Case Study – How to analyze a Web Analytics Report?

Akshay Ranganath

What to see in your Analytics Report?

Once you have for the Analytics Code onto the site, what do you start to measure? Here’s a short article on it with Google Analytics and a Blog on Ubuntu Linux as an example.

The site used for recording is our own groupMAGNET blog, http://groupmagnet.blogspot.com/.

Reports from Dashboard

Visitor Count

The very first report on the site reports on the number of visits to the web site. (See article on definition of Visit).

So, in the above screen shot, on the 16th of October, I received 89 visitors to my website. For the range from Sep 28th to Oct 28th, this is the highest number. For the period of I’ve also got 213 pageviews.

The question that should come in to mind now is: Why such a sudden surge?

Content Analysis

When I see that that on October 16th there were so many visitors, I checked the Top content report. It showed something like this:

This page shows that for the 213 page views, 128 were received from just one page. This page is having a URL ending in “3-Months after Ubuntu”. So, this is the page that has created such a huge surge in the page.

Since I know that most people landed here, I want to now know if they actually found the page useful. To verify this, I invoke the report for the specific page by clicking on the first URL shown in the sceen shot above. This results in a page of the following format:

So, this page is telling me that:

  • On an average, people read this page for 3:32 minutes. This is a very good time considering that the article is really small.
  • But, it also tells me that 99.21% of the users bounced. This means that after reading this article, the visitor to my site navigated to some other web site. This means:
    • I am offering something that is of use to a lot of readers (the huge number of views) BUT
    • My site is not offering a range of solutions to keep the users hooked on.

Hence, if I were to run huge ad campaigns, etc for some other customers, it could not be a big advantage.

The next question that comes to mind is: How did people land on my site?

How do people reach the site?

To answer this question, go back to the first page – the Dashboard and look at the following report (TrafficSources Overview):

This simple report has the details that shows the mechanism by which people are landing on my site.

So, it says that the most number of users landed on my blog via Referring Sites. A referring site is any site that has a link to this blog. (Sites like Google, etc are treated as a special case and reported in the Search Engines).

Hence, my web site is famous not because a lot of people reached through Google Search but, some particularly important source is referring to my site. Who is this site? To see this detail, click on the view report link.

Here the details shows that the top traffic sources are Ububtuhq.com and Digg.com sites.

Conclusion

From the above discussion, we see that the article “3-months after Ubuntu” has drawn a lot of viewers from the sites digg.com and ubuntuhq.com. Knowing the history of what had happened, I can now conclude that:

  • Digg.com and UbuntuHq.com attract good quality viewers for topics related to Ubuntu Linux
  • These sites (digg.com and ubuntuhq.com) also have ability to target users who are specifically interested in a particular topic (Ubuntu Linux)
  • If I have anything to say on Ubuntu, it is probably a good idea to link the article from digg.com and ubuntuhq.com since it gives me viewers who are actually reading my material. (Coupled with the fact that I got around 10 comments, it also means that they actually read the contents and try to understand it too!)

PS: Google Analytics is a free tool. Anyone with a Gmail Id can get the necessary Javascript code for implementing Google Analytics.

How to install packages on Ubuntu behind a Proxy Server?

-Akshay Ranganath

While working behind a proxy, the normal

sudo apt-get install 

may not work. This is because of the command line interface does not detect the proxy settings. To ensure a smooth installation without unnecessary hassles of digging through the settings, using the UI based approach is a lot more easier.

5 steps to setup Synaptics Package Manager for a proxy based network

  1. Open the Synaptic Package Manager by choosing System > Administration > Synaptic Package Manager in the menu.
  2. Provide password for the application to start
  3. Set the proxy settings by using the following menu: Settings > Preferences > Network
  4. Now provide the proxy details for both HTTP and FTP along with the port number.

  5. Click apply and the Synaptics Manager is now ready to download and install packages.

5 steps to installing packages

Once the proxy setting is done, packages can be installed in a very simple manner.

  1. Click on Search button on top
  2. In the search box, choose the package to install. In the screen shot I’ve given WordPress.

  3. Click OK and a result is displayed. Choose the application you are interested in by clicking on the checkbox. Here, you will get a drop down with an option to Mark for installation (you can even choose to uninstall/reinstall/upgrade). Choose this option. Automatically, the package manager will choose all the dependencies to be installed along with the application.

  4. The Apply button on top will now be enabled. You can go with search and choose as many other packages as you want to install.

  5. Click on the Apply button and the packages will be downloaded and installed.

And that’s about it – you are on your way to install and upgrade packages easily on Ubuntu!

10 Simple steps to a faster Ubuntu booting.

-Akshay Ranganath

  1. Open the file /etc/fstab in gedit (Applications > Accessories > Text Editor)
  2. This file will have the partition details of .the hard disk. For all the Windows partition, it will have data of the following format:
    UUID=9877-489A  /media/sda1     vfat    defaults,utf8,umask=007,gid=46 0       1
  3. If the last value is a 1 then, it means that the default setting is to scan your Windows parition every time the system boots. This is not necessary and most importantly waste of time since it is a Windows partition anyway.
  4. Just set the value to a 0. That is for all those lines having the word vfat, set the sixt tab-separated value to a zero to exclude checking.
  5. Save the file on your desktop as fstab.
  6. Open the terminal by using the option Application > Accessories > Terminal
  7. Make a copy of the fstab file for safety by executing the command:
    sudo cp /etc/fstab /etc/fstab.orig
  8. Copy the modified file to the /etc/ directory by giving the command:
    sudo cp /home/{username}/Desktop/fstab .
  9. This should copy the updated fstab
  10. Reboot and see a blazingly fast system!

Traffic Reporting on Analytics

Unique Visitor

The unique visitor metric basically tries tho measure the number of unique people who visited the site within a given period of time. The visitor is counted exactly once for the period. Generally, the unique visitor metric is calculted for a specific period of time. Some examples are:

  • Hourly unique visitors
  • Daily unique visitors
  • Monthly unique visitors and so on.

To clarify, if I visit this blog at 10:30 am and then 6:30 pm, on the 3rd of a month and then visit at 1 pm on the 15th of the month, the report would look as follows:

Hourly unique visitors for 3rd
10-11 am : 1
6-7 pm: 1

Hourly unique visitors for 15th
1-2 pm : 1

Daily Unique visitor
3 rd of July: 1
15th of July: 1

Monthly Unique visitor
July: 1

This metric is used to loosely identify the number of unique people who saw the site. It tries to map the usage of the site to an individual human – this could help in tracking the individual behaviour.

If you have a database background, this is similar to saying “select distinct (visitor details) during the time interval chosen”

Definition

SiteCatalyst & Google Analytics: Unique visitors represent the number of unduplicated (counted only once) visitors to your website over the course of a specified time period. A unique visitor is determined with cookies.

There are some caveats to using this metric. These are quite elegantly explained at Matt Belkin’s blog.

Traffic Source Reports

This report represents the percentage of visitors who have reached the site directly (by typing the URL into the browser), referrer (from a link on some other page) and Search Engines.

This report can be seen using the option Traffic Sources > Overview.

Referrer

A referrer is some other site from which a user could navigate to your site. If there is a link to any page of say Site A to your site, then the Site A refers to your site.

The report for referrer can be used to identify the behaviour of the people who are landing on your page. So for example, if you have a blog that is being referred from two of your friend’s blogs, Blog1 and Blog2, the details will show how many people were referred from each of the two sites. Say something like this:

Referrels
Blog1 – 10
Blog2 – 20

Definitions

SiteCatalyst: (Referrer) A domain or URL used outside of your defined domain to access your site. The Referring Domains Report and the Referrers Report break referrer data into domains and URLs so that you can view the instances that visitors access your site from a particular domain or URL. For example, if a visitor clicks a link from Site A and arrives at your site, Site A is the referrer if it is not defined as part of your domain. During SiteCatalyst implementation, your Omniture Implementation Consultant will help you to define the domains and URLs that are part of your web site.

Google Analytics: (Referrals) A referral occurs when any hyperlink is clicked on that takes a web surfer to any page or file in another website; it could be text, an image, or any other type of link. When a web surfer arrives at your site from another site, the server records the referral information in the hit log for every file requested by that surfer. If a search engine was used to obtain the link, the search engine name and any keywords used are recorded as well.

Referrer – The URL of an HTML page that refers visitors to a site.

This metric is especially useful in seeing destinations from which people are arriving on a site. As the site grows older this list tends to get bigger and bigger. Generally, it’ll probably show nothing since many people would be accessing the site directly due to word-of-mouth marketing.

Generally, for the home page, there will be a lot of “Direct” hits, if the site is well known. After that, the pages are reached using some menu or links. These are not counted as referrer since the “referring page” is also on your own site. So say, you have the site, http://goupmagnet.blogspot.com and an about us page at http://groupmagnet.blogspot.com/2007/06/about-us.html. If user first types the home page URL and clicks on the “About Us” link, the traffic source report will show only one hit for a “Direct” view. The navigation within the site is not recorded here.

Search Engines

People referred from the search engines are (generally) not counted in the Referrer reports. This is just to segregate the referrers from the search engines. For a search engine, the search key used can also be recorded. This in turn can be used for Search Engine Marketing.

For example, if a user hits the Group Magnet blog using the key GroupMagnet, via google, the site will have two reports as shown below.

To view the Search Engine report, the navigation is Traffic Sources > Search Engines.

To view the keyword report, the navigation is Traffic Sources > Search Engines > Keyword.

The other option is Traffic Sources > Keywords.

Definition

Google Analytics: A keyword is a database index entry that identifies a specific record or document. Keyword searching is the most common form of text search on the web. Most search engines do their text query and retrieval using keywords. Unless the author of the web document specifies the keywords for her document (this is possible by using meta tags), it’s up to the search engine to determine them. Essentially, this means that search engines pull out and index words that are believed to be significant. Words that are mentioned towards the top of a document and words that are repeated several times throughout the document are more likely to be deemed important.

References

PageRanking in SEO

This article is intended to provide a fair knowledge about PageRanking in SEO. PageRank is one of the methods Google uses to determine a page’s relevance or importance. Before going into details it’s better to mention the short hands used in this article.

PR: Page Rank of the page.

Backlink: If page A links out to page B, then page B is said to have a “backlink” from page A.

What is a PageRank?

In short PageRank is a “vote”, by all the other pages on the Web, about how important a page is. So a link to a page from any other page counts as a vote of support. If there is no link it doesn’t mean it’s a vote against the page, its only not having a supporting vote.

Quoting from the original Google paper, PageRank is defined like this:

Lets assume page A has pages T1…Tn, which point to it (i.e., are Backlinks to page A).

The parameter d is a damping factor which can be set between 0 and 1. Usually “d” is set to 0.85
C(A) is defined as the number of links going out of page A.

The PageRank of a page A is given as follows:
PR(A) = (1-d) + d (PR(T1)/C(T1) + … + PR(Tn)/C(Tn))

Note that the PageRanks form a probability distribution over web pages, so the sum of all web pages’ PageRanks will be one.

Let us dig it deeper.

PR(Tn) : Each page has a notion of its own self-importance. That’s “PR(T1)” for the first page in the web all the way up to “PR(Tn)” for the last page
C(Tn) : Each page spreads its vote out evenly amongst all of it’s outgoing links. The count, or number, of outgoing links for page 1 is “C(T1)”, “C(Tn)” for page n, and so on for all pages.

PR(Tn)/C(Tn) – so if our page (page A) has a backlink from page “n” the share of the vote page A will get is “PR(Tn)/C(Tn)”

d : – All these fractions of votes are added together but, to stop the other pages having too much influence, this total vote is “damped down” by multiplying it by 0.85 (the factor “d”)

(1 – d) : The (1 – d) bit at the beginning is a bit of probability math magic so the “sum of all web pages’ PageRanks will be one”: it adds in the bit lost by the d.It also means that if a page has no links to it (no backlinks) even then it will still get a small PR of 0.15 (i.e. 1 – 0.85). (Aside: the Google paper says “the sum of all pages” but they mean the “the normalised sum” – otherwise known as “the average”.

How is PageRank Calculated?

It’s obvious from the formula that PR of a page depends on PR of the pages pointing to it. But we won’t know what PR those pages have until the pages pointing to them have their PR calculated and so on… And when you consider that page links can form circles and it seems impossible to do this calculation!
Its really not that difficult as it seems. According to Google Paper we can just go ahead and calculate a page’s PR without knowing the final value of the PR of the other pages. That seems strange but, basically, each time we run the calculation we’re getting a closer estimate of the final value. So all we need to do is remember each value we calculate and repeat the calculations lots of times until the numbers stop changing much.

Lets take the simplest example network: two pages, each pointing to the other:

Each page has one outgoing link (the outgoing count is 1, i.e. C(A) = 1 and C(B) = 1).

Guess 1

We don’t know what their PR should be to begin with, so let’s take a guess at 1.0 and do some calculations:

The numbers aren’t changing at all! So it looks like we started out with a wrong guess.

Guess 2

let’s start the guess at 0 instead and re-calculate:

PR(A) = 0.15 + .85*0

= 0.15

PR(B) = 0.15+ 0.85*0.15

= 0.2775

And again:

And again

and so on. The numbers just keep going up. But will the numbers stop increasing when they get to 1.0? What if a calculation over-shoots and goes above 1.0?

Guess 3

Well let’s see. Let’s start the guess at 40 each and do a few cycles:

PR(A) = 40 PR(B) = 40

First calculation

And again


Clearly those numbers are heading down. It sure looks the numbers will get to 1.0 and stop.

Principle: it doesn’t matter where you start your guess, once the PageRank calculations have settled down, the normalized probability distribution” (the average PageRank for all pages) will be 1.0

So lets take a look at some of examples and study how the PageRank is Getting affected in various scenarios. Values mentioned as PRs in the examples are calculated according to the formula mentioned above.

Example 2
A simple hierarchy with some outgoing links


As you’d expect, the home page has the most PR – after all, it has the most incoming links. But what went wrong is the average PR is not 1, as said earlier.

Why is it so? Take a look at the “external site” pages – what’s happening to their PageRank? They’re not passing it on, they’re not voting for anyone, they’re wasting theirs.

Example 3

Let’s link those external sites back into our home page just so we can see what happens to the average…


Look at the PR of our home page! All those incoming links sure make a difference.

Example 4

A simple hierarchy

Our home page has 2 and a half times as much PR as the child pages.

Observation: a hierarchy concentrates votes and PR into one page

Example 5


Looping

All the pages have the same number of incoming links, all pages are of equal importance to each other, all pages get the same PR of 1.0 (i.e. the “average” probability).

Example 6


Extensive Interlinking – or Fully Meshed

The results are the same as the Looping example above and for the same reasons.

Example 7

Hierarchical – but with a link in and one out.

We’ll assume there’s an external site that has lots of pages and links with the result that one of the pages has the average PR of 1.0. We’ll also assume that there’s just one link from that page and it’s pointing at our home page.

In example 4 the home page only had a PR of 1.92 but now it is 3.31!
Not only has site A contributed 0.85 PR to us, but the raised PR in the “About”, “Product” and “More” pages has had a lovely “feedback” effect, pushing up the home page’s PR even further!Priciple: a well structured site will amplify the effect of any contributed PR

Example 8

Looping – but with a link in and a link out


Well, the PR of our home page has gone up a little, but what’s happened to the “More” page?
The vote of the “Product” page has been split evenly between it and the external site. We now value the external Site B equally with our “More” page. The “More” page is getting only half the vote it had before – this is good for Site B but very bad for us!

Example 9


Fully meshed – but with one vote in and one vote out


That’s much better. The “More” page is still getting less share of the vote than in example 7 of course, but now the “Product” page has kept three quarters of its vote within our site – unlike example 8 where it was giving away fully half of it’s vote to the external site!
Keeping just this small extra fraction of the vote within our site has had a very nice effect on the Home Page too – PR of 2.28 compared with just 1.66 in example 8.

Observation: increasing the internal links in your site can minimize the damage to your PR when you give away votes by linking to external sites.

Principle: If a particular page is highly important – use a hierarchical structure with the important page at the “top”.
Where a group of pages may contain outward links – increase the number of internal links to retain as much PR as possible.
Where a group of pages do not contain outward links – the number of internal links in the site has no effect on the site’s average PR. You might as well use a link structure that gives the user the best navigational experience.

Site Maps

Site maps are useful in at least two ways:
If a user types in a bad URL most websites return a really unhelpful “404 – page not found” error page. This can be discouraging. Why not configure your server to return a page that shows an error has been made, but also gives the site map? This can help the user enormously
Linking to a site map on each page increases the number of internal links in the site, spreading the PR out and protecting you against your vote “donations”

Example 10

A common web layout for long documentation is to split the document into many pages with a “Previous” and “Next” link on each plus a link back to the home page. The home page then only needs to point to the first page of the document.

In this simple example, where there’s only one document, the first page of the document has a higher PR than the Home Page! This is because page B is getting all the vote from page A, but page A is only getting fractions of pages B, C and D.

Principle: in order to give users of our site a good experience, we may have to take a hit against our PR. There’s nothing we can do about this – and neither should we try to or worry about it! If our site is a pleasure to use lots of other webmasters will link to it and we’ll get back much more PR than we lost.

We can also see the trend between this and the previous example? As we add more internal links to a site it gets closer to the Fully Meshed example where every page gets the average PR for the mesh.Observation: as we add more internal links in our site, the PR will be spread out more evenly between the pages.

Example 11


Getting high PR the wrong way and the right way.
Just as an experiment, let’s see if we can get 1,000 pages pointing to our home page, but only have one link leaving it…

Those Spam pages are pretty worthless but they sure add up!

Observation: it doesn’t matter how many pages you have in your site, your average PR will always be 1.0 at best. But a hierarchical layout can strongly concentrate votes, and therefore the PR, into the home page!
This is a technique used by some disreputable sites (mostly adult content sites). If Google’s robots decide you’re doing this there’s a good chance you’ll be banned from Google!

On the other hand there are at least two right ways to do this:

1. Be a Mega-site

Mega-sites, like http://news.bbc.co.uk/ have tens or hundreds of editors writing new content – i.e. new pages – all day long! Each one of those pages has rich, worthwile content of its own and a link back to its parent or the home page! That’s why the Home page Toolbar PR of these sites is 9/10 and the rest of us just get pushed lower and lower by comparison…
Principle: Content Is King! There really is no substitute for lots of good content…

2. Give away something useful

http://www.phpbb.com/ has a Toolbar PR of 8/10 and it has no big money or marketing behind it! How can this be?
What the group has done is write a very useful bulletin board system that is becoming very popular on many websites. And at the bottom of every page, in every installation, is this HTML code:
Powered by phpBB
The administrator of each installation can remove that link, but most don’t because they want to return the favour…
Imagine all those millions of pages giving a fraction of a vote to http://www.phpbb.com/?
· Principle: Make it worth other people’s while to use your content or tools. If your give-away is good enough other site admins will gladly give you a link back. Principle: it’s probably better to get lots (perhaps thousands) of links from sites with small PR than to spend any time or money desperately trying to get just the one link from a high PR page.

Finally

PageRank is, in fact, very simple. But when a simple calculation is applied hundreds (or billions) of times over the results can seem complicated.

Reference:
This article is extracted from a paper written by Ian Rogers. He has been a Senior Research Fellow in User Interface Design and a consultant in Network Security and Database Backed Websites.
It was sponsored by IPR Computing Ltd – specialists in Secure Networks and Database Backed Websites

Blogging to Blogger or wordpress from our own web pages.

By Chandra Nayana

Blogging from our own web pages to Bloggers.com or WordPress.com is simple.
What we have to do is just follow the steps given below:

Suppose we have our own pages in bloggers.com what we have to do is

Step 1:

First login to your bloggers.com site, Then you will be taken to home page as shown below

Step 2:

Then click on the layout in Manage your blogs tab as shown below.

Step 3:

Then click on ‘Add page element’ as shown below.

Step 4:

Then it will open up a window asking for type of page element required as shown below.

As we need to add only HTML code, select HTML/JavaScript element.

Then it will open up a window asking for title and content as shown here:

Then enter title as you need and content given below.

Content:

U can copy code from following link:

Code for Blogging to bloggers and wordpress websites



Then if you view the blog the blog willcontain blogger and wordpress buttons to post to Blogger or wordpress blogging sites as shown here.



Be surprised with Ubuntu!

Today, I installed Ubuntu Linux just to try out what all the hoopla was about. It was a pleasant surprise that I faced.

First of all some really heartening facts:

  1. The installer is genuinely easy!
  2. Installer detects your hardware and good package of software comes pre-installed.
  3. The system works – especially with Firefox inbuilt, and good help it is really quite easy to use.

Let me explain the points in detail.

Easy Installation

Believe me! This installation was a breeze! The last time I did a Linux install, it was when I was in college. At that point of time, it was a technical wizardry if you could install this beast of an operating system, make it work and also ensure that it did not erase and crash you existing Windows installation.

Ubuntu’s unique Live CD installer is a welcome change. Instead of first installing the Operating System, you can first simply start your machine on Linux by the CD itself. So, you not only have an installer, but, you can boot in, see the system in operation and only when you are sure, you can go ahead and install it.

Next, the partitioning was a dream. The most painful area of using Linux was always the partitioning. Sure, Red Hat had some nifty tools, but, the sheer screen showing the partitions was enough to send shiver down the spine of any non-geeky user. In Ubuntu, all I had to do was this:

  1. Choose which drive I wanted for Ubuntu. For this, I chose my D:\
  2. Then, I just cleared off all the junk songs and made some space and defragmented the hard disk. This is to ensure that when the existing disk is partitioned off no valuable data is lost. This is one step that takes a really long time and HAS to be done of Windows. For me, it took about 8 hours to format about 28 GB of my hard disk.

This was like a pre-installation procedure.

Then, I restarted my machine with the Live CD and started the istallation. Just do the following during the partitioning:

  1. Choose manual formating option instead of the guided ones – unless you are planning to have only Ubuntu on your system
  2. Choose the drive you want for installation and delete that partition from the list
  3. Add a partition called swap – this should be 1.5 times the size of RAM
  4. Add a / partition which should be at least 2 GB – this is where all the files of Ubuntu will reside.
  5. Click on the next few steps and you are on your way to installing Ubuntu

Remember that while selecting the partition, just choose the partition to begin from end so that the data is not lost.

The best part was that Ubuntu automatically detected the settings and even configured the dual-boot software (GRUB). I did not have to make some geeky things here to get it working. Though I did read through a lot, which was more of a habit 🙂

Good Software Package

The next pleasant thing was the very good set of software that it provided out of the box. There was the Open Office and Firefox, which I am sure will serve most needs of most people. After all, even in Windows, most of the time, most people use the browser and the MS-Office. Since a browser and an MS-Office like software is provided right from installer, the pain of searching, downloading and installing is directly reduced.

Then, the installer was automatically able to import the settings from Windows – so much so that it even imported my Internet connection details and the Wallpaper! This was really a big surprise to me. When I’d installed Red Hat in the bygone days, internet connection never ever worked with Linux. But this time, it was simply fabulous.

Apart from the basic software, the OpenOffice Writer (compatriat of Word) has the ability to directly export files as PDF which is very helpful for producing professional looking documents.

If you are a programmer, then this is again a real help. The system comes pre-installed with Perl. And with just this one command
sudo apt-get install apache

I managed to install apache. One step installation, something that you expect as a user if Windows is true on Ubuntu. And this is a the biggest relief! I did not have to sit and wade through pages and pages of help on the dependencies and what not. The above simple command detected everything needed and automatically installed everything.

Similarly, with one command I installed php and Java! If you are a developer, this is like a dream (unless you a .Net developer).

System Works!

And coming to the final part of the best thing of Ubuntu, it works! It works the very first time I booted from the Live CD and it worked the very first time I installed. It even detected a wireless connection that never ever worked on Windows! The system also understood that I have NVidia graphics card and got the software for it.

The moment I installed the OS, it said that there were 71 things to be updated – it promptly got them and installed. I did not have to break my head on what to find and update. Just like one click Windows updater, the Ubuntu updater went on and brought my system in synch with the latest. This was almost like a dream come true for me!

Conclusion

All in all, the installation, migration and the use of this new Ubuntu Linux has been a very pleasant and happy experience for me. For all those of you out there, believe me, trying Ubuntu is not so risky as it used to be with other distributions of Linux. Just to make things easier for migration, I’d recommend you do the following:

  1. On Windows, install OpenOffice and get a feel of the software. This is just to wean you away from MS-Office.
  2. Install Firefox and try it. This will ensure that you know how to access internet without IE.
  3. Use Live CD and boot into the system a few times just to get a feel of the system. To get the Live CD, just register here and get a CD shipped to your home – in case you don’t want to download it.

And be on your way to start using Ubuntu – Linux for human beings!

Basic Metrics

-Akshay Ranganath

Now that we’ve see what analytics is and how to start analytics, let’s get on to the next stage – seeing the metrics.

At this point, the assumption is that you have a site to analyze and the analytics code has been pasted onto each and every page that you want to be tracked via the analytics software. Like I explained before our blog is using Google Analytics. Hence, I’ll be showing the screen dumps from the Google Analytics site.

What metrics to see?
This is a very good question! The metrics that you would be interested to see will generally depend on what you intend to measure in the first place. Generally though, there is a basic set of metrics that needs to be captured for any higher level of analysis to take place. In this article, I’ll be covering these simple and general metrics.
For sake of clarity and better understanding, I’ll be defining the various metrics, as defined in Google Analytics glossary (1) and the Omniture SiteCatalyst (2) help center. This is just to give you a glimpse on the little differences that vendors may sometime have in the way their metrics work.

So, let’s get on with exploring the metrics.

Hit

Hit is a metric that is more of a remnant of the log-file based era. Basically, it was a measure of number of times any resource was served from a web server. For example, if your page has a logo, a stylesheet file and the actual HTML, one hit would be reported for each of the file – in effect when this page loaded, the site would record three hits.
Since this measure is not of much use, it is not reported on most of the modern tools.

Definitions

SiteCatalyst: A request to the web server for a file. This can be an HTML page, an image (jpeg, gif, png, etc.), a sound clip, a cgi script, and many other file types. An HTML page can account for several hits: the page itself, each image on the page, and any embedded sound or video clips. Therefore, the number of hits a website receives is not a valid popularity gauge, but rather is an indication of server use and loading.

Google Analytics: A single entry in a server log file, generated when a user requests a resource on a website; a request can result in an error or a successful transmission of any data type.

PageView

Page view is the next higher order metric. This measures the number of times a particular page having the analytics code is loaded by the browser. So, if the same page mentioned above were loaded, the analytics code would be present in the HTML page and hence, only one pageview would be noted by the analytics program.

This is the most basic metric that is measured by most of the analytics packages.

Definitions

SiteCatalyst: A request for a full-page document (rather than an element of a page such as an image, movie, or audio file) on a website; hits are not a useful comparison between websites or parts of the same website, since each webpage is made up of an arbitrary number of individual files

Google Analytics: A pageview is an instance of a page being loaded by a browser.

How to see?
On the Google Analytics do the following to see the PageView report:
Visitors > Visitor Trending > Pageviews

Visit / Session

A session or a visit is the interaction of a user with the web site. If I access a site, close the site, access something else and then return back to the site, then, I’ve visited the site twice. If I access a site and leave it idle for a specific period of time and then try again, then, it is considered a new visit or a session.

This type of a definition is necessary since the session or visit is based on cookies. A concept of session is needed to form a base of an interaction from which any meaning can be derived. For example, if you go to a shop, visit once and then return again to exchange some article, for the shop, you’ve visited twice. Based on this, they can form some information like you came to the shop twice, but bought only once. Or some data like, you came to the shop, stayed for about 30 minutes and then made a purchase of $ 100.

Of course, there is caveat in terms of the visit from a computer. Since it is based on cookies, if you clear the cookies in the middle of an interaction or if the site is accessed by your friend when you left for a quick break – such details cannot be captured.

Definitions

SiteCatalyst: A visit is a term that refers to a visitor’s access to a website. The visit begins when a person first views a page on your company’s website. It will continue until that person stops all activity on the site for 30 minutes. For example, if you log in to http://www.omniture.com, you have one instance of a visit that will last until you have incurred 30 minutes of inactivity, i.e. you have closed the browser or left your computer. If you are inactive for more than 30 minutes, and then you log on again, it is considered a new visit. SiteCatalyst also terminates a visit after 12 hours of continuous activity.

Google Analytics: A period of interaction between a visitor’s browser and a particular website, ending when the browser is closed or shut down, or when the user has been inactive on that site for a specified period of time.
For the purpose of Google Analytics reports, a session is considered to have ended if the user has been inactive on the site for 30 minutes.

How to see?
Visitors > Visitor Trending > Visits

Visitor

In the simplest terms, a Visit is performed by a visitor. This is the level where we are trying to associate an human actor in the entire process of interaction.

SiteCatalyst: A Visitor is a construct designed to come as close as possible to defining the number of actual, distinct people who visited a website. There is of course no way to know if two people are sharing a computer from the website’s perspective, but a good visitor-tracking system can come close to the actual number. The most accurate visitor-tracking systems generally employ cookies to maintain tallies of distinct visitors.

Google Analytics
: The number of actual, distinct people who visited a website. Omniture employs cookies to maintain tallies of distinct visitors.

How to see?
Just click on the Visitors option on the left hand menu.

Summary
Trying to co-relate whatever we’ve learnt till now with an example:
If I were to go to Amazon.com and view some book article, probably add a few things to my cart, edit or remove items and then check out and close the site, I am the visitor who generated so many page views, one each for all the pages that I saw. If I did all the activities without closing my browser and without leaving my browser idle for more than 30 minutes of a time, I’ve done the entire job in one visit!

This covers a short chapter on the absolute very basic metrics of any analytics package.

In the subsequent chapters, I’ll be examining how the metrics can be used to derive various other details for a site.

References:
1. Google Analytics Glossary
2. Omniture SiteCatalyst Help.

Starting Web Analytics – Part 2

Getting down and dirty with Google Analytics
-Akshay Ranganath

In the previous article I’d written about how to start the implementation of an analytics program. In this article, I’ll write about rolling your sleeves and getting into the actual implementation.

Note that the Analytics product that I am using is Google Analytics. In your case it may the product you have chosen but the overall steps will remain similar.

The steps in setting up an analytics program are as follows:

  1. Sign up for an analytics program
  2. Identify the site you want to track
  3. The vendor provides JavaScript tracking code.
  4. Take this code and paste it into each and every page that you want to track.
  5. Whenever a visitor to your website accesses a page, it is downloaded onto the visitor’s machine and the JavaScript code executes and sends out the tracking information to the data center of the analytics vendor.
  6. Log in to your reporting area and see the Analytics reports.

The above process is a simplification of the entire sequence of steps necessary, but it is also quite complete if the initial aim to just “get on with the tracking”.

Starting Analytics Program using Google Analytics

  1. Login to the Analytics site (http://www.google.com/analytics/) using your gmail id.
  2. In the screen, choose the option “Create New Account”
  3. Fill in the details like the URL of the site to track and the time zone that you’d like. The time zone details are needed for reporting like “Unique visitors in a day”.
  4. Enter your details in the next screen
  5. Go through the Privacy Policy and accept it.
  6. At this stage, Google Analytics displays a screen having the tracking JavaScript code. Make a note of this.
  7. Take this JavaScript code and paste it on each and every page that needs to be tracked just before the end of the tag.
  8. Once this is done, come back to Google Analytics. It will show a screen similar to the one below. If you click on the “Check Status” button, the site will start to try and build analytics reports. Please note that after hitting the “Check Status” button, leave it alone for a day or two for the analytics to start getting accumulated.
  9. Once the reporting starts to work, when you log into the analytics site, it will look like below. Click on view reports and stat analyzing!

Starting Web Analyics – Part 1

How to start collecting Web Analytic metrics?
By – Akshay Ranganath

Introduction
The following tutorial is a short primer on how to start collecting the analytics on your website. The goal of this article is explain what is Web Analytics, identify why it is necessary and explain how to start an implementation. The key take-away is help the audience to get a basic understanding and use of Analytics.

No individual product is examined or recommended at this stage. The following diagram explains the basic strategy.

What is Web Analytics and KPIs?
According to Wikipedia (1), “Web Analytics is the study of website visitors”. Using analytics, you can see what the users to the web site are doing, where are they coming from and are they performing the actions that you were expecting them to do.

The question that comes into the mind at this point of time is, “Why do I want to collecting these details?” Well, the answer varies from website to website but, the basic reason is to measure the performance of your web-site against some objectives that you had in mind when you created the site. Some of the possible objectives could be:

  • Are people coming to my site whenever they search “Book” as I am selling books online?
  • Is the new ad that I put on Google search working fine? Is it attracting anyone at all?
  • I just re-designed my site to show the new globally-local image. Is it a hit or are people still vary to use my services?
  • And so on..

These measures are called as Key Performance Indicators (KPIs). According to Wikipedia (2), “key Performance Indicators (KPI) are financial and non-financial metrics used to quantify objectives to reflect strategic performance of an organization. KPIs are used in Business Intelligence to assess the present state of the business and to prescribe a course of action.”

So, Web Analytics is used to track various defined KPIs for a web site. The primary aim of any organization is to define the KPIs correctly. If you don’t know what you want to measure, you’ll probably end up measuring what you never wanted. (Something akin to Cheshire cat and Alice in Wonderland!)

How do I start Web Analytics?
If you are a blogger or a an enterprise embarking on the world of web analytics, the easiest way to start is to follow the three step approach:

  • Start collecting basic metrics on your site
  • Brain storm and identify the KPIs for your web site
  • Tweak the implementation and focus on the reports that delivers value to you

Let me explain each of the steps in detail.

Start collecting metrics
The first step in analytics is to first “go and get the hands dirty” concept i.e., start an implementation on the site without too much of brain work. Let the brain work go on in parallel.

The reason for this type of an approach is that most often, we don’t know how our site is performing. For example, when I had implemented analytics on my blog, I just wanted to see where people are coming from geographically. Instead I found some interesting behaviour where Google was directing users when they had searched some terms like “VIT” and “Cognizant campus”. I had never imagined that someone would land on my blog via Google since that had never been my intention.

In a similar way, the basic implementation will throw up some real surprises to you too. For example, people may be landing on your site due to a keyword search on Google but, that keyword would be a happenstance and not related to what you do. Or better yet, something that you’d never imagined that people would be interested in!

This basic implementation will also give you a starting point to examine and brain storm in identifying the metrics that should be measured on the site.

If you are simply trying to implement analytics for a blog, then try a free product like Google Analytics. If you are an enterprise, the product to choose is a bit more tough (and beyond the scope of this article). Whatever the product you choose, as a first step, go with a very basic implementation – something akin to out-of-box usage.

Brainstorm and identify KPIs for your Web Site
Once you’ve jumped into the ocean (so to speak), you need to dedicate energy into identify what is it that you are trying to measure. This is the core of analytics and will need a lot of elaboration. At a high level, this is what you should do:

  • Check what is your business
    • are you a retailer
    • an online book seller
    • a news publishing company, switching to online media
  • Identify why you are on the web
    • do you intend to generate leads on the web
    • do you want to sell more online
    • do you want to create interest for your shop
  • Correlate with the findings in the basic reports obtained earlier
    • are people coming to your site because they wanted to buy something
    • are people coming in for something that you don’t do
    • are they guided correctly from your keyword ads on Google/Yahoo and so on

This is an area that is very specific to the area of business. The main aim here is to identify why you are online and if the web site’s performance aligned with the strategy of the core business. Once this is determined, you can decide on the following factors:
In my line of business, what should I start to measure
Looking at the performance, is my site fulfilling its role or are people being misguided

Once this step is complete, jump into the third and continuing phase – Optimizing.

Optimizing
This is a stage where you tweak your analytics implementation, key word marketing, email marketing or SEO results to better suit the KPIs that are relevant to the business. For example, if the above analysis shows that people are hitting your site for a wrong keyword, use a SEO technique to ensure that your site appears for the more relevant keywords.

The ability to optimize the implementation of Analytics is dependent on the product being used. For example, Google Analytics is out-of-box while Omniture SiteCatalyst offers many ares of tweaks. Understand your product and implement the tweaks.

Conclusion
The stage of brainstorming and optimizing is a continuous one. Never get too complacent about your site’s performance. Keep measuring and keep improving!

The article is intended as just a thousand feet high view on the process of analytics. A lot of area has been covered in here and over a period of time, I’ll be building on the concepts introduced here.

References:

  1. Web Analytics From Wikipedia.
  2. Key Performance Indicators from Wikipedia.