Views on Page Views

This week, there is a great new post at my favorite tech blog ReadWriteWeb, “The Death of the Pageview” by Tim Trefren, a guest author who is also a founder of Mixpanel, a second generation web analytics company.

Tim puts forth a number of evidence that points to the declining value of the pageview as both an analytics metric as well as a monetization benchmark for start-ups. Web analytics has moved beyond the simple pageview or unique visitor counts, as the mode of interaction on the Web are mostly based on-page rendering of dynamically delivered data that do not require reloading of the page.

To get a complete understanding of users behavior, visits trends and the monetization potential of a website, a plethora of tools are available today, such as:

– Click tracking and replaying tools
– Heat-mapping tools
– Funnel analysis
– Split testing/Multivariate testing
– and more..

Web stats are extremely important for expansion stage software companies, because those companies are at a stage where their websites are the most important marketing (and sales, in some case) channels. Our experience with portfolio companies is that comprehensive website statistics data is an essential component of any marketing or online sales analysis. Many of our sales and marketing support projects start with a comprehensive review of historical website analytics, from where we glean insight for keywords, visitor behaviors and

This might sound rather intimidating for a young software company just trying establish their presence in the market, but the earlier they start with tracking the website, the more data will be collected over time. Furthermore, there are a lot of open source alternative that are free and very customizable.
Besides the tools listed in the article, here are some more links to website analytics tools and resources:

Free Website Analytics Tools at WebDesignLedger.com

Genetify, an open source multivariate testing platform.

Web Analytics 2.0, a great book on next level Web analytics

The next post will be about text mining and how it is being increasingly used as part of customer experience management and product management process.