Analytics and AWStats

AWStats AWStats (Advanced Web Statistics) is an open source log analyzer written in Perl that can use a variety of log formats and runs on a variety of operating systems. The official documentation of AWStats is mostly targeted to system administrators rather than to owners of web site businesses. In short, it’s not much help in figuring out what the statistics mean. Wait a minute! This is a book about Google Analytics, so why the heck are we talking about some open source stats program? Because the thing about analytics is that to make any sense, there needs to be some data. It’s going to take at least a couple days to get any data into Google Analytics. It’ll be months before there’s enough data to make any sense. But you may already have a wealth of historical data right there in AWStats. Never looked at it, you say? Thought so. That data you’ve probably got in AWStats, which maybe you never really understood because there’s no in-depth documentation on it, are still valuable. This is your past. For some things, bigger and newer isn’t necessarily better. Google Analytics and AWStats have different features with different strengths and weaknesses. For some things — many things — Google Analytics blows AWStats out of the water. For other things, Google Analytics uses a different methodology, with its own limitations. There are two main differences between Google Analytics and AWStats. First, AWStats is primarily a site statistics program. AWStats counts more than it calculates. It has far fewer metrics and capabilities than Google Analytics. It’s intended to be a simpler sort of program — nothing wrong with that. Google Analytics is intended from the get-go to be a business strength program. It calculates as much as counts and gives you metrics that, as a business person, you’ll want. Second, AWStats is a log analyzer. Google Analytics relies on cookies and JavaScript (referred to as “scripting” from here on out). This has several farranging implications. For example, to a log analyzer, all traffic coming from a single IP address is one “user.” When using scripting, you set a cookie on an individual user’s machine, or even in a particular account profile. Then, if five computers share an outside IP on a local area network, and there are three user accounts on each computer, you “see” 15 users, not one. On the other hand, if users turn off cookies, or don’t allow “third-party” cookies, you may not be able to track them at all with Google Analytics. At best, you may be able to track them for a particular session, but a half-hour later (or the next day), they will look like brand-new visitors. Another excellent example is tracking search engine visits (see the section “Robots and Spiders” in Chapter 3). A log analyzer has to identify search engines from lists of known spiders, by the spider’s identifying itself, or by a wild guess. Some small percentage of a log analyzer’s traffic may be misidentified as a real person when it’s not. On the other hand, most spiders, robots, and search engines, by default, don’t execute JavaScript code. Google Analytics won’t misidentify these sorts of false visitors. Of course, Google Analytics won’t pick up real visitors who have JavaScript turned off, either. Just as you can argue Mac vs. PC or football vs. figure skating, you can argue script-based tracking vs. log analysis. I’m not going to say one is intrinsically better than the other. There are tradeoffs with either methodology. As long as you know what those tradeoffs are, and what effect they may have on your metrics, you can allow for any ambiguity that might arise. At some point, no matter how you gather data, you’re going to have to plow into the nit-picky little boring stuff: log analysis vs. scripts, nobodies vs. people, pages that are pages vs. pages that really aren’t. So because we work hard and play hard — and you note which comes first — we’re going to dig in and go through some of the details, the basic concepts that will make what you see in Google Analytics mean something.



AWStats Browser

We’re going to get under way by taking a look at the AWStats window

(http://awstats.sourceforge.net/)

shown in Figure 2-1.

The AWStats window has a left-hand and a right-hand frame. The righthand
frame shows the reports. The left-hand frame shows the domain name
for the site statistics you’re viewing followed by a text link navigation list. You
can go directly to sections of the main report from any flush-left link. Secondary
reports, left-indented with a tiny AWStats icon, replace the main report
in the right-hand frame when you click the navigation link.

AWStats Dashboard
AWStats doesn’t have many controls on the dashboard (shown in Figure 2-2).
Much of what can be configured is set by your web host at install time. The
dashboard appears at the top of the main report. AWStats notes the time of the
last update. Most web hosts update in the middle of the night. The time listed
is on the server’s time zone and is not necessarily your time zone. You can
force an update by clicking the Update Now link.

If you need up-to-the-minute results, or if your site is very busy during a
specific part of the day, it’s probably smart to force an update before you look
at the stats. If you’re updating results for a couple days, the update can take
some serious time — upwards of a half-hour — depending on how busy your
web site is. If your site is not very busy, or if it has been only a couple of hours
since the last update, you might have the same overhead as a normal page
reload.
Use the drop-down menus to change the month and year. To view a whole
year, choose Year from the month menu and then the year from the year menu.
Click the globe to go to AWStats home page at SourceForge.net. Click the
flags below the globe to change the reporting language. Available languages
depend on which ones your web host has installed. In this screenshot, French,
German, Italian, Dutch, and Spanish are installed, as well as the English
default.