Visualize effects of hurdles on user numbers I have the following data:
1000 users were invited
 990 emails delivered successfully
 200 visited the system
  60 tried to create an account 
  58 tried to create an account with a valid email
  50 successfully created an account (i.e. chose a secure password)
  40 participated by voting
  10 posted something

While I could use a bar graph, the proportions of 60:58:50 would likely be lost. If I'd use a logarithmic scale, the proportions would be distorted and the feeling of numbers would be lost.
Is there a good way to represent both the (significant) loss in user attention due to the number of hurdles as well as the effect of each hurdle?
 A: Here's one attempt using R and ggplot2, I'm sure there may be others that are more effective.
library(ggplot2)
#Load data
dat <- data.frame(Number = c(1000, 990, 200, 60, 58, 50, 40, 10),
                  Action = c("Emails Invited", "Emails Received", "Visited System", "Tried To Create Account",
                             "Used Valid Email To Create Account", "Successfully Created Account", 
                             "Participated by Voting", "Posted Content"),
                  stringsAsFactors = FALSE)

#Create data needed for geom_segment
dat <- transform(dat, lowval = -(Number / 2)
                 , highval = Number / 2
                 , index = rev(1:nrow(dat)))

#plot it
ggplot(dat, aes(x = lowval, xend = highval, y = index, yend = index)) +
  geom_segment(size = 4, colour = "steelblue") +
  geom_text(aes(x = 0, y = index - 0.25, label = paste(Number, Action, sep = " ")), size = 3.5) +
  theme_bw(18) + #Make default font a bit bigger
  opts(title = "Effects Of Hurdles On User Numbers") +
  opts(axis.text.x = theme_blank(), axis.title.x=theme_blank()) +
  opts(axis.text.y = theme_blank(), axis.title.y=theme_blank()) 


A: Like Chase suggests, funnels or funnel-like charts are a classic way to share this information. Another thing you might check out is the Waterfall chart, but I think those are good at absolute sizes, not relative sizes.
I would suggest one very different approach - spreadsheet simulation.
Often we find ourselves in situations where intuitive reasoning is hard to shake, even with the facts right in front of us. I have found that a good way to make those facts more influential is through simulation that shows how much a change can affect the end result. A simple conversion funnel like this can be easily converted into a spreadsheet model that starts off with 1,000 users, and reduces them with a % conversion at each step. Then you can play with different strategies - "what if we made it 5% easier to choose a secure password by using live AJAX-y feedback" or "what if we made the email more interesting so 10% more people would click the link?" 
Such a simulation is a very basic and limited way of forecasting. In reality, a change in the email that increases the email click rate can easily diminish conversion across all of the following steps, because you're reaching users who are further from your core target, and it could also easily increase conversion across the following steps because you increased people's interest and motivation in finishing. But the value of this is that it helps to focus people on the big picture - which changes, at a first glance, will have the most impact at the end of the funnel?
