Digital marketing has always been a lot like fishing. The World Wide Web is a great untamed sea, and teeming beneath its surface is vast amounts of raw information. Marketers cast their lines, trolling the waters in search of pelagic data—the information closest to the surface—through the use of email marketing tools, content management systems, and content optimization platforms. They then have in-house professionals sift through that data, gaining basic insight into customers’ search habits and online interactions. Armed with that insight, marketers are able to make informed creative decisions in order to better tailor online experiences to suit audiences’ needs and increase conversions. This is the way digital marketing has always been done, but times are changing. Enter Big Data.
The rise of big data—massive stockpiles of deep information—is fundamentally transforming the way some entrepreneurs think about information technology and marketing analytics. As more people opt into social media and user generated content becomes more prevalent, the focus is beginning to shift away from the hook-and-line data gathering methods of old. Today, people are willingly offering up personal data about their everyday lives in unprecedented ways. As a result of this shift in attitudes, detailed personal information is more abundant and easier to access than ever. Consider this:
On average, Twitter users generate about 100,000 tweets every minute
Facebook users share roughly 700,000 pieces of content every minute
Some startups, like HStreaming (now Adello Group) and Precog (recently acquired by RichRelevance, have taken notice. Startups like these have begun trawling the web, casting huge nets to capture as much of data as possible in order to help businesses make testable predictions about the attitudes, habits, and behaviors of huge segments of the population. This information can then be used to break groups of individuals down into increasingly more specific target demographics—“buyer persona.” Which means rather than marketing analytics being tethered to data based solely on visitation and social presence, companies can base their marketing decisions on information gathered from the population’s real-time interactions everywhere across the web.
Social engagement on new media outlets such as Facebook, Twitter, and YouTube is just a small piece of the big data puzzle. An overwhelming amount of digital information is being gathered and stored by search giants like Google, Yahoo!, and Microsoft’s Bing. These companies have stockpiled monstrous caches of individual search queries, browser information, and even metadata about user’s hardware. You’d be hard-pressed to find anyone in the tech world who hasn’t been frothing at the mouth to gain access to it. Why? For starters, nearly every demographic is represented in the dataset. Consider this:
There are around 2.5 billion internet users worldwide
IBM estimates that 2.5 quintillion bytes of data are created daily
Google alone receives over 5 billion searches every day. That’s over 3 million bits of marketing gold every
Secondly, big data is big business because of its transformative predictive power. By gathering information and adhering to the laws of probability theory, companies can accurately predict group behavior—a huge win for specialized data analytics firms and the partners they serve.
Entrepreneurs in the information space have been moving toward a data-for-dollars model over the past couple of years. They’ve begun to understand that there are real limits to an individual company’s ability to store, analyze, and interpret huge amounts of data on-site. Those companies are willing to pay top-dollar to startups that can warehouse and interpret massive volumes of information.
This is the new frontier of marketing analytics. Many predict that this could lead to an era of hyper-specialization, wherein marketers outsource the bulk of their analytics to highly specialized data warehouses where number-crunching machines would go to work compiling and analyzing all that information. Data analysts would then pore over it, extracting meaning from the filtered data. Finally, it would be passed on to marketers who would then focus their in-house efforts on implementation and refinement of marketing deliverables based on those “pre-crunched” figures. The numbers don’t lie. Big data is rearranging the entire marketing ecosystem. Get ready.