I had asked a question in my previous blog1 as to whom, and how much, is web analytics really helping. In further thinking about this, I started researching more on web analytics and its usefulness to both companies and consumers. Doing this, I have been introduced to several new concepts in the analytics world and got side tracked into some of the major concerns on consumer privacy driven by this methodology. So, here I am, writing, from my limited research knowledge on web analytics, about these findings and some of the privacy concerns posed by web analytics.
While there are search engine websites competing, against the giant, Google, to improve their market presence and analytics tools for customers, there is another business that has sprung up to help these customers maintain privacy of their visitors from these analytics websites. Piwik and Nabler are few that offer “extra protection” in this regard to their customers. When getting into more details on how this is done, I was surprised to see the simple techniques utilized in protecting client’s data just by training employees to setup difficult to crack passwords on their systems. Why have some, or should I say almost all websites these days, collect private, confidential data off its customers and then develop other businesses around it to protect that data? One of the concepts I learned during this research was “predictive analytics” and how it can be implemented to predict future events based on historical data. This historical data is a collection of transactional data performed by a certain customer or a segment of customers that is used to develop a pattern and then marketing strategies based on it.
As for all the data collection analytics methods employed, predictive analytics has posed some privacy concerns too. Though the example5 I have is not exactly related to how this analysis technique is being used in the web world, but it sure can be considered a potential privacy deterrent when used extensively by web analytics tools.
Web analytics is surely helping shape our web experience to be better than ever. It sometimes is saving people money by suggesting, recommending products of their interest, again, based on individual browsing history and categorization into a particular segment. But, do the consumers want to get this extra gain at the expense of losing their privacy, that still remains a question to be answered..
4. Web Analytics 2.0 by Avinash Kaushik