What kind of web analytics package are you running?
Chances are, if you run a site, the only analytics you’re running is Google Analytics, or something equivalent. For most high-level traffic analysis, it’s Good Enough, but for anything else, it Sucks Bad.
The reason is that for most entrepreneurs, they have a small # of issues they care about, when it comes to their traffic:
- Is their site growing?
- Are users sticking to the site?
Problem is, beyond this high-level view, the underlying DRIVERS of these statistics aren’t available. The goal is not just to passively observe what’s going on in your site, but to understand the underlying variables enough to make changes and see what happens.
For example, let’s take a look at viral marketing metrics…
Are female users more viral?
Jeremy Liew recently wrote about the observed phenomenon that female users are more viral:
I recently spoke to the people who run a popular social network and they shared some of their stats with me:
1) In 2007, 56% of total signups were female.
2) Females are 33% more likely to invite friends than are males.
3) Females are 10% more likely to respond to an invite from a female vs. a male.
4) Males are 50% more likely to respond to an invite from a female vs. a male.
Definitely interesting stuff.
And it reminds you that if your business is based on viral marketing, and you don’t know who in your system is likely to be viral, it’s impossible to optimize for increasing your distribution. And that sucks.
Build custom integration to dig one level deeper
What you really want to do is to dig one level deeper in your traffic analytics so that you can start to make changes to the underlying levers. After all, you’re tracking this information not as a passive-activity, but as a way to adjust and optimize your business, right?
If you’re a video site, it’s not enough to just track pageviews – instead, you want to know how many comments are being left for each video. Or how many videos are being watched in a session. Or the difference in these stats between users that churn out, versus users and stick around. Or how many friends an average user has. These are all super-important metrics.
This is all the more important when you are dealing with ads. After all, a pageview is not a pageview, depending on whether it’s US versus international, whether it’s the 50th ad a user has seen or if it’s the 1st, and so on. The most specific your goal is (monetization versus growth versus retention), the more you want to tie your statistics to user-centric stats versus the generic stuff that’s available in any analytics report.