we talk about research, it’s hard to avoid Google.

But I came across a quote this morning that suggested an even better way we can harness the power of Google: be more like it.

Google’s first female engineer, Marissa Mayer, is reportedly responsible for the site’s clean, minimalist look. She said of the site, “Google has the functionality of a really complicated Swiss Army knife, but the home page is our way of approaching it closed. It’s simple, it’s elegant, you can slip it in your pocket, but it’s got the great doodad when you need it. …  A lot of our competitors are like a Swiss Army knife open — and that can be intimidating and occasionally harmful.”

The best prospect research and management shops definitely feature the utility of a really complicated Swiss Army knife. From complex prospect identification tools like statistical modeling analysis to robust prospect management systems that track myriad concurrent activities, to rich, in-depth information development – prospect research departments can do a lot of really cool, really useful things.

But do we feature the elegance and simplicity of a closed Swiss Army knife or the Google search interface? Do we make it easy and effortless for our “users” to interact with us? I’m not convinced that we do so as much as we should, and that may be an opportunity for improvement.

A complaint I’ve heard from frontline fundraising staff (not necessarily at my institution) is that it can be too difficult to interact with a prospect management system – entering contact reports or updating prospect or proposal tracking information is too tricky. And that’s a big turnoff and clear deterrent from use.

Similarly, we can analyze and score prospects twelve ways to Tuesday, and the barrage of numbers runs the risk of making people just throw up their hands and say “Uncle! That’s too much for me. I’m just going to ignore all that.”

And if a researcher puts together a prospect profile that goes WAY beyond what is needed for the task at hand, we run the risk of crowding out the most important, most useful information. (Imagine opening ALL the gadgets on a Swiss Army knife and then trying to just use the scissors tool! Anybody need a band-aid?)

To some extent, most of us think about this sort of thing frequently, but I imagine by incorporating more thoughtful, elegant design with a focus on simplicity into everything we do, we make the fruits of our labors more accessible and desirable to use.

SearchAndKnife

The “Threshold of Hireability”

When you’re trying to fill an open position, the way to do it is by finding the best candidate in the applicant pool, and then offering them the position, right?

Well, sort of.

You can go this route, and it’s particularly tempting after you’ve  reviewed all of the candidates, phone interviewed many of them, brought several of them in for in-person interviews, and brought a few in for MORE in-person interviews, ALL while trying to keep up with the workload in your short-staffed shop.

“Let’s just hire the best available candidate, and we’ll move forward from there.” (After all, any deficiencies they have can be made up for through some super-awesome training and coaching on my part!)

Problem is, if your top candidate doesn’t cross the Threshold of Hireability, you aren’t doing yourself any favors. Any time I’m deciding whether or not to extend a job offer, the most important question I ask is whether or not the candidate crosses this Threshold. If not, I keep looking.

What exactly is the “Threshold of Hireability?” It’s the dividing line that separates the truly hireable candidates from the ones that are just okay. If a candidate doesn’t make it past this line, don’t even consider hiring them, even if you are in a pinch.

How do you set your Threshold of Hireability? Ultimately, that is up to you as the person making the hiring decision, but it comes down to this: What are the skills and attributes that are essential for the successful candidate? What are the deal-makers and deal-breakers in terms of what a candidate brings to the table? What qualities does the candidate need to have to be a valuable addition to your team?

Consciously defining your Threshold of Hireability — and then thinking about your top candidate(s) in the context of that standard — positions you to make a much better hiring decision than you would if you simply chose the best applicant. There are a number of reasons why you don’t want to make a bad hire, and the Threshold of Hireability is one “tool” that can help keep you from making such a mistake.

Never settle for anyone who doesn’t meet the standard you set; and if you find that more than one candidate clearly exceeds the Threshold, wonderful! Your hiring decision just got a whole lot easier!