Sunday, August 23, 2009

Web Analytics: Maximizing Profitability by Maximizing Data.

Just like any living organism or in this case, an electronic organism, it seems that Web Analytics has evolved to keep up with the rapid changes brought on by time. That's the way it should be for if a system stays stagnant while the world surrounding them undergoes a metamorphosis then surely, that system will be considered a white elephant and rendered useless.

Web Analytics used to be a simple system, a system wherein website administrators based their sites success on user page views, hits, number of top exit pages, website engagement and visitor screen resolution.

That is Traditional Web Analytics.

It's dead.

The methods mentioned above simply wont work anymore in this cutthroat online world where competition seems to have multiplied a thousand fold. User Page Views and Hits simply shows the amount of current users in your site, while number of top exit pages show the amount of people who have left your site, website engagement and visitor screen resolution shows whether your site works well with a user and within his machine.

Traditional Web Analytics answers WHAT but not WHY. In other words it dishes out trivial data.



As previously stated, Web Analytics has evolved and its systems has incorporated more in-depth features such as click density analysis, visitor primary purpose, task completion rates, segmented visitor trends and multichannel impact analysis.

In simpler terms, you will be able to measure what links within your site is most clicked, what the customer wants to do, whether your users achieved what they want to do within your site, when most customers go to your site and how other websites impact yours.

These data are usually gathered by using FAQ pages, statistics on what page users usually arrive on and leave on, what banner ads bring in the most customers and a user feedback page.

With all the tools available, how can one use Web Analytics as a strategic advantage over competitors?

Web Analytics obviously provides you with a gigantic amount of data. The challenge now is whether you can interpret that gigantic amount of data and transform it into a gigantic lead over your competitor within your market.

Focus on Customer Centricity

Only 15 - 25% of website traffic comes to purchase a specific item within a certain website while others do rather trivial things such as research, job offerings, complain and download media.

To be successful, one should entice its users to actually purchase and to do that, one should centralize on its operations on the market. Entice customers? How?

Simply by not having a generic website.


What I mean is that one should reach out to different markets and design a website that is custom made to a certain market segment. In doing that, more and most customers would feel at ease while using your site and the chances of them buying a product would increase and along with it, the chances of keeping a customer.



Follow the 10 / 90 Rule

90 percent on your people.

10 percent on your tools.


People are your greatest asset and managing them well will provide you the golden nugget. Prioritizing machinery over your employees will spell trouble because as of now, machines generally can't operate themselves thus needing an operator, a good operator.

Now, if you have invested more on machines rather than people, most likely you don't have a good operator.

Anyone can strike a nail with a hammer but no one does it better than a carpenter.



Solve for Business Questions

Solving various business various questions would sometimes require you to do things that aren't in the manual. These type of questions would force you to look for answers outside your usual sources thus providing you with new information and knowledge. Ask yourself, what can we improve on and find the data that would allow you to answer it, by doing it you are not only widening your sources but also improving your standing.

That are some tips regarding some strategic uses of Web Analytics. Another good tip is to hire a GOOD Analyst, someone who is an expert at what they do because these type of people provide insight which others can't and will never reproduce.



This blog is for DataMin Class under Mr. Mon Duremdes