The amount of data in our world is exploding, with the volumes expanding from megabytes and terabytes to petabytes. According to Pricewaterhouse-Coopers, there are approximately 75 to 100 million blogs and 10 to 20 million Internet discussion boards and forums in the English language alone. According to a recent Gartner report, enterprise data is expected to grow by 650% in the next five years.
The increasing volume and detail of information captured by enterprises, and the rise of multimedia, social media, and the Internet, are likely to fuel exponential growth in information for the foreseeable future. Almost every person, and many things—imagine traffic sensors or electric meters—are both data producers and consumers.
Analyzing these large and growing data sets, so-called “Big Data,” will become a key basis of competition, underpinning new waves of productivity growth and innovation. McKinsey & Co. estimates that a retailer using big data to its fullest potential could increase its operating margin by more than 60 percent.
Marketing executives are particularly influenced by the emergence of Big Data. It offers a whole new category of information and information-processing capabilities that are changing the kinds of questions marketers can ask and have answered.
Big Data can unlock significant value by making information transparent and usable at much higher frequency. Armed with Big Data, marketers can know how much consumers spent, the markets or regions in which they spent it, when they spent it, what they spent it on, and in which channels. Among the most important questions marketers are asking include: How is the rising use of smartphones affecting brick-and-mortar stores? Do different customer segments make use of multiple channels in different ways? Who are the highest-value customers, and are they loyal or considering moving to a different brand?
By answering strategic questions such as these, Big Data is fundamentally shifting the way CMOs work. Imagine one day being able to gain insight into the real-time attitudes, behaviors, and intentions of consumers by knowing why people buy and where markets are going. Imagine that this insight informs every decision the organization makes, from fraud detection to customer conversion. Every hour of every day, performance problems are solved before they become financial problems, and customers help the organization innovate well in advance of demand. There is no need to imagine because that day is today—and CMOs are responsible for donning the Big Data mantle.
CMOs' new role.
A New Role For CMOs
Today, a fundamental role of the CMO is to capitalize on the complexity of Big Data. In billions of chats, blogs, emails, mobile phone calls, and social networks, consumers are talking about every business and organization. Somewhere in this massive conversation are shouts, whispers, clicks, and purchases that will determine each company’s success or failure.
Yet many organizations are data rich, but insight poor. Marketers today must transform available data into feasible, immediate action plans. The notion of turning data into real-time insight, and insight into instant action, is a common and growing theme.
While Big Data is big, it is also fast—and both of these elements require better collaboration between marketers and CIOs. Today, few people are amenable to batch processing, with jobs submitted on Monday and results provided on Friday. Marketers need answers to questions such as which customers are responding to a new offer on a landing page. Customers want information such as how many minutes they have used up on their cell phone plans. The answers are expected instantaneously. With aging infrastructures, CIOs are feeling the pressure to deliver on the pace of Big Data, and, as a result, are turning toward new technologies and data analysis solutions that deliver information in near real-time.
“For chief marketers, the key is to understand technology better and collaborate with CIOs to know how to obtain operational data in the time frames required,” said Jeff Holden, vice president of client relations for Marlabs, a technology services provider. “Today, most people and things on earth are both data consumers and providers, with expectations for immediate response. Chief technology executives will need to turn from ‘big iron’ data center technologies to new solutions and the cloud to meet user expectations.”
Structured And Unstructured Data
So where can CMOs start? As data and the need to analyze it in real time and make predictions based on insights become a bigger competitive imperative, marketers’ responsibilities are becoming increasingly IT-focused. They need to learn new terms and evolving business intelligence and predictive analytics technologies and practices. As a first step, CMOs can start with a few basic terms.
When talking Big Data, structured and unstructured data are among the most often cited concepts. The lines between structured and unstructured data are blurring, as are the definitions. But essentially, structured data is transactional data—often stored in a relational database or data warehouse. Unstructured data is free form—email, audio, video, chats, Web pages, and so on.
While structured data is projected to grow at a CAGR of 21.8%, it is far outpaced by a 61.7% CAGR predicted for unstructured data in traditional data centers, according to IDC. Data will grow 800 percent during the next five years, with 80 percent of it being unstructured, Gartner says.
Effectively managing and harnessing this vast amount of structured and unstructured information presents both a great challenge and a great opportunity. The growth and diversity of available information from many sources will create new demand for applications that yield business value through content analytics, predictive analytics, and real-time analysis using sophisticated data services. Tackling the ever-growing pool of transactional data and enriching it with insights from interaction data like social, sensor, call detail records, and image data is no easy task, yet it has become businesses’ most important asset.
Also worth noting, Big Data is just one component of “Extreme Data.” Gartner states there are four dimensions to Extreme Data—volume, velocity, variety, and complexity—and these dimensions are critical when it comes to winning the battle for control of enterprise data amid the conflicting requirements of business intelligence and reporting versus data mining and statistical analysis. Big Data is used mostly to describe the size of data, or what’s now being equated to the “volume” dimension of Extreme Data.
Where To Start?
Here are a few considerations and tips to turn Big Data into an organization’s most important asset:
1. Determine the “right” information and coalesce it into one place. The first issue is determining which information is useful—conversions, Facebook “Likes,” customer support experiences, subscription duration, seasonal buying patterns, and so on—and where it resides. For CMOs, information can be housed in call-center systems, ATMs, point-of-sale systems, kiosks, RFID tags, reservation systems, social media networks, business intelligence software, data warehouses, and more—and these silos typically do not connect with one another. All of these have two main things in common. First, they generate massive amounts of rapidly changing data. Second, they rarely connect together in a meaningful way to provide CMOs with immediate insights. CMOs need ways to gather customer intelligence onto a single platform in a simplified, automated way that empowers immediate business decisions.
A solution that thinks ahead.
2. Find a scalable solution capable of spanning information silos. Choose a system that can accept data from any source, including data warehouses and business intelligence tools. Find a Web-based or cloud-based solution that will scale to meet the demands of Big Data because today's data management challenges pale in comparison to those of tomorrow.
Moore's Law supports the idea that computing power and storage capacities have been doubling every 18 to months. That's an increase of about 1,000 times every few years. Despite this increase, data is now growing at a faster rate than storage capacity and computing power. Some projections foresee that, by 2012, only about half of the data produced can be efficiently collated and stored. This means that instead of purchasing more storage and computing power, new strategies are required. Cloud-based architecture approaches that leverage parallel processing across multiple data centers and servers are the practical way forward.
Extreme data is adding a dimension to the already stressed data warehouse environment. The scalability and performance of database management systems are being pushed to the limitAgain, the cloud is the only viable platform thatcan scale out with ease—without an organization having to continually bear the burden of creating and managing its own massive databases, servers, and already overloaded data warehouses.
3. Think real-time. Think visible. CMOs and their staffs need to quickly analyze large volumes of rapidly evolving data in real-time. Most available tools used to analyze very large volumes of data trade off the breadth and depth of the analysis with the time it takes to arrive at meaningful business insights. As a result, organizations have struggled to make timely, intelligent business decisions.
Several solutions are capable of providing powerful, immediate data visualization that allows marketers to immediately infer meaning. Once patterns are made visible, marketers can make quick business decisions that improve overall business performance. Invest in solutions that put data to work quickly.
The ability to manage extreme data will be a core competency of marketers. They need to be able to visualize patterns, gain insights immediately, and innovate based on what they’ve seen and learned, deriving new forms of information—such as mobile interactions and social network feedback—and tying it to structured data, such as bill payment or subscription renewal. Perhaps a user logs into a dating service many times per day and has been a long-term customer. The lifetime value of the customer is high, yet the customer’s subscription is about to expire and the latest bill has not been paid. This information can be used to predict churn for that unique individual. The dating service could reach out to that person at the right time with the right offer to increase user satisfaction and further enhance the lifetime value of the customer.
Information on individuals or groups can be analyzed and modeled in real time to spot trends and patterns. This pattern-seeking and response process, however, also needs to happen in real-time and be automated on a scale that allows the business to adapt rapidly. The gather-visualize-learn-adapt cycle can then be completed in various mediums and across channels, such as social computing analysis or mobile offer campaigns.
4. Track return on investment per channel. Oftentimes, marketers have a difficult time understanding the true value and returns that are derived from their marketing dollars by channel. It is possible to know how each channel, individually and collectively, is affecting the business. Whether a customer comes from paid search or a social media interaction, it is important to attribute revenue to a specific channel or use remarketing to boost conversions through different channels. All of this is possible using today’s solutions. By gauging individual actions as well as applying predictive models—which exploit patterns found in historical and transactional data to identify risks and opportunities--to particular user groups, marketers can have a more substantive positive impact and garner greater results.
With a common platform for marketing information and the ability to visualize patterns and make predictions, CMOs can make the right trade-offs and informed decisions. Will optimizing the home page pay off most? Or should we focus on a promotion on Facebook? Should we be delivering coupons through mobile devices? With only so much time and limited marketing resources, executives must choose wisely. Solutions are available today to simplify and automate insights and enact marketing processes to boost returns.
5. Get used to a new role. Both IT and marketing executives’ roles are changing. IT executives are no longer the sole owners of the technology stack, but instead are now business partners. For CMOs, the need to consolidate, visualize, and act on data housed in various data silos is more important than ever. The real issue is no longer building a bigger, better data warehouse; instead, it is making sense of big data and finding patterns in it that help organizations make better business decisions. Today, this job falls to the CMO in partnership with the CIO.
Turning Big Data Into Big Opportunities
CMOs have assumed a powerful, new role. They have a window into the world of Big Data—and their guidance and insights will form the basis of strategic decision-making during the next decade. They are responsible for grappling with the explosion in unstructured data and making sense of the conversations occurring through dozens of channels, every day. Using a Big Data approach, they can create a picture of real buying patterns and sentiments tied to millions of real consumers. But first they must determine how to take a sensible approach, harness the right solutions, and work together as partners with IT executives to turn Big Data into smart decisions and big returns.
Read related article, “For CMOs, 'Big Data' Is A Very Big Deal.”