How to express error as a percentage? I have data about how many unique users do a certain thing for each day of a month. I can average it, and i would like to display the variation in a intuitive format (such as % of  something).
Is there a standard way of doing this? 
I've found standard error, which is $\frac{\sigma}{\sqrt{n}}$, which is not particularly intuitive for users of the data.
If anyone needs clarifications, please ask. I'm not too clear about this myself.
EDIT: in response to the answers, it's for building out a analytics dashboard for use by the entire company (so many people probably don't understand standard deviation). In particular, we are doing A/B testing for various metrics over a period of say 1 month. We basically would average all the metric per day to give a number for that period, but there are variations day-to-day and would like to have some good way of expressing that. 
 A: It may be meaningful to just divide by the average. E.g. the average number is 1000 and the std is 200, so in a sense this means the actual number can vary by 20% from the baseline.
Also, if you could say who the user of the data are and what they are doing with it, it might be useful.
A: The standard error of the mean tells you how precise your estimate of the mean is; that doesn't seem to capture what you're trying to do.  I would use either a) a histogram, if you care mostly about showing variation, or b) a line chart or area chart, if you want to say something about variation while also showing progression over time.
A: Assuming your distribution remotely resembles a normal curve, you could convert the standard errors into a more intuitive percentage value pretty easily. For example, if the distribution is pretty normal, approximately 95% of your population falls within +/-1.96*SE of the mean. Building from SheldonCooper's sample values, you could say, "The average was 1000 and about 95% of the population was between 600 and 1400." Likewise, about 70% of the population falls within +/- 1*SE, etc. 
If your sample distribution tends to deviate from normal by a lot, don't despair, but try to provide more details so we can help.
A: As @rolando2 mentioned, the histogram might be a tool for displaying the variations; and also, as @ashaw stated, you might need to find where 95% percentage of number go to, then, you can probably just use box plot to generate the basic features of your dataset, and put the data to the dashboard that is shown in the company without the box plot. For box plot, you might check here:
http://en.wikipedia.org/wiki/Box_plot

Hope this helps, at least for inspiration...
A: $$\text{Percent Error} = \frac{\text{Error}}{\text{Theoretical value}}\times 100$$
A: The more intuitive form to express the Standard Error in terms of percent is called Relative  Standard Error $(RSE)$ which is the expression of the Standard Error $(SE)$ as percent, this is the formula:
$$
RSE\%=\frac{SE}{\bar{x}}\times 100
$$
where, 
$RSE\%$ is the Relative Standard Error in percent 
$SE$ is the Standard Error 
$\bar{x}$ is the mean value of the sample 
and,
$$
SE=\frac{\sigma}{\sqrt{n}}
$$
where, $\sigma$ is the sample standard deviation, and $n$ is the size (number of observations) of the sample.
I was dealing time before with the same problem because I had many variables with different units, and I found the $RSE$ as a good alternative to show my results. I hope it can be useful for you too. You can find additional information here: Australian Bureau of Statistics, and Investopedia.
Regards
