Access Management

One very helpful feature of Google Analytics is the ability to give other people—
your IT manager or administrator, other executives, or your partner—the ability
to see and manipulate your Analytics account.

If you’ve ever worked with someone else and had them inadvertently
change something that you didn’t want changed, you may be nervous about
which privileges you grant to other users. Maybe you want them to control
everything. Maybe you only want to allow them to look at the reports. The
Access Manager lets you control who can see what and who can do what with
your whole account. You can control who has access to individual profiles
from the settings page for each profile.

The Access Manager is located near the bottom of the Analytics Settings
page. Click the Access Manager link and you’ll be taken to the Access Manager
dashboard, shown in Figure 5-8. From this dashboard you can add users and
manage those users’ privileges.

Adding a User

Recently there have been several studies about how executives want to be
involved in the collection and reporting of business intelligence, such as the
information gathered by Google Analytics. According to these reports, executives
want to be right in the middle of the action. They want access to the
reports and to receive information about what data are being gathered, how
often, and from where.

Google Analytics is built for multiple users. If you have an executive
screaming over your shoulder every day that he wants information about the
ROI (return on investment) of your web site, Analytics makes it easy to overload
him with all the information he could ever desire. All you need to do is
add your executive as a user on one or more profiles.

To add a user to your profile, go to Analytics Settings ➪ Access Manager.
In the Access Manager window is an Existing Access box that shows who your
current users are and what levels of user they are. Click + Add User in the
upper-right corner of the box to give another person privileges.

You’ll be taken to the Create New User for Access page, where you should
enter the user’s e-mail address and name, and set the access type, as shown in
Figure 5-9. If you are allowing the user viewing privileges only, you can choose
to permit access to individual profiles. If you select Account Administrator, the
user, by default, will have access to all profiles and the profile lists will disappear. When you’ve entered the relevant information, click Finish and the user
account will be created.

If you’re not sure you want the executive (or anyone else) to have complete
control over your Analytics account, you can always add them to a report
mailing list, like the one that you learned to create in Chapter 4. This is an easy
way to give your executives the information they demand without having
them poking around in areas where they could create havoc.

Website Profiles

How many web sites do you own? Do you have just one or do you collect them
the way Monopoly players hoard hotels? Maybe you’ve got a web site and a
separate blog or a personal site and an e-commerce one? If you have multiple
sites to track, you know it can be a hassle if you have to track all those sites separately. It takes time to keep up with each site, and it’s always hard to come up
with extra time.

Google Analytics makes it easy for you to track the analytics and metrics for
multiple sites or even subdomains by creating profiles that you can manage
from one location. Below the Analytics Settings ribbon is a Website Profiles
table. This table contains all the links you need to administer your various profiles,
to add a profile, or to change or delete a profile. There’s also a status category
that gives you a quick look at the tracking status of each profile you’ve
created. If for some reason your tracking code isn’t working properly, you’ll be
able to see that very quickly in the Status column of this table.


Adding a Profile

When you sign into Google Analytics for the first time, you’ll be directed to a
web site where you set up your first profile (you may remember doing this
back in Chapter 4). Once you get that first profile set up, you can add additional
profiles through the Website Profiles dialog box.
Here’s how to add a new profile to those you’re tracking:

1. In the Website Profiles table on the Analytics Settings dashboard, click
Add Website Profile.

2. As Figure 5-4 shows, the information page for the new web site profile
appears. Select from the options to add a new domain to track or to add
an existing domain to track. The new domain is for a site that you are
not currently tracking. The existing domain would be a portion, or page,
of a site you’re already tracking that you would like to track separately.
(The way time-zone information is presented may differ slightly among
users.)

3. After you select the Profile Type, select whether your site is an HTTP
site or an HTTPS site (HTTPS is usually used for secured pages, like
checkouts or registration pages). Then enter the URL of the web site
that you want to track in the Add a Profile for a New Domain text box.

4. If you’re adding a page to an existing profile, then click Add a profile
for an existing domain, select the Domain Name you want to add the
profile to, and give the profile a name.



5. Click Finish.

6. You’ll be taken to the Tracking Status screen, as shown in Figure 5-5.
The code that makes it possible for Google to track your site is located
below the Instructions for Adding Tracking. Copy that code and paste
it to the bottom of your Web page before the tag, and the site
will be added to your profiles for tracking.

Checking Status

Once you’ve added the code to your web site, it will appear in the Status category
on your Analytics Settings dashboard as pending. You should see the status
of the tracking on your site whether it is Pending or Receiving Data.
Pending means that Analytics is still gathering information.

It could take a couple of days for Analytics to gather enough information to
begin producing reports. When enough tracking information has been gathered,
the message Receiving Data will be displayed in the Status category.

Editing a Profile

Once you’ve created your Analytics profiles, you can edit or change the profile
information by clicking the Edit command that’s on the same row as the profile
name in the Website Profiles table. The profile name is usually the URL of
the web site you’re tracking, though it might be something like “Web Store” if
you’re tracking the part of your web site where e-commerce takes place.
The profile settings page is shown in Figure 5-6.

This page enables you to change four types of profile setting

■■ Main Website Profile Information: Change the profile name or the
URL of the site you’re tracking, or set a default page —the index page
of the site you’re tracking. Add query parameters, set your time zone
and currency settings, or choose which reports you would like to have
access to.

■■ Conversion Goals and Funnel: A conversion goal is a target page you
want users to reach. For example, if you want to drive traffic to sign up
for your corporate newsletter, your conversion goal would be the “thank you”
page for the sign-up process. The number of people who actually
reach the “thank-you” page is then counted toward the conversion goal.
Funnels are pages that you expect your visitors to pass through to reach
your conversion goal. You can specify up to 10 pages as funnel pages.
Those pages are then monitored to show traffic patterns and how users
navigate through your site to your conversion goal—and where people
drop out of the process that leads them to a goal. You’ll learn more about
creating and tracking goals and funnels in chapter 7.

■■ Filters Applied to Profile: Filters help you achieve more accurate measurements
of the traffic on your site. For example, you can choose to filter
visitors who enter your site from a specific domain as a way to ensure
more accurate reports. The most common use of this feature would be to
filter out traffic from your IP address. Say that your browser loads your web site’s home page when you open a new window. You don’t want to skew data about real visitors by counting hundreds — if not thousands — of your own visits and page loads. A filter can tell Google Analytics to ignore anything that comes from your IP address, resulting in more accurate metrics. Filters can be quite complicated, especially when you begin to create advanced filters with Regular Expressions, so
you’ll find more information on this topic in Chapter 6.

■■ Users with Access to Profile: In many organizations, more than one person
will want or need to have access to the information that Analytics
collects and the reports that it returns. There are two levels of access:
View Reports and Account Administrator. View Reports allows the user
to look at any reports in that profile. Administrator privileges allow the
user to make changes to View Reports and make changes to settings.
This is where you add users for individual profiles, instead of adding
them to the whole account.

All these settings can be changed at any time. If you try something and it
doesn’t work, you can change it again until it does work. Each web site you’re
tracking has its own profile settings, so you can manage each profile in a way
that works best for that profile.

Deleting a Profile

Change happens, and it’s a good bet that your needs will change over time.
You may change the name of your web site, add profiles you want to track, or
delete profiles. To delete a profile, navigate to the Analytics Settings page; then
find the name of the profile that you want to delete. Click the Delete link that’s
in the same row as the name of the profile. As Figure 5-7 shows, you’ll be
prompted to confirm that you want to delete the profile. Click OK and the profile
will be deleted.
Make sure you really want to delete the profile from Analytics before you
click OK. Once you confirm, there’s no way to get the profile back. If you
change your mind, you’ll have to recreate the profile from the beginning and
you’ll lose all your historical data

The Settings Dashboard

It’s one thing to collect data. Any web statistics program will do that. But to go
beyond gathering data to producing usable information —that’s something
completely different. While most analytics programs produce almost any kind
of data your heart could desire, they don’t make it easy to use. And if you can’t
figure out what the data mean, you can’t use that data to your benefit.

To produce meaningful data, even with the easiest of analytics programs,
you have to set up the program correctly. Set-up should be easy. The first dashboards, after all, were on horse-drawn buggies. Far from those horse-andbuggy
days, most professional analytics programs require experienced professionals to configure them. Google Analytics is strictly DIY, beginning with the simplest dashboards first. The more complex settings are no more than a few clicks deep.


Analytics Settings
When you log in to Google Analytics, the first page is the Analytics Settings
dashboard shown in Figure 5-1. This dashboard is your gateway to creating
and managing your profiles, controlling access to those profiles, and setting
filters.


The main (top) menu bar of the Analytics Settings dashboard has two basic
choices: Analytics Settings and View Reports. If you have more than one profile,
you can select which one you’d like to view from the drop-down menu, as shown in Figure 5-2. Otherwise, the default profile (whichever one you added first) will load when you click View Reports. Jerri has only one web site profile in her account, her freelancer’s site, www.JerriLedford.com.

If you’ve been given access to profiles in another account, you will have a
second drop-down menu on the far right. As Figure 5-3 shows, this is the menu
that contains the different accounts connected via your Google Analytics
account. For example, the www.JerriLedford.com profile is the default in Jerri’s
account, whereas the SkateFic profile is in Mary’s account. Using the Access
Manager, Mary gave Jerri administrative privileges to the SkateFic profile. Jerri
can see all the metrics and make changes to settings in the SkateFic profile.

Part Two ■ Setting Up Google Analytics

Next to some reports within a section, you may notice there is a small arrow
that points right. This arrow, shown in Figure 4-10, indicates there are additional
reports under that category. For example, within the Visitor report section,
there is a category for Visitor Trending. When you click the Visitor
Trending link, the navigation bar expands even further to show the reports
that are available on that next level down. The important thing to remember,
when navigating through Google Analytics 2.0, is that the more clicks you
make, the deeper into the collected information you’re drilling.

One of the nice things about the Dashboard page is that it’s completely customizable.
You can quickly add the reports that you use most often to this front
page by following these steps:
1. Navigate to the report that you want to include on the dashboard. All of
the reports for each section of Google Analytics are located in the navigation
bar on the left side of the screen.
2. Once you’ve reached the report that you want to add to the Dashboard,
click the Add to Dashboard button, shown in Figure 4-11.

3. The report is added to your dashboard and a message (shown in
Figure 4-12) is displayed on the current screen. The next time you view
your dashboard, you should see that report at the bottom of your screen.

You may find it irritating that this new dashboard system does not enable
you to remove one report. The Site Usage report that appears at the top of the
page is there to stay. You cannot remove it, and you can’t move it to a different
location on the page, which you can do with the other reports that you place
there.
To move a report from one place to another on your Dashboard, all you have
to do is place your pointer over the gray bar at the top of the report. Your
pointer will change to a four-pointed arrow. Click-and-hold that bar while you
drag the report to the desired location. Using this method, you can arrange all
of your reports (except that Site Usage report) in any order that works best for
you. Kudos to Google for making this element of Google Analytics 2.0 much
more user-friendly than in the previous version of the program.
There are also some changes to the way in which you get help in Google
Analytics 2.0. In the previous version of the program, getting help was most
difficult. The online help system was set up in a very circular, hard-to-navigate
way. With this new system, however, all you have to do is navigate to the
report on which you need help, then click the About This Report link on the
left side of the page. A tooltip appears, explaining the purpose for the report,
and the basic “need-to-know” information.
For more in-depth information, click the Conversion University link just
below the About This Report link. Again, a tooltip opens, giving you a preview
of the additional information that’s available in Conversion University—
Google’s training system. If you want to know more than what’s provided in
the tooltip, click the Read More link at the bottom of the tooltip box, and you’ll
be taken to the relevant article at Conversion University.

Finally, as you navigate through Google Analytics 2.0, you may notice two
buttons near the top of each report page. These buttons—Export and Email—
indicate new functionality that users of Google Analytics have been waiting for.
Use the Export button to export any report or Dashboard to a file. You have
your choice of file types: PDF and XML are file types that are available for all
reports. But CSV and TSV file formats are also available for some reports. If you
want to export a report to one of these file types, all you have to do is navigate
to the report, click Export, and then select a file type from the links that appears.
After you click the link, a dialog box appears prompting you to open or save the
report. Use the dialog box to specify where you want to save the file and what
the file name should be and then click OK. The report will be saved.
When you click the Email button, you’re taken to a page like the one shown
in Figure 4-13. From this page, you can send a report to an e-mail address as an
attached file.
To send a report in e-mail, all you need to do is add the e-mail address the
report should be sent to, create a subject and description for the message, and
then select a file format. On the right side of the page is a preview of the message
that will be sent. When you’ve finished entering the information, click the
Send button and the message will be sent to the specified recipients.
The e-mail option also allows you to schedule a regular mailing of a report.
If you click the Email button from within a report you’ll be taken to the Setup
Email page. From this page, click the Schedule tab. The page will reload and
you’ll notice that there is now a Date Range/Schedule drop-down menu, and
the Send button has changed to Schedule.
Set up your e-mail just as you would if you were sending a single e-mail,
except set the schedule for the report you would like to have sent. You have some
options there also for the frequency of the data you’d like sent. For example, if
you choose Weekly, then the report that’s sent will include all of the data from the
one-week period since the last report was sent.
Once you’ve set all of the options, click the Schedule button and the message
is scheduled to be sent, on the schedule you have chosen, to each of the
recipients you specified. Once the message is sent, you’ll be returned to the
report view, but a gold bar at the top of the report will display a confirmation
that your report sending schedule was set. In that bar, there is also a link to
Manage Scheduled Reports. Click this link to view scheduled reports, stop
sending them, or modify them.
If there is more than one report you would like sent on the same schedule,
then you can add a report to an existing schedule. Navigate to the report that
you would like to include in the scheduled send, then click the Email button at
the top of the page. When the page reloads and the e-mail form is showing,
click the Add to Existing tab. This takes you to a page that displays the reports
that you have scheduled to send at specific times. Select the schedule to which
you would like to add the report and then click the Add Report button. The
report is added to the existing schedule and you’re returned to the report page.
The ability to send your reports by e-mail or to export them to files makes
Google Analytics 2.0 an even more useful tool than it has been in the past. It’s
no longer necessary to take screenshots or captures to share this information
with other people inside or outside your organization. Now all you need is an
e-mail address. With a few mouse clicks, you’ll have your reports delivered to
whoever may need to see them, or you can even schedule regular mailings so
that you don’t have to think about such things. This feature adds much more
usability to the Google Analytics application.

Navigating Analytics

By now, you’ve had a taste of navigating through the Google Analytics site. It’s
an intuitive, point-and-click navigation method that lets you start at the most
general of pages and takes you deeper into more specific pages as you go on.
For example, when you sign in, you’re taken to the Analytics Settings Dashboard.
If you click one of the View Reports links on that page, you’re taken to
the reports for the corresponding web site. The first page for each account (or
web site) that you’re monitoring is the Dashboard page. This page, shown in
Figure 4-9, is an overview of the reports that are available to you through
Google Analytics for that specific account or web site. It allows you to see
quickly the most important measurements for your site.
From the Dashboard page, you can navigate to every other report in Google
Analytics 2.0. The navigation bar on the left side of the screen is where you’ll
find links to all the reports. Each section of reports is divided into a group that
includes all of the reports related to that aspect of analytics. If you click the title of the report section, the navigation bar expands to show links to each of the
reports in that section.

Part Two ■ Setting Up Google Analytics

Activating Tracking

Analytics uses a snippet of JavaScript code to track the traffic on your web site
as shown in Figure 4-6. You have to place that code on your site before the
Analytics tracking is activated. It’s not hard to do. All you have to do is copy
the code that Google provides when you set up your account and paste it into
your web site code before the tag at the end of the page.
Save and republish the page, and Google Analytics will automatically detect
the correct placement of the code. This may take a couple days. Or it may happen
quickly. We’ve seen it happen both ways.
The key piece of information in the tracking code is the line that begins
uacct=UA followed by a seven-digit number. This number is unique to each
web site profile, and it tells Analytics which profile owns the ping your site
sends when a page gets loaded.
After you’ve pasted your code into every page you want to track, click
Continue. You will be brought to your Analytics Settings Dashboard shown
in Figure 4-7.
On your Analytics Settings dashboard (which you’ll learn more about in
Chapter 5), you should see a message that indicates the code has been detected
and data are being gathered for the analytics. The detection of the code should
be immediate, but it could take a couple of days for any analytics to appear. In
the meantime, if you click the Check Status option, you’ll be taken to the Status
Tracking page, as shown in Figure 4-8.

Analytics will say whether it detects your tracking code or not and whether
it is waiting for data or receiving data. Depending on how busy your web site
is, it can take several days to several weeks to get enough data into Analytics
to make the graphs mean anything. Regardless, Analytics always shows a listing
of your code on the Tracking Status page in case you misplace it somehow
(for instance, during a site redesign). Click Done when you’re finished with
the page to go back to Analytics Settings.

NOTE To track more than one page of your web site, you need to add the
tracking code to every page you want to monitor. For example, if you have
15 pages in your web site and you want to track all of those pages, you need
to place the code snippet on every one of those 15 pages. Any pages that do
not contain the tracking code will not be monitored.

At that point, all of the reports and graphics for your site metrics should
appear in your Google Analytics account. Google Analytics is a historical analytics
program, which means statistics are not tracked in real time. The statistical
data that appear in your analytics reports will be one to two days behind. It’s not
a perfect solution, but despite the delay, the depth of information provided is
both accurate and useful.

Signing Up for Google Analytics

When you’re ready to get started with Google Analytics, the first thing you
need is a Google account. If you’re a Gmail or AdWords user, or if you followed
the instructions mentioned previously for creating a Google account, you
have everything you need.
All you need to do is sign in, using the account information that you already
have. Google Analytics is not in beta anymore. It’s open to the public. Just
enter your Google Account name and password as shown in Figure 4-2 and
click Sign in. If you prefer for Google Analytics to be in another language, the
program supports 17 languages including Queen’s English, Russian, French,
and Chinese. You can select your preferred encoding from a menu in the upper
right-hand corner before you sign in.
You’ll land on a splash page like the one in Figure 4-3. Click Sign Up to
continue.

Now, to the meat of the sign-up process. From the page shown in Figure 4-4,
choose http:// or https:// from the menu, depending on whether your site is
on a secure server or not. Then enter your site’s URL. In this case, we’ll be tracking
the web site for Mary’s mother’s rental house (Mary is already tracking
every other site she owns).

Give the site a name, although Google Analytics will automatically enter the
domain name for you. Choose the country where you’re located. This sets the
time zone menu to show only the correct time zones for your country, so don’t
choose France when you need Fiji. Next click Continue.

First, You Need a Google Account

If you don’t have an account with Google, signing up for one is easy. The
amount of information required is minimal, just your e-mail address and
physical location. In Figure 4-1, you can see the information required to create
an account with Google.
You can sign up for a Google account through the main Google web page.
Go to www.google.com and click the Sign In link in the top right-hand corner
of the page.
On the page that appears, you’ll see a sign-in dialog box where you can
enter your username and password. You won’t have that information yet.
Instead, click the link below this box that says Create an account now.
On the next page, you’ll enter your sign-up information. You’ll be asked for
your e-mail address, password, location, and a verification word. Once you’ve
entered that information, read and accept the terms of service, and then click I
Accept. Create my Account.
Google sends out confirmation e-mails for new accounts to prevent spambots
from creating bogus e-mail accounts. Within a few minutes you should
receive a confirmation e-mail. When you do, click through the link in the
e-mail to activate your account. Once that’s complete you’ll have an active
Google account.

Getting Started

When Google purchased Urchin on Demand, industry analysts predicted that
the merging of Google’s technology with Urchin’s capabilities would be a
great relationship. Chalk one up for the analysts because it truly has turned
out to be a marriage made in analytics heaven. Sure, there were some growing
pains in the beginning, but combining a successful analytics program like
Urchin with the power and simplicity of Google’s technology has created an
application that anyone can use.
It’s not all roses and champagne, however. Even paradise has bugs, and
Google Analytics isn’t immune to them. Fortunately, the bugs have been pretty
minor. You should have a minimum of frustration setting up Google Analytics.
You could encounter a few issues, but we’re going to walk you through those
to make this as painless as possible.

Setting Up Google Analytics

The average professional analytics package is eminently flexible and powerful.
It can track every detail, every goal, and every bounce on your web site.
Unfortunately, that also means you have to be a propeller-head—or hire
one—to set up and use the average professional analytics package. You’ll
spend a lot of dough getting every last detail exactly right, and it’ll take more
time than you have.
Google Analytics is not your average professional analytics package. Yes,
it’s slightly less flexible, but it’s every bit as powerful. What sets Google Analytics
apart is that it’s intuitive —easy to use—even if you want to integrate
Google Analytics with your AdWords campaigns. You won’t even need a propeller
on your hat, much less one implanted in your skull.
Still, there are some steps in the Google Analytics setup that could be a bit
tricky. Part II includes everything you need to know about setting up Google
Analytics, including how to integrate it with AdWords. Each chapter walks
you through a different aspect of setting up Google Analytics. No propellers
required.
If you really want more advanced information, however, you can find that
elsewhere in the book. Chapter 9 covers some of the advanced functionality of
Analytics. These real-world examples will have you using analytics in ways
you may not have even dreamed were possible.

Error Codes

It’s worth noting that Google Analytics, by its nature, doesn’t collect information
on HTTP errors. Those errors are part of the log file, and Google Analytics
doesn’t look at logs. The only real point of interest is the 404 “not found”
errors. If you click the 404 link, it’ll take you to a page such as Figure 3-21 that
lists all the URLs for the pages visitors requested that could not be found.
The web server will know where to send visitors looking for those pages. If
the URL is pointing to an old name that no longer exists, or shows that there’s
a misspelling in your HTML, you can fix it. On the other hand, it may be an
attack on your web server if the URL isn’t familiar (especially if it contains
funny characters like \x05), or if the URL has a long, long string of nonsense
after it, or if it contains things like admin or .dll, which you don’t have on
your web site. But unless those attacks are successful or overwhelming in
number, you’re probably safe in ignoring them.

We’re Done!

We made it! Now that we’ve tied up all the loose ends and, we hope, taught
you all the basics, it’s time to move on to Google Analytics. You’ll see, as you
go on, more of what Google Analytics can do that AWStats can’t, but you’ll
also see that what you’ve learned about AWStats is valuable in itself.
Onward!

Key Words and Key Phrases

Speaking of targeted traffic, if you want to know what people are searching for
in those search engines, look no further than the Keywords and Keyphrases

These search terms are bringing visitors to your site. Unless you’re an 800-
pound gorilla yourself, the Keywords table won’t mean a whole lot, except
that having your best keywords appear the most is desirable. See how “figure”
appears 5,586 times and “skating” clocks in at 6,128, but “figure skating”
brings in only 135? That’s what we mean. SkateFic is ranked so far down in the
search for “figure skating” that it seldom gets found. The traffic you do see in
the table is actually brought in by AdWords.
For the most part, however, SkateFic’s key-phrase performance is pretty
good. There are only two anomalies (Kristina Lenko and Kristina Cousins),
which bring people in but don’t actually appear anywhere on the site. The rest
of the key phrases are on topic and likely point to relevant content. By clicking
Full List, one would see that “figure skating” appears in roughly half the
searches, meaning people are generally interested in the subject matter
SkateFic offers. This is important. Years ago, the two top searches were “Tina
Wild,” a porn star, and “hockey wives” —don’t ask, we don’t know either.
Obviously, those searches did not bring in people who were interested in what
SkateFic had to offer: a skating serial chapter that mentioned hockey players’
wives and where the main character Tina had a wild-hair day.

Miscellaneous

At present, as shown on Figures 3-18 and 3-19, the only part of the Miscellaneous
table that’s working is the tally of bookmar
The measures of “favorite” bookmarking in the two figures above are
important for at least two reasons. First, they tell you how many people liked
your site enough to bookmark it —meaning that they plan to return again and
again. They may never actually return, but some do. This is called “stickiness.”
You want your site to be sticky. The “favorites” metric helps you keep tabs on
how big your core audience is—the people who intend to come back.
Second, if you follow this over the months, you can see whether your content
is becoming more compelling or less—are more or fewer people intending
to come back? SkateFic.com ran at 4.7 percent bookmarks for the five
years or so before February 2006, as recorded cumulatively in Figure 3-18, Figure
3-19, covering February 2006 to February 2007, shows a big change. Not
only did a healthy 5,749 enter the site during that year, but 2,156 bookmarked
it—37.5 percent compared to the average of 4.7 percent for previous years.
One could explore the reasons for this, but Google Analytics records only
effects; it won’t tell you why. What it does give you are hard numbers showing
that the stickiness of SkateFic.com more than tripled in a year, from 709 to
2,156. The site has gotten stickier, and it’s doing better at attracting an audience
interested in figure-skating fiction.

Connect to Site from

The “Connect to site from” report has two sections: top and bottom. Figure 3-14
shows the upper part of the top section.
First is the traffic (pages and hits) coming from people who type your
URL—direct addresses—or use a bookmark. These are your regular customers
or readers, your core traffic. They know where your site is from memory
or they have your site bookmarked. Chances are, they’ll be back because
they know you have what they want.
The second line of the upper section is for people coming in from newsgroups.
Newsgroups are one of the more ancient forms of Internet communication,
the killer app of 1991. Newsgroups, which tend to be very uncontrolled
and egalitarian, are falling by the wayside, whereas conduits where content
can be controlled (such as mailing lists and web forums) are on the rise. There
was no incoming traffic from newsgroups. If there had been, it would have
indicated that there was some word of mouth about your site and that people
were visiting based on recommendations from other visitors.
The rest of the upper section lists search engine activity. Google tends to rule
this list, with five times more traffic than everyone else put together. The first
line has numbers for the aggregate of all search engines. The rest of the lines
have names of individual search engines with two unlabeled numbers. Those
numbers should be labeled, from left to right, Pages and Hits.
The bottom section of the table lists the external URLs that drive the most
traffic. The top URL in Figure 3-15 is a Google AdWords ad. Fourteen (of 25)
other URLs in the top-external-links list are either ad forms that repurpos
Google results or are AdWords-for-content placements from third-party web
sites using the Google AdSense program.
Clicking Full List will give you a full list of all external URLs. On SkateFic
.com, the vast majority of those URLs are AdWords-for-content placements.
But you have to know what to look for. You can’t count on AWStats to tell the
difference between a real external link and yet another AdWords placement or
search engine result.
You can, however, filter the full list results. Figure 3-16 shows only the
results that explicitly come from Google (there will be others that come from
Google but don’t say so). It’s worthwhile to note that the percentages given on
a filtered full list refer to the percentage of that filtered data set, not to the overall
full list of external links. So the 63.1 percent of all the ads that reference
Google comes directly from AdWords placement on Google’s own web site
So what does this all mean? Should you be concerned with the raw numbers
or only with the percentages? How should your percentages of direct-address,
search engine, and external-link traffic compare?

It’s like this: You want to keep current readers and customers coming back.
You also want new readers and customers to find you. A very low percentage
of direct addresses may indicate that people are not returning after their first
visit or that your offline promotional efforts are not effective. This means that
your site is not sufficiently sticky, or that people get to your site and don’t find
what they need. It means you’re not building a core audience.
A low percentage of search engine-driven traffic can mean that your site is
not well optimized for search engines and people are not finding it. About two
years ago, Mary overhauled SkateFic.com with search engine optimization
(SEO) in mind. The percentage of traffic driven by search engines doubled, as
did total traffic.
If the external links aren’t bringing in the traffic, you need to be concerned
about word of mouth and viral marketing. This is especially so if most of your
external-link traffic is coming from repurposed Google searches, small search
engines, and AdWords placements. It means that you don’t have a lot of sites
that spontaneously link to yours.
So how is SkateFic.com doing? Search engine traffic is about 50 percent—
not too shabby. Bringing in that many new people every month is growing the
core readership by hundreds of eyes every month. Direct-address traffic is
about 43 percent, which means SkateFic.com has a happy and returning fan
base and is a healthy content site. But with only 6.3 percent of page views coming
from external links, and many of them from small search engines and
AdWords, SkateFic.com isn’t doing very well as far as word of mouth. Putting
more effort into getting links from other sites, especially figure skating–related
sites, could pay off handsomely in the long run. Independent external links are
a crucial part of an SEO strategy and would improve search-engine results,
bringing in more, better-targeted traffic.

Operating Systems and Browsers

If you’re a Mac or Linux person, how many times have you heard what
amounts to “We only care about Windows users”? Certain designers and even
web site owners want to design sites only for the very newest Windows version,
the very newest Internet Explorer browser. Cross-platform compatibility
be damned! “So few people use Mac or Linux (or Netscape or FireFox or visit
from their PDA or mobile phone) that we don’t need to support it.”
But is that really true?Is it really true that all you need to support is the newest
IE and the newest Windows? According to Figure 3-11, it would indeed seem that 87.4 percent of
hits come from Windows machines and 75 percent from IE.
It’s not as exact as it would be if AWStats gave us pages or unique visitors,
but it’s the best we’ve got. Looks like a lot of Windows users. It might lead you
to decide that the right thing to do is to support the newest IE 7 and the newest
Windows Vista.
And you would be dead wrong.
Let’s do some estimates. The earlier examples and screenshots show February
2006 (so don’t get confused), but in February 2007, there were 5,749 unique
visitors and 72,780 hits. That’s 12.65 hits per visitor. The 63,653 hits from Windows
machines work out to about 5,000 visitors. The other 750 odd visitors are
on Mac or another OS. Maybe 12 percent doesn’t seem like much, but are you
willing to turn away more than 750 potential readers and customers? Mary
doesn’t happen to be, so even if she weren’t a Mac-hack-from-way-back, she’d
be putting the extra time and dollars into cross-platform compatibility. It’s
good business.
But say you’re willing to sacrifice 12 percent of possible customers. You’re
sticking to the major-OS/major-browser strategy to save money. Saving
money is good business. Are you sure you’re saving money only supporting
the most recent IE version?
Take a look at Figure 3-12 to see who’s using IE 7. Certainly not the majority.
An estimated 2,700 visitors are using IE 6. About 1,500 are using IE7 (up from
14 in the first edition of this book). On the flip side, the approximately 400 people
using versions of IE5 in February 2006 have dropped to 78 in February 2007.
IE4 has dropped to single digits, and IE3 has dropped off the radar completely.
It’s probably time to drop support for IE3 and IE4 and to consider dropping
support for IE5. But IE7? If you only supported IE7 (which is notoriously
finicky), you’d be leaving the majority of your visitors who are still on IE6
behind.
And other browsers: FireFox, Safari, Netscape, Mozilla and so on? A scant
hundred fewer visitors use those browsers than use IE7. So in an effort to support
1,500 users, a whole lot of sites are ignoring 1,400 users. Supporting only
the latest and greatest is starting to look foolhardy indeed, isn’t it?
What’s more, Mozilla, FireFox, Netscape, and Camino are all related, as are
Safari and Konqueror. Support FireFox and Safari and you’re likely to support
Netscape, Mozilla, Camino, and Konqueror as well, with little extra effort. It’s
a six-for-the-price-of-two sale!
Now what exactly does “Unknown” mean? Many of those “unknown”
browsers are not as unknown as you might think. Being book authors distinctly
lacking in curiosity, no one here ever clicked that Unknown link in the
title bar to find what you now see in Figure 3-13.

Pages-URL

The Pages-URL report (see Figure 3-8) lists the top 25 URLs by the number of
times that page was viewed. Links across the title bar will take you to the Full
List of all URLs recorded for your site.
The Entry and Exit links (see Figure 3-9) go to pages showing the full list of
URLs sorted by the most entries and most exits, respectively.
The Entry and Exit lists, as with many of the secondary pages, allow you to
filter the list with Regular Expressions. A Regular Expression (abbreviated
RegEx) matches patterns using a special syntax that we’ll discuss in more
depth in Chapter 6. Also in Figure 3-9, the RegEx .*/serials/.* matches all
the URLs that contain the directory /serials/. At SkateFic.com, the serials
directory contains all the currently running serial novels. From a business
standpoint, knowing how to filter the Pages-URL list gives you the ability to
look at different sections of your web site —that is, if your web site is structured
so that different sectors of your business correspond to different structural
parts of your site.
What if they don’t? What if you use variables to steer people to different parts
of your site? For example, in Figure 3-9, the top two URLs are for /chapters/
index.php. While not immediately apparent, those two URLs can represent
hundreds of individual chapters, because each of them comes with a variable
such as: /chapters/index.php?Chapter=23 for Chapter 23 of the serial.
A business with an online catalogue might have one catalogue page that
uses an item number to pull item descriptions from a database. A site that uses
a content management system (CMS) may have very few actual pages and
may only differentiate pages by a series of variables in the URL. See any of
those variables in the URLs that AWStats shows? Nope?
We don’t either.
This is another one of those things that AWStats doesn’t do that you’ll find
you need. It’s great to know how many people read chapters of one serial or
another (or read articles or visit the catalogue). But it’s not as helpful as knowing
that 2,000 people read the newest chapter (or article) and that 337 people
read 10 other chapters or that 1,500 people looked at the week’s sale item and
that 1,800 people looked at a bunch of other catalogue items.
Here’s another important piece of information that you both need and
don’t.
The /figure-skating-trivia/ directory contains a single page with
numerous short biographies of figure skaters. It has turned out to be a top
search term for SkateFic.com. It’s also the most visited page on a regular basis.
Look at the Entry and Exit numbers. You would think they’d have some
relationship to one another, but they don’t. A person could enter the site on
another page, poke around a while, find the trivia page, read for a while and
then leave for another site (or a cuppa joe) —no entry, one exit, one view. A
person could do the reverse, enter at the trivia page, exit elsewhere—one entry,
no exit, one view. A person could enter on a different page, read some, check out
the trivia, and end up reading one of the poems in a different part of the site—
no entry, no exit, one view. Finally, a person could enter the site on the trivia page
and leave immediately—a “bounce”—one entry, one exit, one view. That’s the
person we want to know more about! Do we know anything about them? No.
The trivia page is only a draw insomuch as it lures people further into the site.
The trivia page on SkateFic.com is like a controversial article on a content site or
a sale item on an e-commerce site. It’s all well and good that people look at
that page, but what you really want is people to be pulled further into the site.
It’s that supercheap sale item at the grocery store, a loss leader. How effective
your loss leader is depends on how many people get further into your site
from that page.
AWStats can’t tell you that. It can say how many people viewed a page. It
can say how many people entered there. It can say how many people exited.
What it doesn’t say is how many people saw that page and only that page.
That particular analytical association is a crucial one.

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.

Monthly History

The Monthly History has two parts: a bar chart and a table of values. The values
in the chart and the numbers in the table correspond to the Summary
information for each month. Each column of the chart has a total at the bottom
that appears on the earlier –Year– Summary. As with the –Year– Summary, the
total of Unique Visitors is not accurate. (This is the problem discussed near the
end of Chapter 2.)
In the bar chart, each colored bar is in proportion to other bars of that color.
However, there is no correlation between different colored bars. In Figure 3-1,
the tallest yellow bar and the tallest turquoise bar are the same height. But the
tallest yellow bar is 18,530 visits, whereas the tallest turquoise bar is 173,849 hits.
The Monthly History has a simple purpose. It exists solely so that you can
compare traffic numbers from month to month. Why did traffic double in February?
Why did it drop off in March?
These questions are as much business related as site related. In the specific
case at SkateFic.com, the 2006 Winter Olympics were in February, driving
interest in figure skating through the roof for a short period. But then, despite
TV coverage of the world championships in March, traffic fell as casual fans
went back to their regularly scheduled programs. With eight years of historical
data behind us, it’s easy to see that the pattern of activity was the same during
the 1998 and 2002 Olympics.
This is another benefit of having metrics. You can discern both short-term
and long-term patterns, sometimes just by looking. Does your web site peak in
August every year? Did editorial coverage in a major magazine spike traffic in
January? Do you get a lot of traffic around a particular real-world event? What
are the long-term and short-term trends?
Another way of looking at traffic, by days and hours, is shown in Figure 3-2.

Unique Visitors

The big problem with counting unique visitors is that it’s impossible to figure
out from server logs who’s unique and who’s a visitor. Figure 2-7 deals with
this problem.
There are caveats aplenty here because you’re counting visits from unique
IP addresses, not actual people:
■■ Any sort of local area network connected by a single Internet gateway
may have several users with the same apparent IP address.
■■ A proxy server owned by an ISP that caches frequently accessed pages
will show up as one unique visitor even though it represents hundreds,
if not thousands, of users. You can put a no-cache directive on your pages,
but it works only if the proxy pays attention to it. And using such a directive
may slow your site for some users.
■■ In the home, it is very common to have more than one person using the
same computer. You may have three different people visiting from one
IP address.
■■ People visit from different places: from home, work, school, or from a
laptop at the coffee shop. What looks like four unique visitors may
actually be only one.
■■ People on dial-up change IP addresses almost every time they log in. If
a person visits every day from a different IP, that person looks like 20 or
30 people, depending on how the ISP assigns IP addresses

There isn’t much you can do about these issues. It’s the nature of the
beast — and log analyzers. Google Analytics is script-based, so it does not
have many of these problems, but it has a series of issues of its own. The bottom
line is that you can’t measure unique visitors with complete accuracy. You
measure unique visitors as well as you can and you make sure to compare
apples to apples. As far as the technology goes, AWStats Unique Visitors is the
number of unique IP addresses that made requests to your web server. It’s the
best measurement a log analyzer can provide of how many people visite

Yearly Summary
AWStats calculates its metrics on a monthly basis. To produce yearly metrics,
it adds the results from all months, with the warning While this strategy doesn’t affect the other metrics, it also doesn’t produce an accurate number of unique visitors. If a particular IP appeared in January, March, and July, it would add three unique visitors rather than just one. It’s not practical to save all the logs and run the analysis on one huge lump every time
the user wants a year-to-date. Suffice it to say that the AWStats unique-visitors
metric is not accurate in the aggregate.

People and Not People

First off, there’s the difference between Traffic Viewed and Traffic Not Viewed.
In general terms, Traffic Viewed is generated by people. This isn’t a completely
sure thing, but it’s close enough for most purposes. Traffic Not Viewed is generally
generated by things that are not people. This includes robots, worms, or
replies with special HTTP status codes.
Robots are software programs that access web pages for their own purposes.
Search-engine crawlers (also known as spiders) are robots that index web pages
for inclusion in their search results. There are other spiders with less savory
purposes such as harvesting e-mail addresses for use by spammers. Worms
attack your web server, either to shut the server down (a denial-of-service
attack) or to break into the server. Either way, worms can create a large amount
of traffic that is of no interest beyond making sure it doesn’t overwhelm your
server completely. We’ll get into “special status” HTTP requests a bit later. But
in general, these are “noncontent” responses that redirect the visitor to another
page or inform the user that the page cannot be found.

Bandwidth

The bandwidth measurement is a webmaster’s first lesson in the importance
of collecting useful metrics as opposed to useless ones. With the exception of
knowing whether a site is nearing or over its bandwidth limits, there is pretty
much no useful business purpose to a measurement of bandwidth. Most web
sites don’t benefit from knowing the size of the average download.
With one small exception. Here in the United States, we tend to think of
everyone as having high-speed Internet. The fact is that broadband penetration
is less than 50 percent in the United States. According to the Organization
for Economic Co-operation and Development (www.oecd.org) only 137 million
people have high-speed access worldwide. Such figures could mean that half
of the people who visit your web site are using dial-up at 56 Kbps or less.
At 56 Kbps, loading time for pages and other content such as multimedia is
a big issue. It used to be that you had about 10 seconds for your page to load
before a user would abandon the page. Now you have about two seconds. You
can use the average bandwidth per visit along with the average pages per visit
to get a very rough estimate of how much data your average visitor is downloading
and how much time it takes.

Hits

For the first few years that we had web sites, we all quoted the number of
“hits.” It wasn’t until 1997 that we realized hits are another meaningless metric.
Why? To a web server, any access of any document — a page, a script, a
multimedia file, an image, and so on — is a hit. Because one page or site may
have lots of images, and another may be mostly all text, hits become a particularly
poor measure of a site’s performance and an even worse measure of how
a site performs in comparison to other sites.

Pages

Finally, we’ve reached a meaningful metric — pages, also known as page
views or page hits, the subject of Figure 2-4.
Back in the dark ages of 1997, when we were all using page counters, page
views were what we were actually trying to count. In AWStats, the Pages metric
is the aggregate of page requests.
Still looking at the summary on the main page, scroll down to (or click the
navigation link for) Files Type. The Pages total, 37,395, includes 19,037 static
HTML page views, 18,330 dynamic views for pages with a .php extension, 27
CGI script accesses, and 1 “com” page, which has no description. You wouldn’t
be a dummy if you didn’t even know what that file type was. As it happens, it’s
a command file, a program, but exactly what it does is beyond our scope here.
Is that com file a page? Why? A program can output a page. Not always, but
that’s one of the caveats of analytics software — assumptions. AWStats makes
the assumption that a com file is a program that outputs a page, and it counts
an access of that com file as a page.
Is it a page for business purposes? Unless you have a com file that you
specifically know produces a viewable page, it probably isn’t. And that means,
for business purposes, that this portion of the Pages metric is meaningless.
Only pages that are pages should count. If you have a lot of pages that are not
pages counting, it’s a problem. If it’s only a few, a small percentage of your
total, you’re probably safe to ignore the pages that are not pages.

Number of Visits

The Number of Visits a web site receives should be straightforward. That
would be nice and easy, wouldn’t it? Of course, it would.
No such luck, as Figure 2-6 indicates.
Like Pages, Number of Visits has two key assumptions: How long a visit is
and how much time has to pass between page loads to make one person have
two visits? Fortunately, there are industry standards — after all, this isn’t 1997.

A visit is as long as it is. As long as the visitor keeps clicking from page to page,
it’s still one visit. However, when the user stops clicking for 30 minutes, the
visit ends. If the user starts clicking again, it’s a new visit. Thirty minutes is the
industry-standard timeout for visits.
So, say a user toddles into SkateFic.com at 9:00 a.m., and between 9:00 and
9:30 she clicks from page to page, reading her favorite serial fiction. At 9:30 she
gets a phone call. For the next 28 minutes, she talks on the phone. When she
hangs up at 9:58, she finishes reading the page she left to answer the call and
loads the next page at 9:59. That’s one visit, because the break between page
loads was less than 30 minutes.
Now, say the same user is having a Grand Central Terminal sort of day. The
phone rings again at 10:00 a.m. This time the user talks for 31 minutes. When
she goes back to reading and loads a new page, she’s initiating a second visit
as far as AWStats is concerned. Same person, same day — and, if you asked
the user, same visit — but for pretty much every stats and analytics package,
it’s two different visits.
The average of 1.23 visits per visitor varies in meaningfulness. For a site that
gets a lot of returning visitors, it might have some meaning. For a site where
90 percent of visitors never return, the average doesn’t mean much, because it
is dragged down by the vast bulk of people who never return. You could have
10 people who average three visits per month and 90 people who come once and
never come back. Average visits will be 1.2, but it won’t be a very useful metric,
except to tell you that most of your visitors don’t return after the first visit.

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.

What Analytics Is Not

The short answer is: Google Analytics is not magic. It’s not some mystical force
that will automatically generate traffic to your web site. Nor is it the flashing
neon sign that says, “Hey, you really should be doing this instead of that.” And
it’s most certainly not the answer to all your web site traffic problems. No, analytics
is none of those things.
What analytics is is a tool for you to use to understand how visitors behave
when they visit your web site. What you do with that information is up to you.
If you simply look at it and keep doing what you’re doing, you’re going to
keep getting what you’re getting.
You wouldn’t place a screw driver on the hood of a car and expect it to fix
the engine. So don’t enable Google Analytics on your site and expect the application
to create miracles. Use it as the tool that helps you figure out how to
achieve those goals.

If Analytics Are So Great, Why Don’t We Have Them?

The short and simple answer to this is that medium and large companies that
can afford analytics do have them. There are many analytics software packages
that cost money, among them WebTrends, HitBox Professional, and Manticore
Technology’s Virtual Touchstone. The low-end price for web analytics is $200
per month. The high-end price? A couple grand a month is not unusual. To the
microsite, the small site, the web merchant on a shoestring, the mom-and-pop
site, the struggling e-zine, the blogger who aspires to be Wonkette but isn’t
yet—that is, to most of the sites on the web —two hundred bucks a month
sounds like a lot of money!
Then, in mid-2005, Google rocked the boat, buying a small company called
Urchin. Urchin was no Oliver Twist. It was, in fact, a runner-up for the 2004
ClickZ Marketing Excellence Award for Best Small Business Analytics Tool. Itproduct, Urchin Analytics, had a monthly cost on the low end of the market —
about $200 a month —and was designed for small businesses.
Six months later, Google did something completely unprecedented. It
rebranded Urchin’s service as Google Analytics with the intention of releasing
it as a free application. Google prelaunched it to a number of large web publications
(among them NewsForge.com, where Mary Tyler is a contributing editor).
And shortly after that, Google opened it to the public, apparently
completely underestimating the rush of people who would sign up — a quarter
of a million in two days.
Google quickly limited the number of sites that registrants could manage to
three, although if you knew HTML at all, the limitation was pathetically easy
to bypass. Google also initiated a sign-up list for people who were interested,
which eventually morphed into an invitation system reminiscent of the controlled
launch of Google’s Gmail. The moral of this story is, “Don’t underestimate
the attraction of free.”

Why Analytics?

First there were log files and only people who bought really expensive software
could figure out what the heck the half-million lines of incomprehensible
gobbledygook really meant. The rest of us used web-page counters. Anyone
could see how many people had come to a page. As long as the counter didn’t
crash, or corrupt its storage, or overflow and start again at zero, there would
be a nifty little graphic of numbers that looked like roller skates (or pool balls
or stadium scoreboard numbers or whatnot).
Around 1998, the arbiters of taste on the Internet (i.e., everybody) decided
that page counters were so 1997 and that there must be a better way.
And also about that time, web site statistics packages or “stats” came into
common use—not common use by huge businesses that could afford thousands
of dollars for software but common use by us peons who rent our web
space from hosting companies for as little as $5 a month. Stats packages basically
collect data but leave you to analyze that data. So they tell you what happens;
they just don’t put what happens into any type of business context.
If you have Windows-based hosting, you may have a Windows-specific
stats package, or your host may use the Windows version of one of the open
source stats packages. If you have hosting on a Linux web server running
Apache (and about 60 percent of web servers run Linux and Apache), you’ll
most likely have Analog, Webalizer, or AWStats, and you may have all three.
These software packages are open source under various versions of the GNU
Public License (GPL). This neatly explains their ubiquity.

Basic Analytics

Having web site statistics is one thing. Understanding what they mean and
what you should do with them is another thing altogether. If what you want is
to get into the nitty-gritty, reams of information are available to you. If, however,
what you’re really looking for is a quick, easy-to-understand explanation
of analytics and why you should care, read on.
This part of the book gives you the working knowledge you need to understand
the importance of analytics, all in three short chapters. When you’ve
finished reading these first three chapters, you’ll understand basic web measurements,
how they apply to your web site, and the difference between site
statistics and analytics. Then you’ll be ready to tackle Google Analytics.