Greg Munves

Some people confuse the term “Web analytics” with the more general fields of BI and analytics. While BI and analytics can help make sense out of a wide range of transactional data, Web analytics, as its name implies, deals specifically with clicks, links and other types of Web activity.

These interactions between the user and website can be modeled as transactional data. They are both time-series based, and contain information on the interaction between the user and the business. Because of the need to leverage historical data to evaluate advertising effectiveness and social impact, to optimize e-commerce offerings, and to A/B test websites, we have seen a growing interest in cloud-based, big data analytics solutions like 1010data’s for Web analytics.  The explosion of Web data caused by the growth of social media, streaming / rich media and the real time Web is driving the need for technology that can handle massive amounts of Web-driven data and bridge the divide separating more general business analytics and Web analytics.

Solutions that can help e-commerce sites and Web publishers better understand the data is a step towards getting value from, or monetizing the data. I was reminded of this by an article in DIGIDAY: The Big Bet on Social Data.  Brian Morrissey writes:

At a time when content businesses grope for business models, it’s clear where the real money remains: data. The best part about data: no need to publish content or even attract users. The latest evidence: Clearspring Technologies, a company that started as a widget maker back in the heady days of MySpace, closed a big $20 million funding round, led by former Twitter and Zynga investor Institutional Venture Partners, to build out its social data business. Clearspring boasts it sees a billion Internet users — all without operating a single Website… “What social has done is unlock data,” he said. “The biggest outcome of social media is big data.”