> Of course statistics lie.

I definitely see your point, and I'm not going to presume to know a lot
about statistics, but I'm talking about some pretty basic math, I think, so
I'm wondering if you can elaborate based on an example.

Let's say you make some small design tweaks to a homepage and see a 25%
increase in conversions within a week after the new version goes live, and
the increase stays decently stable for months afterwards. Before, you had 6k
conversions per month, and now you have somewhere between 8k and 9k per
month.

Can you elaborate on how something as simple as this can be misinterpreted?
I believe it can be, I'm just having trouble seeing how.

Also, I realize many stats and such are a little trickier to interpret than
this, but generally, site stats aren't that complicated.

Once, for example, I noticed that out of 1,100 new registrants for a
subscription-based application in the span of one week, only about 10% had
actually gone through the setup process for the app after paying their
initial subscription fee. This was easy to spot because the EULA was the
first page a new user hit, and only 100 or so of these new users had hit the
EULA that week.

Tracing the process backwards, I saw that the email that went to new users
after signing up contained 42 links (stupid Marketing dept!), only 1 of
which went to a Help doc about how to set up the application and get
started. This link was buried in the middle of a long block of text. The
safe bet was that most people were not seeing the link.

We stripped out the vast majority of the links, left in only a few key ones,
focused the email around the 3-step process for setting up the app instead
of linking off to a Help doc, and generally cleaned things up quite a bit. A
week later, the  percentage of people who hit the EULA had gone from 10% to
over 80%.

Again, how can simple numbers like this be misinterpreted?

-r-
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