A prior is your starting belief before new evidence shows up and not in some mystical sense but in a practical, operational one.

“Ask more, make more.”
“Recency is the strongest predictor of giving.”
“Brand spend is less valuable than fundraising spend.”

These aren’t law, they’re assumptions that once worked well enough to stop being questioned.

Priors are hard to avoid and useful but only as a path to belief change – you begin with a prior, you observe new evidence, you update toward a new belief by weighing two things: how confident you were to begin with, and how strong the new evidence is.

The core idea is simple, belief is a dial, not a switch. Strong, consistent evidence should move you more than weak or noisy evidence. One anecdote should move you a little, a repeated pattern across contexts should move you a lot.

What most people and most organizations actually do is messier. They anchor on the original belief and adjust too little, even when the evidence is strong. Supporting evidence is treated as high quality, while contradictory evidence is dismissed as flawed or “not generalizable.” Even when the original reason for a belief collapses, the belief itself often survives. In some domains, people update more readily when the news is good than when it is bad.

This doesn’t mean people never change their minds, they do but usually less than the evidence warrants, and only when it does not threaten incentives, identity, or comfort.

Fundraising is full of beliefs that feel like facts because they are old and familiar. Here is a non-exhaustive, sampling of those I’ve come across.

• Ask more, make more. Volume is treated as the primary growth lever, with limited attention to diminishing returns or downstream effects.
• Recency is the number one predictor of giving likelihood. A useful proxy has been mistaken for a causal driver.
• A dollar on fundraising is more valuable than a dollar on brand. Measurability is treated as a substitute for value.
• Spend should always shift to the highest ROAS channel. Backward-looking efficiency metrics are used as strategy.
• Engagement is defined as non-financial behaviors, and more is always better. Activity is confused with commitment.
• Treating everyone the same is the most efficient approach. Operational simplicity is mistaken for economic efficiency.
• Base rates and baselines are underweighted. Normal variation is misattributed to tactics.
• Emotion causes behavior. Emotion is treated as the lever rather than the state people seek to resolve.
• Motivation is about quantity, not quality. Stronger pressure is favored over better alignment.

None of these beliefs are absurd, most were once adaptive. The failure is not having priors, it’s refusing to update them in proportion to the evidence now available.

This is not a data problem, it’s a belief problem.

The prior audit
Most organizations cannot list their priors because they have never made them explicit. They live in planning assumptions, dashboards, and phrases like “we’ve already tried that.”

A prior audit is straightforward, write the beliefs down, then ask two questions: 1) What evidence would disconfirm this?  2) And have we actually gone looking for it?

If the answer to the second question is no, the belief is not evidence-based, it’s familiar-based.

Precision, not certainty
The sector rarely rejects data outright, instead, it dismisses it as noisy, context-specific, or not scalable.  Evidence treated as low precision cannot move a belief, no matter how consistent it is.

Small tests get waved away, mixed results get ignored and learning is postponed in favor of confidence.

Beliefs that pay rent
Some priors persist because they’re useful in protecting budgets, headcount, legacy channels, and creative identities. They simplify planning and blur accountability.  From this perspective, refusal to update is not irrational, it’s economically coherent since the beliefs survive because they pay rent.

Updating is a cadence, not a decision
Belief revision is often treated as a rare event, something that happens after a major study or a bad year. That framing guarantees conservatism.

In practice, updating should be operational – small tests, frequent measurement, explicit statements of what belief is being tested and how much the result should move it and regular posterior updates, not annual planning theater.

We changed the pipes, not the priors
Fundraising has modernized its infrastructure – digital platforms, automation, data warehouses, AI tools, etc.

What has lagged is intellectual updating. Beliefs about donor sameness, attention economics, emotional regulation, personalization, and diminishing returns still reflect a world of cheaper media and more captive audiences.

We built new pipes to deliver old assumptions faster.

Institutions love priors and they persist until they become too expensive to maintain. The sector doesn’t need louder tactics, it needs fewer sacred beliefs.

Kevin