How should Web Analysts spend the average work day?

Web AnalysticsLooMag Book Presentation October 2007

A Must Have: Web Analytics: An Hour a Day

If you visit a website, you leave behind a significant amount of data (mostly anonymous), whether you buy something or not. The website knows every “aisle” you walked down, everything you touched and everything you put in your cart and then discarded.

If you buy, the site manager has data about where you came to the website from, which promotion you are responding to, how many times you have purchased before and so on. If you simply visited and left the website, it still knows everything you did and in the exact order you did it in.

Add to this the fact that now there is a massive proliferation of tools that will instantly create reports presenting data in every conceivable slice, graph, table, pivot or dump that you can imagine the challenge.

Yet all this fantastic clickstream data will help you understand What happened. It is important to realize that all that data can only provide a vague hint as to Why something happened, both because clicks only represent action and are not really good at sharing intent.

This is the reason qualitative data is crucially important.

It is the difference between 99% of the website analysis that happens that yields very little insights and the 1% that provides a window into the mind of a customer.

Combining the What (quantitative) with the Why (qualitative) will provide a company with a long term strategic competitive advantage.

While there are many options for qualitative analysis, perhaps the most important qualitative data point is how Customers/Visitors interact with your “web presence”. It can lead to actionable insights faster while having a richer impact on your decision making.

Your goal should be to get beyond the flavor of the month “buzzy metrics” and strive to get a hard core understanding of customer satisfaction and the hindrances to successful task completion on our websites.

There are many different methodologies to collect Customer qualitative data, including:

* Lab Usability Testing (inviting participants to complete tasks, guided or unguided)
* Follow Me Homes / Site Visits (observing in a customer’s “native” environment)
* Experimentation/Testing (the latest new and cool thing to do, a/b or multivariate)
* Surveying (the grand daddy of them all)

If you are new to this world the last one is a great way to step into this new world and unlike what you might have heard it is both easy to implement, can be a continuous methodology, highly quantitative and is most often chock full of insights that will lend themselves to be very action oriented.

Every successful web analytics strategy strives for a understanding of not just the What but also the Why. Good Luck!

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