Days and Hours

The Days of Month, plus Days of Week and Hours reports (see Figure 3-3), all
answer the same basic questions: “Is traffic to the web site cyclical?” and “Did
any special events influence traffic?” Days of Month gives you a daily breakdown,
lets you compare against the average, and shows how AWStats arrived
at the Summary numbers.
From a business standpoint, comparing monthly reports shows that
SkateFic has a much stronger showing in the winter, during the figure-skating
season—duh. The 2006 Olympics also boosted traffic considerably in February
2006. There aren’t any particular intramonthly trends, even when comparing
across months.
Too bad that the Days of Week and Hours reports aren’t as useful. In the Days
of Week report, averaging tends to even out both anomalous bumps and meaningful
anomalies. The Hours chart, unlike the Days of Week chart, gives you
aggregate numbers where averages would be more meaningful. The Hours
graph is the saving grace, showing peak hours around 8:00 a.m., 2:00 p.m. to
3:00 p.m., and 9:00 p.m. (remember those are Central Time).
What does it mean in a business sense? The Days of Week chart means
absolutely nothing because averaging kills any bumps that might have meant
something. The Hours chart shows that SkateFic is busy before work, after
school, and after the nightly news. Most visitors are probably from the continental
U.S. because the site is busiest during the U.S. day. There’s a significant
population of night owls and people from the Eastern Hemisphere because
there is a base line of traffic even while westerners are sound asleep. This
raises the geographical question.

Countries
Americans have a terribly bad habit of being Amero-centric. AWStats uses a
reverse domain name system (DNS) to figure out where site visitors are coming
from. The top 25 countries of origin are listed on the main page in order
from most traffic to least. Usually, there are a significant number of incoming
IP addresses that cannot be resolved. These are listed as “Unknown.”
By clicking the Full List link, you can see all the countries that showed up in
the logs. Would you think that people in 96 countries—including Iran,
Bermuda, Nigeria, Mongolia—would be interested in figure-skating fiction?
That seems to surprise everyone who isn’t still laughing over the idea that figureskating
fiction actually exists.
Your site may have a much greater reach than you realize. Knowing this can
influence decisions about content and e-commerce. Would your site strategy
change if you knew that 35 percent of your traffic was coming from the European
Union?
We thought so.

Hosts
The hosts list (see Figure 3-5) offers several different views of the same information:
the host names and IP addresses of visitors. This is the same information
used to tell which country visitors hail from.
On the main page of AWStats, the first line after the title bar gives an
overview of how many known and unknown/unresolved hosts there were, as
well as how many unique visitors this represents. Then the main report starts
with the host who requested the most pages, listing hosts in descending order
from most traffic to least.
In Figure 3-5, you should note two interesting points. First, unlike the other
reports that show only “people,” the hosts list shows both “people” and “not
people.” Spiders and other robots are not second-class citizens on the hosts
list. Second, Google spiders have the top five wrapped up. What does this
mean? Well, Google indexes the site for new content at least once a week,
sometimes twice. For a small site, this is very good news. It means that the 800-
pound gorilla of search engines has taken notice and indexes regularly. New
content will not languish in obscurity

Robots and Spiders

In Chapter 2, we talked about visitors who are people and visitors who are not
people. One particularly important kind of visitor that is not a person is an
indexing spider or web crawler. The Robots/Spiders report (see Figure 3-6)
lists the various named and unnamed but identified web crawlers that have
run their sticky little legs all over your pages.
Named spiders are known robots from known entities: Google, Inktomi,
MSN, Yahoo, and so forth. Other spiders are not known, but when they hit a
special file on the top level of the web site called robots.txt, the server marks
them as spiders. Robots.txt tells spiders where they are allowed to go and
what they are allowed to index. For example, if you didn’t want the pictures
on your web site indexed, you could put a line in your robots.txt to make the
whole images directory off limits to spiders. Most good spiders pay attention
to these directives, but there’s no money-back guarantee.
Hits from spiders are reported a little differently from hits by other entities.
For each spider, the first number under Hits is the number of requests the spider
made. Then there’s a plus sign and the number of times the spider successfully
“saw” the robots.txt file. As you can see from Figure 3-7, different spiders
hit the robots.txt file in greatly varying numbers. Those numbers could mean
anything from lots of spider visits to very inefficient spidering methods. In general,
spiders are good. Being indexed is good. Being found is even better.

Visits Duration

Why does this report make us cringe —okay, just Mary, it’s her web site after
all. The Visits Duration report shows how long visits were. The average visit is
about 2.5 minutes. That’s not too bad. But then, you look at the numbers that
went into those 2.5 minutes. Fewer than 2,000 people stayed more than two
minutes. Only 15 percent stayed more than 30 seconds! For a content site,
that’s enough to shake an editor to her soul.
One of the measures of a successful content web site is how “sticky” that site
is. Stickiness is about whether visitors bounce in and then bounce out just as
fast. Apparently, lots of people do. Either they find what they want and leave,
or they don’t find what they want and leave. Either way, they leave before they
get deeper into the site.
This observation in itself is valuable. But where did most of these people
come from? How did they encounter the site? Did they leave immediately, or
did they try to load another page? Did they find what they wanted and leave?
Or didn’t they look? Those last two are very different things.
AWStats can’t tell us. While AWStats provides the raw data of “who came,
how many, where?” it can’t say “who came and left immediately, how many
dug in deeper, and where did they go?” For that, you need Google Analytics.
This is one park where the Little Leaguer, good as he is, can’t hit a homer.