Why Data Like a Lab – It Just Wants to Make You Happy

We had to take a tough break from blogging for a little while.  We lost one of the Buck-White Boys on February 15.  The original Buck-White Boy, the lab by which all others will be measured and the Dog That Started It All.  Tucker.

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Tucker was the best.  He was the best part of a Pet Partners  Animal Assisted Therapy team.  One of the sweetest, kindest, most joyful animals you would ever want to know and he took a huge part of our hearts with him.

On his therapy visits, Tucker didn’t do well sitting still – he did better in situations where he could go from room to room and visit with people.  He’d turn a corner and walk into a hospital room, where someone would be desperately ill, and the whole room would just light up. He’d smile and wag and soon everybody was smiling and wagging.

He just wanted people to be happy.

That’s labs, man.  They just want everyone to be happy.

Now, I’m not going to anthropomorphize data so much that I’m going to compare it to a therapy dog, but . . . your data pretty much just wants you to be happy.

Data doesn’t want to be difficult, it doesn’t want to be messy and complicated and tough to deal with.  It just wants you to be happy.

Your fundraising data is the single greatest tool you have – well, other than your rock star personality, amazing charm, superior intellect and dashingly good looks.  Without good data, all of that goes to waste because, without information, who are you sharing all of that awesomeness with?

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Clean, structured, secure data makes your job 1,000 times easier.  If you don’t have to worry about your data, you can spend your time loving on donors.

That’s what I mean by your data wants you to be happy – it wants you out there changing the world, not sitting in the office crunching data sets or cleaning up salutations.

We were fortunate to get Tucker as a nine-week-old puppy and we invested a lot in his training and development.

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The older he got, the fewer bad habits he had and we could always revert back to that training to remind him what good behavior was.  He ultimately passed the AKC’s Canine Good Citizens Test.

Invest in training your data, keeping it clean and up-to-date and don’t let the bad habits accumulate – that’s a happy database.  And a happy database = a happy and successful fundraiser.

 

 

 

At Home in the Annual Fund

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C’mon, sing with me now, “Our house.  In the middle of the street.  Our house . . . ”  Or we could have gone with, “Our house is a very, very, very fine house . . . ”  This is a multi-sensory blog; great info and musical ear-worms.  You’re welcome.

If you don’t know Helen Brown, I’d encourage you to get to know her.  Really a leader in the world of Prospect Research, super smart, writes a great blog and a couple of months ago had a mic drop moment with “Why wealth screenings – and prospect researchers – are so reliant on real estate.”

Go read it; I’ll wait.

Right?  Wasn’t that good?  She’s so on point.  My favorite bit:

You may be right, you may be wrong, but at least it’s something to go on in this business where we’re all operating on uncertainty, every single day. We attach ratings to and hang our hopes and our cultivation strategies on people who may or may not support our organizations. It’s a guessing game to which we apply the most solid things we can to a sea of uncertainty.

The rating is a just starting point anyway.

Preach, sister.

I reached out to Helen and got her blessing to riff on this a little bit.  I love prospect research.  I think it’s one of the coolest things in our arsenal, but it’s certainly not my forte.  Nor is it the end-all, be-all panacea of solving all our fundraising issues.  Research and predictive modeling take the guessing game out of the equation and turn a shotgun approach into a laser focus.

The Rating Is Just a Starting Point Anyway

Folks, there’s no certainty in Fundraising.  OK, there’s one – nonprofit organizations will always need  to do it.  Other than that, anything’s possible.  Every technique, best practice and sacred cow is just there to help reduce some of the variables.

That’s what prospect research does.  Especially in higher-end major gift work.

But we don’t often use it in the Annual Fund, especially in segmentation.  Why?  Because usually all we have is real estate.

If you’ve done a screening of a whole bunch of names – 300 or 300,000, doesn’t matter – you skim off the top tier, those with the highest ratings.  Funnel them into Major Gift portfolios for next steps – identification, cultivation, etc.

SOAPBOX MOMENT:  Major Gift folks, please, when you’re done with your identification/qualification process, pretty please release those unqualifieds back into the Annual Fund pool so we can get ’em solicited and not let them stagnate.  We all know you can’t manage a portfolio of 500+ prospects, even though you’re a Fundraising Rock Star.  #pleaseandthankyou

Typically what you’re left with is a whole mess of mid-range prospects and donors that have one piece of data from public information – real estate. (And then a whole lot more that have no publicly available data at all).

Sometimes Some is Enough

To Helen’s point – it’s something.  It’s something we now know about this individual.  We have an idea of what they’re like because we know what real estate they’ve purchased.

Does it tell us what to ask them?  No.

Does it tell us what their capacity is?  No. (Although you can surmise a capacity based on real estate, there’s no way to tell what their debt-to-income ratio is).

Does it give us a clue on response?  Possibly.

In a direct response acquisition or renewal campaign, prospects with real estate can out-perform those with no rating at all.  Most likely in average gift vs participation.  There have been many tests and programs that have shown that those with higher real estate values tend to give a higher level gift than those without it, especially when you’re using an ask string.

Because it’s something.  It’s something that says, “Hey, there’s some capacity here.”  And sometimes some is enough to make a difference.

As Helen said, “We can use it to form well-educated guesses.”

It’s worth testing.  It’s worth the investment of having, and using, that data – at all levels.

It’s worth not dismissing just because “it’s just real estate.”  If you’ve got nothing else, it’s at least something to help an educated guess.