Nowadays, the clients we get here at Buzz Starter are mostly successful sites that used to do well with their evergreen words or what most people know as the main taxonomy, or main keywords for the other “most people” bucket. A good number of these clients still continue to suffer since the Panda update, roughly 3 years ago and have been having a difficult time implementing changes to their site, mostly because the lack of in-house expertise of implementing the latest SEO best practices. The indecision has cost their business greatly when it comes to monetization of their traffic, especially for sites who’s bread and butter rely on Google Adsense or selling display adspace.
Last time at the BuzzStarter Insider, was elaborating how big data has emerged as a critical piece in today’s businesses. Companies from different segments and verticals are starting to embrace the value of what it has to offer. Organizations who have already implemented massive infrastructure and investment capital are leveraging the value of big data to get ahead of their competition with cost effective results. On the last part of this article, I would like to give you where I believe my perceptions and predictions are on where this going to be a tremendous help.
I remember when I started tinkering the first set of web reports back in 1996. It was a report running on CGI, comes out of the box with Apache that displayed a lot of cool graphs such as Hits (Yes! We used Hits as a measure back then.) coming from referring domains, mostly .com, .net and .edu TLDs. I remember pouring over a number of pie charts displaying where ISP hits are coming from, and they came from all over the place. At that time I found that data so amazing and interesting, sort of magical. It was almost like discovering a unicorn or a full spare tire. Where our system admins saw only the value of the data from a skin deep perspective, such as figuring out where people are coming from, as a webmaster at the time, I just saw a lot, lot more. I recall thinking that, if we were to measure traffic going to the site as Hits, then we were not effectively identifying the traffic. I also started thinking about other applications of the data such as figuring out what people liked or didn’t like on our website, or what type of content our traffic reads on a daily basis and figure out how to monetize that.