Big Data and Web Analytics

Big data is so hot right now.

There is a flurry of discussion about how big data will change web analytics. Analysts are learning what new skills they will need to stay ahead of this trend. From a broad perspective, though, big data is not a new trend in web analytics. The increased ability to leverage big data introduces new options for web analysts, but it shouldn't really change our focus.


Big Data, Have We Met Before?

"Big data" in web analytics simply refers to merging disparate data sets (e.g. online and offline) into a single database for analysis. The magic of big data is in finding ways to connect those data sets. That's what we, as analysts, have helped clients do since the beginning, first by measuring the influence of radio and TV ads on web traffic and now by quantifying social media efforts. One major development is the volume of data that analysts can work with because of new tools and new methodologies. But the questions analysts are trying to answer are the same as they have always been. Who are our customers? How do we best address their needs? What can we do better when we interact with them?

Everything Is Different, But Nothing Has Changed

Because the questions are still the same, the way we approach big data is the same as we should have approached web analytics all along. Even though big data increases the need for good analysts, it doesn't fundamentally change what makes a good analyst. Dealing with bigger data doesn't mean the data is more accurate, per se. It still deserves a fair amount of skepticism and creativity to interpret it. There are the same limits on what we can accurately achieve with models. And analysts still have the same hurdles in selling their recommendations to their stakeholders.

New Risks

Big data also introduces new risks. There is, of course, the PR risk to a company that appears too invasive. But the more sinister risk is that analysts and stakeholders alike will become more trusting of the data because there is more of it. In fact, with the increased volume comes more potential for errors in how we interpret it. If analysts rely too heavily on statistical models and canned reports from tools, they run the risk of overlooking the human factor in the numbers.

Make no mistake. Big data is exciting. It brings new possibilities for web analysts. Understanding how to leverage it can help companies connect with customers like never before. Understanding the risks it brings can prevent embarrassing (and expensive) mistakes.

The next four parts in this series will discuss how web analysts can use these powerful new tools and avoid pitfalls. None of them discuss specific tools or SQL-type languages because those will rapidly change and evolve. Instead they will describe fundamentally how big data can empower a company that uses it wisely.

This is part 1 of a five-part series on big data and web analytics.

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