Correlation is not causation. This is one of the key ideas to bear in mind when thinking about big data and what it means to the industry today. The spread of social media, e-commerce, digital marketing, and the plethora of data captured off many industrial practices means that big data is getting really big. A huge amount of data about anything and everything is being captured. But how is it being used? We know that companies that can seize the opportunities presented by proper analysis of big data have the ability to gain the competitive advantage. The challenge, however, is to use all that data and translate it into meaningful and actionable outcomes.
The ability to show correlations with big data analytics is practically a given, but the track record of showing causation has been less than spectacular. Incorrect selection of datasets, pre-programmed biases, and unaccounted values all plague the ability to draw real insights from the use of big data; companies large and small are looking into better ways of thinking and working these large bits of information into a meaningful whole.
Questions involve not only in the capture of meaningful data but into how to do it in the first place. Is a Hadoop Cluster really what you need? Should you build a data science team? And if so, where do you find them? And when you do find them, what data should they be focused on? These are just some of the questions that speakers will be addressing at the Big Data and Analytics Innovation Summit in Shanghai.
Despite the challenges, when big data is used effectively it can create some wonderful insights for your company. Like analyzing the components of truly compelling storytelling, improving customer service, gleaning insights on customer interaction or identifying previously unknown and untapped market segments through the analysis of big data. These and other topics of interest to digital marketers will be on the table for the Digital Marketing & Strategy Innovation Summit in Shangai.
The challenges that face analysts and marketers can be remarkably similar, especially within the realm of real-time analytics. With social media, the ability to capture and analyze unstructured data is vitally important, but by its very nature, unstructured data is a very time-consuming process. Can it be done faster, and if so, how? Is it simply a matter of having faster processors, or of having better processes?
While digital marketing will no doubt benefit from data analytics, is it really realistic for marketing agencies to set up their own data analytics division or could this be outsourced? Buying analytical data can be cost-prohibitive, but will innovations like the decision engine or online analytics software allow start-ups and SMEs to tap into what good data analytics can do for them?
When it comes to outsourced analytics companies are already looking into the idea of a Consumer Data Mall - a coalition of data-driven marketers looking to find meaning within the data that seems to overwhelm others who are ill-equipped to find the signal within the noise. If such enterprises are of interest to you, or if you’re interested in digital marketing and the big data evolution, then I invite you to sign up for those summits today. There will be plenty of cross-networking opportunities for those in big data and digital marketing at the event and a wonderful chance to meet and share ideas.