mean (arithmetic mean)

The arithmetic mean is what most dashboards simply label "average": add up every value and divide by how many values there are.

$\bar{x} = \frac{x_1 + x_2 + \dots + x_n}{n} = \frac{1}{n}\sum_{i=1}^{n} x_i$

In everyday speech "average" can mean any typical value, so in a report it pays to be precise: the mean is one specific calculation. Average order value (AOV), average revenue per user (ARPU) and average session length are all means.

The mean's big strength is that it is tied to the total: mean × count = total, always. That makes it the right measure for forecasts and budgets. If CatChow expects 400 orders next month at a mean of $45, that is $18,000 of revenue. Neither the median nor the mode can do this.

Its weakness is the flip side of the same property. Every value counts in full, so one extreme value can drag the mean far from where most of the data sits. Product data (order values, time to purchase, revenue per customer) usually has a long right tail, and the mean then lands above what a typical customer does. Always glance at the median next to it: if the two are close, the data is roughly balanced; if the mean is well above the median, a few large values are pulling it up. For a mean that resists a handful of extremes there is the trimmed mean, and for combining means of segments of different size, the weighted mean.