The importance big data has in modern advertising strategies is unmistakable. It has completely transformed the way business owners manage their enterprises and is actively being used to help companies identify and utilize new business opportunities and focus their advertising campaigns only on those most likely to make a purchase. Yet, being presented with large amounts of data is one thing, but knowing what do with it is a completely different ball-game. The insight big data promises is often meaningless without context and the ability to isolate just the right measures that are most effective for improving business.
Big data refers to the practice of collecting enormous amounts of information from a wide variety of sources, both digital and traditional ones. It includes CRM databases, market research results, transaction data, as well as the ever-growing collection of customer behavior tracked using computers, gaming consoles, TVs, in-store sensors and mobile devices. What’s so unique about big data is that it can be used in a number of different ways in almost every part of the business ranging from improving products and services to working more efficiently and providing better customer experience.
On the other hand, large sets of consumer data require proportionally large storage capacities, complex systems for data management capable of going through all that data and organizing it into manageable chunks and an experienced data-management professional to translate that data into beneficial insight. One of the most effective ways of analyzing such enormous amounts of data by using artificial intelligence, but entrepreneurs and small business owners simply don’t have the required budgets to properly utilize and implement a data-sifting AI.
Up until recently, big data strategies were centered around exploration and gathering as much information as possible. For the majority of companies today, however, the focus has shifted from analyzing large amounts of data and is slowly but surely mowing towards taking those large amounts and reducing them to just the right data. Professional data intelligence companies such as Isentia take big data, separate what’s important for businesses from the rest of the clutter and produce intelligent data which can later be used to determine the exact measures needed to actually make a difference.
Intelligent data allows marketers to focus their advertising and data strategies on identifying the lowest number of key performance indicators required to improve business. Some metrics are central to your brand’s success, while others are only actually helpful when setting within a particular touchpoint. For example, bounce rates might be an important figure for managers and testers, but may completely be unrelated to the long-term growth of sales.
Identifying the correlation between specific data points and their impact on the brand and overall sales data is what allows marketers to know exactly which metric should be used as an adequate indicator of growth. Making the move from big data to intelligent data means that marketers no longer have to invest large parts of their budgets into powerful data-processing platforms. Instead, they can focus their efforts on finding just the right talent armed with a firm understanding of the appropriateness and quality of any given data and capable of supporting the business analytically.
The future of analytics
Although mining and analyzing data is nothing new in the world of advertising, the applications, content, and platforms associated with that data are. They are constantly changing and evolving, which means that data professionals and statisticians need to be well-versed in the current metrics such as location-tracking data, social media resonance, online performance, video-viewing statistics and much more, across a multitude of channels and devices, all in order to determine which one has the largest impact on both online and offline sales.
Analytics talent capable of accessing and measuring the impact of different variables is still rather scarce. Marketers are still learning, testing and developing their abilities to accurately analyze and interpret data and translate it into business- and department- specific insights. Only with an adequate analytics expertise and thought vigorous learning and testing can marketers venture into the domain of predictive analytics and leverage various metrics to anticipate which segments of the target audience and which customer actions will be the one resulting in a desirable outcome.
Predictive analytics is already used to assess how consumers interact across different key points and to quantify the relationship each of those interactions or even combination or interactions have on customer retention. This allows marketers to further prioritize their activities and, in turn, maximize sales and customer satisfaction rates, a feat that would normally be unthinkable if it weren’t for big data and intelligent data. Although we have only scratched the surface of business-oriented data analysis, marketers are learning and constantly testing the ways in which they could harness the astonishing power that is big and intelligent data in an effective, and more importantly, lucrative manner.
Guest article written by: Dan Radak is a marketing professional with eleven years of experience. He is currently working with a number of companies in the field of digital marketing, closely collaborating with a couple of e-commerce companies. He is also a coauthor on several technology websites and regular contributor to Technivorz.