Big data - challenge or opportunity

Editor's Notes

• #5: We work with marketing to understand their needs—translate that into technology
• #9: How much information is there in the world? As of 2012, about 2.5 exabytes of data are created each day. 1 exabyte is a billion gigabytes or a million terabytes.University of Southern California researchers calculated that the world has access to enough data-storage capacity to hold 295 exabytes (295 followed by 20 zeros) of information.There are reports aplenty about technology driving a data explosion. University of Southern California researchers actually sat down and calculated that humans can store, communicate and compute about 295 exabytes of information, or about 404 billion CDs.
• #10: How much information is there in the world? As of 2012, about 2.5 exabytes of data are created each day. 1 exabyte is a billion gigabytes or a million terabytes.University of Southern California researchers calculated that the world has access to enough data-storage capacity to hold 295 exabytes (295 followed by 20 zeros) of information.There are reports aplenty about technology driving a data explosion. University of Southern California researchers actually sat down and calculated that humans can store, communicate and compute about 295 exabytes of information, or about 404 billion CDs.
• #12: The growth of social networks for business. Social networking account for 22% of all time spent online. Real business is taking place today in public and private social networks. It has moved far beyond using LinkedIn for recruiting, or Facebook for consumer marketing outreach. The benefits accrue quickly from being able to communicate and collaborate easily with extended networks of employees, partners, customers, across internal and external social networks.The ascendency of mobile computing. By the end of 2011, more smartphones shipped than PCs.. And Apple sold more iOS devices in 2011 than they sold Macs in 28 years. “Bring your own device” (BYOD) to work is an undeniable trend in the workplace, bringing freedom and convenience for users, but headaches for IT. Users want to interact anytime, anywhere, with localized, contextual content. And they aren’t afraid to sidestep IT if they don’t get the access they want. IT can try to ban access, but more often than not, needs to rethink their approach to mobile and secure those mobile devices to minimize risks from loss, theft or misuse.The continued rise of Cloud computing. With Forrester alone estimating enterprise cloud computing to grow to over $240 billion by 2020. It’s hard to find ANY current IT project today not considering cloud-based deployments. The conversation is no longer one of outright rejection due to security and quality-of-service concerns. Instead, the discussion is about the right mix of capabilities for the business. What should be delivered by cloud vs. on premises? How do I ensure new services are integrated with the solutions I already have in place? What’s the right policy and governance model I should be looking for from my cloud services providers? What level of customization do I really need, and how much standardization can I get away with? Despite cloud’s increasing sophistication and security in applications, information stores, transaction processing, or even analytics, critical questions still remain. The availability of information, which drives social, mobile and cloud technologies, is the connective tissue in this "nexus of forces."Gartner"In the nexus of forces, information is the context for delivering enhanced social and mobile experiences," Chris Howard, managing vice president at Gartner, explained in the report. "Mobile devices are a platform for effective social networking and new ways of work. Social links people to their work and each other in new and unexpected ways. Cloud enables delivery of information and functionality to users and systems. These forces of the Nexus are intertwined to create a user-driven ecosystem of modern computing."
• #25: Volume. As of 2012, about 2.5 exabytes of data are created each day, and that number is doubling every 40 months or so. More data cross the internet every second than were stored in the entire internet just 20 years ago. This gives companies an opportunity to work with many petabyes of data in a single data set—and not just from the internet. For instance, it is estimated that Walmart collects more than 2.5 petabytes of data every hour from its customer transactions. A petabyte is one quadrillion bytes, or the equivalent of about 20 million filing cabinets’ worth of text. An exabyte is 1,000 times that amount, or one billion gigabytes.
• #27: For many applications, the speed of data creation is even more important than the volume. Real-time or nearly real-time information makes it possible for a company to be much more agile than its competitors. For instance, our colleague Alex “Sandy” Pentland and his group at the MIT Media Lab used location data from mobile phones to infer how many people were in Macy’s parking lots on Black Friday—the start of the Christmas shopping season in the United States. This made it possible to estimate the retailer’s sales on that critical day even before Macy’s itself had recorded those sales. Rapid insights like that can provide an obvious competitive advantage to Wall Street analysts and Main Street managers.
• #28: As more and more business activity is digitized, new sources of information and ever-cheaper equipment combine to bring us into a new era: one in which large amounts of digital information exist on virtually any topic of interest to a business. Mobile phones, online shopping, social networks, electronic communication, GPS, and instrumented machinery all produce torrents of data as a by-product of their ordinary operations. Each of us is now a walking data generator. The data available are often unstructured—not organized in a database—and unwieldy, but there’s a huge amount of signal in the noise, simply waiting to be released. Analytics brought rigorous techniques to decision making; big data is at once simpler and more powerful. As Google’s director of research, Peter Norvig, puts it: “We don’t have better algorithms. We just have more data.”
• #32: Customers and Prospects
• #41: 1. Use All Forms Of Customer EngagementBy customers, we mean prospects and your buying customers. Customer engagements, or interactions, are critical to the marketer from a segmentation and buying-behavior perspective. But accessing, using, and acting on that data can be daunting in today’s marketing automation systems.To tap into all forms of customer engagement--online and offline, across any marketing channel--a purpose-built marketing data mart, integrated with your marketing and campaign platform, is required to bring together all of your customer interactions and purchasing history to make the data actionable.2. Make Customer Intelligence StrategicMost marketers want more customer intelligence, but they’re not sure how to get started with the avalanche of customer data that exists today. Marketing automation and campaign management provides various ways to measure campaign performance through reports and dashboards. But what about customer intelligence that really looks into buying behavior?For example, what if you could perform a buy-cycle analysis, identifying the behaviors of prospects at the buying stage with the kinds of online and offline channels that most correlate to the receiving the types of information they need to move onto the next stage?Customer-intelligence capabilities provide a holistic view of prospects and customers, including: Profiling results by campaign and customer attributes Identifying opportunities based on the level of risk and reward Using new forms of interactive reporting and data discovery, based on campaign performance and interaction historyUsing a marketing data mart with customer-intelligence tools specific to your customer-interaction history turns your marketing-automation platform into a driver of revenue performance.3. Transform Big DataEveryone works to clean their data, but it’s not just about deduplication or merge and purge. Beyond your marketing-automation and campaign-management platforms, more needs to be done to transform data to make it truly usable and actionable, including: Using data libraries to clean and validate data Decoding raw incoming data to improve its usability Using derived attributes based on complex relationships within the data that enable you to more rapidly discover buying behavior to use directly in campaigns driven by your platform Creating a quarantine around incomplete data until it is ready for use
• #42: To understand whom we should target, let’s take a step back and try to understand the mechanics of Twitter. A user – let’s call him Joe – follows a set of people, and has a set of followers. When Joe sends an update out, that update is seen by all of his followers. Joe can also retweet other users’ updates. A retweet is a repost of an update, much like you might forward an email. If Joe sees a tweet from Sue, and retweets it, all of Joe’s followers see Sue’s tweet, even if they don’t follow Sue. Through retweets, messages can get passed much further than just the followers of the person who sent the original tweet. Knowing that, we can try to engage users whose updates tend to generate lots of retweets. Since Twitter tracks retweet counts for all tweets, we can find the users we’re looking for by analyzing Twitter data. Marketing automation vendors are adding a lot of functionality to help marketers address this data explosion. This includes big data analytics, attribution modeling, integrated social analytics, and spend management. Helpful automation technology will condense the data into actionable "views" so that you can use it to make decisions about future messaging. If the data analytics can be done at the customer level (which is unfortunately not universal yet), then marketers can integrate it directly with the CRM or marketing database in order to optimize offer placement in real time. That is where the real power of automation comes in - we want to use all the data available to make meaningful connections with customers when they are in market to receive the message. Oh, and to make that connection on the proper device or channel, too!However, this data management challenge is not just a technology challenge. Organizations need people with the skills to translate that jumble of information into meaningful insight and real business value. We've heard a lot about the "data scientist" role, and it's becoming more and more real every day for more and more marketers.
• #48: Content Management (CMS): Implementing a content management system to support personalized interactions on the company's Web site.Customer Relationship Management (CRM) : Upgrading the existing CRM system to support personalized interactions involving members of the sales team.Marketing Automation (MA) : Upgrading the marketing automation system (Eloqua) to support personalized interactions via email and other digital channels.Integration and Mapping : Integrating the three systems -- customer relationship management,marketing automation, and content management -- to create centralized buyer profiles that could then be mapped to a defined buying process.Measurement and Reporting : Implementing the dashboards and measurement tools necessary to support ongoing performance measurement and management.