By Deloitte
In 2010, Google’s Eric Schmidt said, “I don’t believe society understands what happens when everything is available, knowable and recorded by everyone all the time.” He was referring to the fact that in the digital world, data are everywhere.
We create them constantly, often without our knowledge or permission, and with the bytes we leave behind, we leak information about our actions, whereabouts and characteristics.
This revolution in sense-making ― in deriving value from data ― is having a profound and disruptive effect on everything from supply chains to corporate strategy. In particular, it is generally forcing executives to rethink how they understand, reach and even influence their customers. Simply put, with so much data available, especially on social networks, the ability to know the people you sell to and to monetize that knowledge has never been greater.
That said, most companies are only beginning to scratch the surface of what’s possible with social data. Many are still operating in the pre-social media age, simply trying to make sense of the data they have-rather than the variety of sources that exist. But even those that are best-of-breed have only started to tap into the true potential of this information.
Still, very few companies are able to act on this kind of information. We will explore what it takes to go beyond just an analytics solution.
Customer analytics is hardly news to most executives. Organizations have been gradually embracing it over the last 20 years.
The first of three waves is playing out in the space of big data. In this wave, organizations can tap an incredible amount of information that makes customer targeting more feasible. The key feature of this wave, however, is that the data inside it are not social-they are drawn from closed or proprietary mechanisms instead of what is often stored openly on the Internet. More importantly, because these data aren’t social, they lack a broader context about the relationships and behaviors of the people creating them.
The second wave gets closer to adding that color and came about with the rise of social media. As Andreas Weigend, the former chief scientist at Amazon. com explains: “Users started to actively contribute explicit data such as information about themselves, their friends or about the items they purchased. These data went far beyond the click-and-search data that characterized the first decade of the Web.” Rather, they provided specific new insight into customers by putting their decisions in a social and personal context.
Twitter, Facebook and LinkedIn are familiar platforms in this wave. For companies looking to target ads or customize their products, this information can be incredibly powerful. It can also drive new forms of digital listening. Many organizations, for example, are starting to build social media “command centers” to take in social data and react to them in real time.
In fact, this kind of implicit analysis of social data is only beginning to emerge and constitutes what we see as the third and most powerful wave of data analytics. In this wave, the focus shifts from the voice of the customer to the individual’s behavior. But more importantly, it looks at that behavior in the context of who is around them and how they interact. It gets below the curated, surface-level information we put out about ourselves online, to help understand what our digital trails and network really say about us.
According to a recent article in The Economist, Bharti Airtel, India’s biggest mobile operator, which handles over 3 billion calls a day, has greatly reduced customer defections by deploying social network analysis software … and IBM, the supplier of the system used by Bharti Airtel, says its annual sales of such software, now growing at double-digit rates, will exceed $15 billion by 2015.
Privacy concerns notwithstanding, these trends can be an extraordinary boon to consumers. The last decade saw the Web awash in a rapidly rising tide of information, leaving most people helpless to filter through mountains of unstructured data. Companies offered more products, advertisers pushed more messages and it simply became too difficult to manage. With social data, companies were given a powerful means to help cut through the clutter.
An important point about this third wave, however, is that it is hardly limited to data from social networks. Auren Hoffman, the CEO of Rapleaf, a leading data-mining company says, “the next big data revolution will be around mobile. If you think about mobile devices as sensors, our phones know more about us than our partners do.” In fact, they are one of the most common sensors in existence: there are already more than five billion mobile phones in use worldwide, with another billion on the way in 2012.
One of the people doing this kind of analysis is Professor Alex (Sandy) Pentland of MIT. His work ― which he calls Reality Mining-aims to understand place for snapshot-style and predict human behavior by combining market research, but when real-time sensing of millions of mobile phones with advanced mathematical real-time models.
So far, he can predict things like what iPhone applications you are likely to buy and even describe a city’s cohesion, attitudes and behaviors by studying mobile location trails .At a recent technology conference, he demonstrated software that he described as 95 percent accurate at determining what company you worked for, simply by analyzing your interactions and patterns of movement.
Perhaps the most important conclusion from this and the other examples in this section is that the universe of data we can draw upon to understand our customers is almost limitless. Social data needn’t be from social networks, and social analytics is much bigger than just listening to chatter on Facebook. To lead beyond today, companies will likely have to develop a deep and real-time understanding of their customers through a variety of digital trails.
How can you start to develop these insights within your own organization? A first and overarching step is to realize that “it’s not just about technology,” says Marc Benioff, chairman and CEO of Salesforce.com. Rather, “it’s about a fundamental shift into a new age of leadership with a new type of executives who behave and operate in new ways.”
The next and most difficult step relates to Benioff’s point above: building an engine to run your business on these flows. It isn’t enough to simply collect and analyze data. After all, data are only as valuable as how they are applied. Instead, companies will need to figure out not just how to extract information about their customers, but how to structure their organizations to act on it in real time; how to customize offerings on the fly; how to respond quickly to changes in consumer behavior; how to intelligently manage privacy and risk; how to segment, price and market effectively, as new information comes in.
What will set firms apart, however, is how well they are able to leverage the power of data in the second and third waves. With it, they can understand things like relationships and influence that are deeply important when trying to give consumers a nudge.
However, this doesn’t mean companies should marginalize the first wave or skip over the second in order to get to the third. We think each wave reinforces and is made more powerful by the last.
Companies can achieve better results by striking the right balance among the three. And like all things data, even this will need a tailored fit.
This article was provided by Deloitte Korea.