Modelling the Donor, Part 3-- The Bene Score
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S1 E13

Modelling the Donor, Part 3-- The Bene Score

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Speaker 1:

Welcome to this edition of Beep Behind Each and Every Product covering the latest products and features in our platform at Click and Pledge. So today we're doing a deep dive into what might be the most, foundational challenge in fundraising. It's something that really separates the effective programs from the ones that feel like they're just spinning their wheels.

Speaker 2:

Mhmm. The ones stuck in that cycle of, you know, high turnover and burnout.

Speaker 1:

Exactly. Our mission here is to bridge the gap from fundraising theory specifically, this big idea that you have to avoid surprising your donors to what you actually do, the practical application in our platform.

Speaker 2:

And that idea of surprise is so critical.

Speaker 1:

It's the biggest killer relationships, we think. So if we know that, the huge question for every fundraiser is how do you know what a donor is expecting? How do you get inside their head? Okay. Let them pack this.

Speaker 2:

Well, that's it, isn't it? That inability to just know what the donor is thinking? That's where all the friction is. Right. Every single donor, every person has what we call an internal model.

Speaker 2:

You can think of it like a a personalized map in their head that guides their expectations, their trust.

Speaker 1:

And what they think is an appropriate ask.

Speaker 2:

Crucially, what they think is an ask.

Speaker 1:

Yeah. So And since we can't, you know, plug a USB drive into their brain, which I think most fundraisers wish they could.

Speaker 2:

Top of.

Speaker 1:

That internal model stays completely hidden. So if we send a huge gift ask to someone who's only ever given bucks through a text campaign, we're not just sending a mismatched ask, we are violating their internal model.

Speaker 2:

You're violating their model.

Speaker 1:

Yeah.

Speaker 2:

And that causes surprise which leads to friction, resentment, and almost always no gift. Right. And if you're operating without any insight into that model, every single thing you do, every email, every call, it's basically a high risk gamble. You're just throwing darts in the dark.

Speaker 1:

And hoping you don't break the trust you spent years building.

Speaker 2:

Precisely. So that brings up the big question. How do we get beyond the guessing games? How do we get the actual data driven insight we need to deliver that perfect relevant ask?

Speaker 1:

Well the answer isn't telepathy, it's inference. Since we can't read their thoughts, we suggest that effective fundraising has to rely on watching their actions.

Speaker 2:

Reticulously.

Speaker 1:

Yeah. All their interactions, their patterns, all of it gives us clues. It lets us infer what that internal model looks like and really importantly what they are prepared to do next. Here's where it gets really interesting.

Speaker 2:

Okay.

Speaker 1:

This brings us right to the core of our solution in the click and pledge platform, the Binet score.

Speaker 2:

Right, the Binet score is the tool we built specifically to solve that inference problem. We designed it to be a powerful, dynamic predictive model. Its only job is to forecast donor behavior with a high degree of mathematical certainty.

Speaker 1:

So it's not just one of those simple RFM scores then? Recency, frequency, monetary?

Speaker 2:

No, not at all. That just kind of ranks people by how much they gave. This is different. The Binet score is a living, breathing measure that tells you where the donor is right now

Speaker 1:

in their journey with you. Okay. So say a donor lands on a new page or clicks a specific email link or even just updates their address. How does the Binet score handle that? Is it just adding points for everything they do?

Speaker 2:

No. And that's the absolute critical difference. If it were just simple addition, a $100 gift from three years ago could easily outweigh them, you know, clicking on a volunteer link yesterday.

Speaker 1:

Which would give you a totally wrong picture. A

Speaker 2:

completely wrong prediction. The real power here is that the Binet score brings all of those interactions together, every tiny signal, every big transaction to give you this clear synthesized picture of their current intent. And it's not based on some arbitrary weighting system, it's driven by some really sophisticated, belief updating math.

Speaker 1:

So if it's not simple addition, what's the math doing to make sure a click today is weighed correctly against a donation from last year? That leads us right to the technology behind it. Why is our approach so good at prediction?

Speaker 2:

So we recommend that fundraisers understand that the Benei score uses Bayesian estimation.

Speaker 1:

Okay, Bayesian. I hear that and my mind immediately goes to an advanced probability class.

Speaker 2:

It sounds intimidating, I know. But let me make it really relatable. What's so fascinating is that Bayesian estimation is basically the same belief updating math that our own brains use constantly.

Speaker 1:

Our brains!

Speaker 2:

Yeah, it's how we process new information and update our own internal model of the world around us.

Speaker 1:

I like that, the brain analogy. Tell us a bit more about how that works.

Speaker 2:

Okay, think about walking into a room. Your brain instantly makes a prediction about what's going on. Then, someone speaks or a door opens. Your brain doesn't just throw out its first guess.

Speaker 1:

No, it adjusts.

Speaker 2:

It integrates that new data to form a better, more accurate belief about what's happening. It dynamically updates its map of reality that is Bayesian estimation in action. And our Binet score does the exact same thing with donor data. A lot of standard models they treat old data as just static facts. Bayesian estimation though it sees every data point especially the new ones as evidence.

Speaker 1:

Evidence, okay.

Speaker 2:

And this evidence constantly, incrementally, updates the probability that a donor will take a specific action.

Speaker 1:

So let's say a donor gave a big gift five years ago but lately they've been clicking every single volunteer email we send.

Speaker 2:

Perfect example.

Speaker 1:

The Bayesian model doesn't just keep them ranked high because of that old gift. It sees the new super relevant volunteer clicks and it updates its belief about what they want to do now.

Speaker 2:

Exactly. It might shift them from a lapsed major donor to a highly engaged volunteer lead. We suggest fundraisers really recognize the power of this. It's synthesizing all the data, not just the last gift or the biggest one, to give a mathematically sound prediction of their next likely action.

Speaker 1:

And it just keeps getting smarter over time.

Speaker 2:

It's always learning. Every data point makes the predictions stronger and more accurate.

Speaker 1:

That's a huge shift. We're moving away from these static lists based on ancient history and into a truly predictive way of looking at our supporters. So what does this all mean for the person running the campaign and trying to be an effective fundraiser? What is the practical payoff?

Speaker 2:

The primary benefit is a total shift in strategy. You move away from what is essentially high risk guesswork to a science of giving that's built on certainty.

Speaker 1:

Let's call the old way what it is. Random outreach. You're just throwing money and time at every group and hoping something works.

Speaker 2:

And it's expensive, it's stressful, and it usually just results in that donor surprise we talked about.

Speaker 1:

We want to move away from that chaos.

Speaker 2:

Absolutely. When we use the Binet score, we can adopt a low risk, high certainty science. We stop creating surprise and we start creating efficient, relevant and predictable pathways for giving.

Speaker 1:

Can you give us concrete example? How would a fundraiser actually use this to lower that risk?

Speaker 2:

Sure. Let's say you're planning your big year end appeal. You have 10,000 donors. In the old model, might sort them by their last gift amount and, you know, cross your fingers.

Speaker 1:

Right. Hope for the best.

Speaker 2:

With the Binet score, you can segment them based on their inferred intent. The score doesn't just predict if they'll give, it helps predict what type of ask they're ready for.

Speaker 1:

Ah, okay.

Speaker 2:

For instance, a donor whose Binet score is rising because they keep clicking your impact report links. They're showing high interest and trust. The school might suggest they're ready for an upgrade or maybe a recurring monthly gift.

Speaker 1:

Because they're in that relationship building headspace.

Speaker 2:

Exactly. But on the other hand, a donor with a stable kind of moderate score who hasn't clicked anything in four months, they might be the perfect person for a simple low friction text to give appeal.

Speaker 1:

So instead of blasting everyone with the same generic please give your best gift letter, you're using the Binet score to pre qualify the ask based on where they are right now.

Speaker 2:

Precisely. The ask is tailored because we've inferred their current behavioral model, all thanks to that constant Bayesian updating. This just means we're way more likely to present the right opportunity at the right time.

Speaker 1:

So we suggest this power lets our customers deliver the right message to the right person.

Speaker 2:

The right message to the right person at the right time, whether that's a big campaign ask, a monthly pledge, or even a call for volunteers, it minimizes the friction and maximizes the relevance. It turns fundraising from a guessing game into a precise strategy.

Speaker 1:

That is the very definition of efficiency. Maximizing return on your marketing spend and even more important, the longevity of that donor relationship. You're focusing time and budget where the math tells you it will work. So by observing actions and using the Binet score, we're giving fundraisers the tools to create predictable environments where giving is the the anticipated and desired outcome, not some kind of accident.

Speaker 2:

And if you look at the really big picture, this kind of scientific predictability lets organizations forecast their revenue with so much more accuracy. It moves your big strategic decisions from just intuition to objective evidence.

Speaker 1:

That's a powerful way to end it. Moving from just hoping something works to knowing exactly where to aim and doing it with same math that drives our own decision making.

Speaker 2:

And we absolutely want to remind everyone listening that this tool, the BEN8Score feature, is completely free. It's already part of the Connect platform in our fundraising command center. We want everyone to start benefiting from this predictive approach right away.

Speaker 1:

For more information about this and all Click and Pledge products, make sure to visit clickandpledge.com and request for a one on one training or demo. Whether you are a client or curious about our platform, just ask us, and we will gladly get together with you to chat.

Speaker 2:

And don't forget to subscribe to this podcast to stay up to date with all the latest and greatest features of the Click and Pledge fundraising command center.