Site Tagging based Web Analytics tools

Another category of WA tools rely on site tagging.

(1) they create an account for you on their server
e.g: Google Analytics, Yahoo Analytics

(2) You decide on the pages you want tracking metrics. Typically you will do so for your entire website.
Then tracking code is added to the pages that you want tracked.
E.g: The ever so familiar javascript tags that are added when Omniture is implemented
Remember .js :)
The WA tool may make use of cookies on your machine that already existed or create new ones

(3) Each time a visit/click happens on your website the .js code gets executed, contacts the WA server and sends this information.
So over a period of time, the server builds a repository of information that mirrors the server log file. The server may dynamically insert it in a minable format into the data mart residing at the WA server

(4) the WA tool lets you login on their server with the account you created first and view a set of reports for your website.
Each time you ask for a report, they are querying their data mart

Server Log file mining based Web Analytics tools

TOOLS BASED ON LOG FILES:

When you click www.ivarta.com on your browser, what you are doing is sending a request to the server at ivarta to send you the ivarta.com home page.
When you continue to browse on the site visiting various links all your visit data is logged into a "Log file"

A log file would be common for all visits on the server and would contain details like:
(a) Cookie
(b) Visit IDentifier
(c) sequence of click
(d) page URL Clicked
(e) timestamp of the click
(f) other parameters that are sent to the server
e.g: When you click on the login button at yahoo.com, your login_id and password are sent as parameters to the yahoo.com server
page tags are also parameters passed
These are called tagging parameters that help the server to gather more information on the visit/visitor

These log tools present a mountain of information that can be used to extract patters and understand about visitor behavior on the site.
These analytics tools mine the server log files (through a process called extract-transform-load ETL) to create a mini data mart. This can then be combined with company specific data sources to complete the picture

Example of tool based on server log files is the erstwhile HBX then erstwhile Visual Sciences and now Omniture Discover OnPremise

Web Analytics Tool Architectures: Server Logs vs. Site Tagging

Web Analytics tools come in two broad flavours:

(1) Ones that rely on server log files
(2) Ones that rely on site tagging

Let us go through their workings in detail in the coming posts

metrics: Building blocks of web analytics

Let us start with the definition of the building blocks of web analytics:
Visit/Session
User/Cookie
Request/Click

Imagine a world with only 3 machines: McA, McB and McC
and that folks named A, B and C are logged on to those machines

Consider the following sequence of browsing by the person on McA

DateTime Machine Page
11th Jan 10 AM McA Home_page
11th Jan 10:20 AM McA Category_page
11th Jan 10:30 AM mcA Product_details_page
11th Jan 10:45 AM McA add_to_cart_page
11th Jan 11 AM McA payment_page
11th Jan 11 AM mcA thankyou_page

Every page visited corresponds to a page_view/request/click
So above there were a total of 1+1+1+1+1+1 = 6 clicks/requests/page_views

so a page_view/click/request is defined as a "request for a page"

Time between the clicks is as follows
1 & 2: 20 minutes
2 & 3: 10 minutes
3 & 4: 15 minutes
4 & 5: 15 minutes
5 & 6: 0 minutes

All clicks with no idle time of 30 minutes between them form part of a

visit. So in the above sequence there was only 1 visit

So in our above example there was ONE visit and SIX clicks

Since it was from the same machine (assuming the user did not clear the

cookies), it is a single user.

Now let us change the sequence



When we visit a website, the website stores a cookie on our machine - This

is to identify us uniquely the next time we visit the site. That is how

Amazon identifies visitors on their repeat visit and shows them web pages

with products/categories viewed on earlier visit - customizing the

experience

Typical Ecomm Sales Funnel

The sales funnel

For hypothetical purposes, let us imagine a website: www.abc.com
with only 5 pages:
www.abc.com Called Home_Page
www.abc.com/cameras called Category_page
www.abc.com/cameras/camera1 called Product_detail_page1
www.abc.com/cameras/camera2 called product_detail page2
www.abc.com/addtocart called Cart_page
www.abc.com/payment called payment_page
www.abc.com/thankyou called thankyou_page



As you can see there is a purchase funnel where people can start off at any
of the pages prior to thankyou_page and complete a purchase