Mean, Median, Mode
Your end-of-year fundraising report says the average donation was €47. That sounds healthy. The board is pleased. But then you pull up the actual donation list, and something feels off. Most gifts are €10 or €15. A handful are €25. There are two at €500 and one at €2,000. Where exactly is this €47 "average" donor?
They don't exist. And that's the first thing you need to understand about summarizing data.
When most people say "average," they mean the mean, which is the total divided by the number of donations. If 200 people gave a combined €9,400, the mean is €47. The math is correct. But the number is misleading, because a few large gifts pull the mean upward, away from where most of your donors actually are.
The median tells a different story. Line up all 200 donations from smallest to largest, then find the one in the middle. That's probably around €15. The median is the point where half your donors gave less and half gave more. Unlike the mean, it doesn't get dragged around by a single wealthy supporter.
Then there's the mode, the value that shows up most often. If 68 out of 200 donors gave exactly €15, then €15 is your mode. It tells you what's typical, the amount your donation page probably suggests as a default or that your recurring donors settled on.
These three numbers answer different questions. The mean tells you about total revenue divided equally. The median tells you about your typical donor. The mode tells you about your most common gift. When they disagree with each other, that disagreement is itself useful information. It means your data is lopsided, with a long tail on one side. In fundraising, the mean is almost always higher than the median, because donor distributions skew right. A few major gifts pull the total up while most people give modest amounts.
This matters in practice. When you report "average donation" to the board, the mean makes things look rosier than the median would. When you set suggested amounts on your donation page, the mode tells you what people actually choose. When you forecast revenue, you need to know whether you're counting on a few big gifts (mean-driven) or a broad base of small ones (median-driven). A campaign that loses its top three donors will see the mean collapse while the median barely moves. How much the mean bounces around month to month is a question of spread, which we explore in Day 2.
Grant reports are another place this shows up. If a program served 50 participants and you report average outcomes, one outlier success story can inflate the mean. The median gives funders a more honest picture of what most participants experienced. Showing the 25th and 75th percentile, as we cover in Day 3, paints an even richer picture.
The mean tells you about your money. The median tells you about your people. The mode tells you about your defaults. Know which question you're answering before you pick one.
See It
Click "Add Large Donation" to drop a €500 gift into the dataset. Watch how the mean jumps while the median barely moves.
Reflect
Pull up your last fundraising report. Does it use the mean or the median when it says "average donation"? What would the number look like if you used the other measure instead?
If your organization lost its single largest donor tomorrow, how much would your "average" donation change? What does that tell you about how much of your story depends on a few people at the top?