BIG DATA BEYOND AND. How companies can find insight in Big Data by TYLER DOUGLAS. visioncritical.com

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1 BIG DATA AND BEYOND How companies can find insight in Big Data by TYLER DOUGLAS

2 CONTENTS INTRODUCTION THE BIG DATA CRISIS THE RISE OF BIG DATA: HOW COLLECTING DATA BECAME INTEGRAL TO BUSINESS THE ADVANTAGES OF BIG DATA BIG DATA S LIMITATIONS BIG DATA AND CONCERNS OVER PRIVACY GETTING TO THE WHY ILLUSTRATIONS BY JACKKRIT ANANTAKUL HUMANIZING DATA CONCLUDING THOUGHTS END NOTES ABOUT THE AUTHOR 2 of 17

3 INTRODUCTION We live in a world awash in data. Every credit card swiped, loyalty card presented, TV show watched and movie downloaded, every Facebook post, Tweet, Pinterest pin, Candy Crush game, Etsy transaction, and Fitbit reading it s all encoded in trillions and trillions of ones and zeroes ready to be mined, organized, aggregated, prioritized and translated into meaningful information. We live in an era in which computing advances have ignited and propelled an explosion in terabytes, petabytes and zettabytes (1 ZB = 1 trillion gigabytes) and more. For businesses, big data can mean big money if professionals can gain insights from the vast and expanding sources of information out there. But big data has become a serious problem for many companies: the amount of data they re collecting is overwhelming, and they can t decide what data is useful. Big data can give companies answers to some of their questions especially when it comes to marketing to their customers. Where are they? What are they looking at? What are they buying, and what are they passing up? But big data can t tell companies why customers make the choices they do. In this e-book we ll discuss the tremendous rise of big data, its great promise and real limitations, and why recognition of both is important for companies to reach and understand customers. We ll provide powerful examples of top-tier companies, including Netflix and LinkedIn, that have figured out how to get what they need out of big data. Today s successful companies have learned that big data doesn t provide all the answers. They recognize that big data is simply one tool among many that can help inform important business decisions. 3 of 17

4 THE BIG DATA CRISIS The amount of data companies collect keeps growing. They urgently need a strategy to make sense of it all 1 PHOTOS STORED ON FACEBOOK AMOUNT SPENT ON BIG DATA (estimated) 40 billion (2010) 250 billion (2013) $31 billion (2013) $114 billion (2018) AMOUNT OF INFORMATION STORED DIGITALLY only 0.5% of big data is being analyzed (According to estimates by IDC) AMOUNT OF DATA PRODUCED IN 25% (2000) 98% (2015) 21 billion Number of Internet-connected products expected by days in 2015 = All of history of 17

5 THE RISE OF BIG DATA: HOW COLLECTING DATA BECAME INTEGRAL TO BUSINESS Big data refers to the massive amount of information amassed digitally every time we watch something on cable TV, buy airline or concert tickets, purchase something in a department store, do just about anything online and so on. Big data also refers loosely to the analytical tools employed to make sense of all this information. Big data is ubiquitous, it s growing and it s getting tougher and tougher for companies to understand. As early as 1990, Peter J. Denning, then the director of the Research Institute for Advanced Computer Science at NASA s Ames Research Center, was worrying about how his fellow scientists could ever extract meaning from the ever-growing sea of data they collect: The imperative to save all the bits, he wrote, forces us into an impossible situation: the rate and volume of information flow overwhelm our networks, storage devices and retrieval systems, as well as the human capacity for comprehension. 2 By 2010, the term big data had entered the common lexicon. Data, data everywhere, 3 a 2010 article in the Economist, cited Walmart s one million transactions every hour, Facebook s 40 billion photos (by 2013 that number had jumped to 250 billion, and was increasing by 350 million each day 4 ), and 65% of senior executives embrace big data to stay competitive one-week analyses of the human genome s three billion base pairs as illustrative of the world s unimaginably vast amount of digital information. The effect is being felt everywhere, from business to science, from government to the arts, the Economist continued. Scientists and computer engineers have coined a new term for the phenomenon: big data. Big data is not just about digitizing existing information. It s about rendering more of our lives into data in real-time where we are, what we like, with whom we interact, what and when we buy and more. Social media platforms such as Twitter, LinkedIn, Facebook, Snapchat and Instagram are examples of the real-time datafication of customers lives. More and more companies are harnessing the power of big data to help guide strategic business decisions and gain insights into customer behavior. Here are just a few examples: 1 The Australian Open The Open relies heavily on big data during its tournament, in response to the demands of tennis fans around the world. Australian Open marketers analyze information such as social media conversations and player popularity to predict viewing demands on the tournament s website which helps organizers determine how much computing power they need at any given time. 5 2 Ski resorts Some resorts rely on big data to increase customer engagement through gamification the application of game-design thinking to activities like ski- 5 of 17

6 Collecting, correlating and analyzing data from customer interactions across channels is the key to transforming the customer experience from nightmare to nirvana ing that you might not think of as games. At some ski resorts, customers wear Radio Frequency Identification (RFID) systems, so skiers can be tracked. The resort compiles stats such as the number of runs skiers make, the number of feet they ski, and how often they get to the slopes. Customers can access this data on the resort s website, and compete with their friends to earn better rankings and rewards. All this encourages customers to spend more time on the slopes. 6 3 PASSUR Aerospace PASSUR, a provider of decision-support technologies for the aviation industry, uses big data to improve upon estimated times of arrival (ETAs) normally provided by pilots. PASSUR combines publicly available weather data, flight schedules and proprietary data the company itself collects, including feeds from passive radar stations installed near airports that track every nearby plane. The huge stream of digital data, archived for more than a decade, enables PASSUR to make sophisticated analyses of aircraft arrival times. Its service, called RightETA, has helped at least one major U.S. airline virtually eliminate gaps between estimated and actual arrival times, according to the Harvard Business Review article, Big Data: The Management Revolution. 7 4 Macy s The department store, working with IBM, has gained a more comprehensive view of its customers by integrating online forms, point-of-sale data, and social media information. The exercise has enabled Macy s to offer its customers a more personal shopping experience, and offer tailored pricing and promotions. 8 Most senior executives know that big data is here to stay, and that organizations which invest in gathering it and understanding it are investing in their future. One recent poll found that 65 percent of senior executives say they risk becoming irrelevant if they don t embrace big data. 9 THE ADVANTAGES OF BIG DATA Big data is huge in volume. It s high in velocity that is, created in real or near-real time. And, it s diverse in variety. For marketers, researchers and executives, these attributes of big data mean they have access to much more information about their customers than ever before. They know where they are, what they re watching, what they re buying and when, what they re saying to their friends, what views they re spreading about a company and its products, and more and all of this the moment it occurs. Big data, if managed effectively, can 6 of 17

7 cient and deeply satisfying interactions that benefit both customers and business. While huge amounts of information are collected on people s daily activities, big data increasingly is about the passive monitoring of hand-held and wearable devices, home appliances, vehicles, and other things connected to the Internet that provide companies with insight into behaviors and everyday choices. Big data will continue to grow in significance as this Internet of Things matures. The number of connected products is expected to hit 21 billion by 2018, so companies that don t prepare to manage this new data resource will be at a competitive disadvantage. It s vital that companies embrace big data, recognize its growing significance, and learn how to maximize its potential as a major tool to drive strategic decisions. Those that fail to do so will be left behind. be crucial for omni-channel marketing by strengthening a seamless meshing of customer experiences across marketing platforms, including TV, radio, the Internet, ipads and tablets, smartphones and physical stores. Collecting, correlating and analyzing data from customer interactions across channels is the key to transforming the customer experience from nightmare to nirvana, IT analyst and consultant Kurt Marko of the technology blog MarkoInsights wrote in Forbes recently. 10 The nexus of big data and machine learning in all its forms are the underpinnings of well informed, highly effi- BIG DATA S LIMITATIONS For many businesses, big data emerged in recent years with great expectations that it could answer all questions about customer desires and behaviors. But like most new trends in technology, Gartner s Hype Cycle applied. The Hype Cycle, used by companies to become educated about the promise of an emerging technology in their industry, 7 of 17

8 fail to pay off? One reason is that companies already have access to a lot of customer information, but they don t really know how to leverage it to make good strategic decisions. Without this foundation, adding big data into the mix often adds little value. Companies need to learn how to manage information, analyze it in ways that advance their understanding of its customers, and then act intelligently in response to new insights. Companies don t magically develop those competencies just because they ve invested in high-end analytics tools, information science academics Jeanne W. Ross and Anne Quaadgras from MIT and Cynthia M. Beath from the University of Texas at Austin wrote in the Harvard Business Review. 11 They first need to learn how to use the data already embedded in their core operating systems, much the way people must master arithmetic before they tackle algebra. According to Ross and Quaadgras, one reason that companies are unable to benefit fully from their investments in big data is that management practices haven t caught up with their technology platforms. For example, companies that have installed digital platforms, such as enterprise resource planoffers a graphic representation of how new technologies typically mature over time. The initial enthusiasm for big data was marked by inflated expectations followed by a trough of disillusionment when early experiments with big data failed to deliver. For many new technologies, users slowly become more enlightened about what it can offer, second and third generation products are developed that make the technology more useful, and finally productivity takes off as the technology matures and people and organizations recognize its potential. It s expected that big data will follow this trajectory. Today, however, many people believe big data alone can t deliver what they want: actionable information with which they can make effective decisions that benefit their customers and their bottom line. Everyone assumes you need big data, says Ray Poynter, a leading expert on market research. The question is, what do you add to make it useful? Do you add to it being engaged with your customers and having two-way conversations with them? Do you engage in new business models? There are lots of points of view about how you complement big data. Today, many companies are trying to figure out what value big data can give them, and how to gather, mine and make sense of it. Within a company, big data can present several challenges. Data collected by an organization is often siloed finance holds tight to point-of-sale data, marketing controls social media data, while customer service has complaint data which prevents companies from building a comprehensive picture of their customers. Companies have access to a lot of customer information, but they don t really know how to leverage it to make good strategic decisions. Without this foundation, adding big data into the mix often adds little value Why do a lot of investments in big data 8 of 17

9 Despite these limitations, big data remains an increasingly powerful tool for business intelligence. But as more companies seek out big data, and especially as our personal digital footprints expand and social media platforms strive to monetize the personal data they collect, organize and archive, many people view the prevalence of big data as an intrusion on their privacy. Too often, customer data is collected passively, withning (ERP) systems and customer relationship management (CRM) systems haven t yet taken full advantage of the information they make available. A cultural change is needed within companies so that all decision makers have performance data at their fingertips every day, Ross and Quaadgras write. As an example of a company that uses data effectively, Ross, Quaadgras and Beath cite 7-11 Japan, which provided its employees with daily sales reports and supplemental information such as weather forecasts, what sold on the last day the weather was similar, what sold the previous day, what sold on the last the same date a year prior, and what was selling in other stores. Importantly, clerks were connected to suppliers to encourage the development of items that would suit local customers tastes. The 7-11 Japan story was not about big data or investments in data, but about a lot of little data. It s about betting your business success on the ability of good people to use good data to make good decisions, the authors wrote. Empowering employees in this way, and arming them with the data they need, helps them make better operating decisions on a daily basis. It can also lead to a constant stream of innovation. Big data, in other words, isn t the answer to all questions and it s no replacement for the on-the-ground decision-making of real people interacting with real customers. Once seen widely as a holy grail for companies seeking real-time insight on their customers, social media analytics has failed to deliver on those lofty expectations. Consider this: 85 percent of social media updates 85% of social media updates come from so-called enthusiasts 29% of a typical company s audience are enthusiasts come from so-called enthusiasts, but only 29 percent of a typical company s audience is enthusiasts. (Check out our recent report to find out what else social media analytics can t tell you about your customers) The vast majority of social media users are in fact relatively quiet. Companies can t hear them, although they re listening to you. This means that social media analytics can mislead companies about what matters to customers as a whole, when in fact what they re seeing is only a very thin slice of their audience. People who spend a lot of time online are typically younger, better educated and more affluent than the overall population again, offering many companies a limited view of existing and potential customers. BIG DATA AND CONCERNS OVER PRIVACY 9 of 17

10 Big data can reveal much about what s going on, when it happens and where it happens. But we haven t really arrived at the day when big data can reliably tell us why customers behave in a certain way out permission. Opt-out options are rarely explicit and often missed. For instance, cross-device tracking, a powerful tool for marketers, enables companies to track their customers digital lives, from general web searches to social media posts regardless of the device or platform used. Such tracking especially troubles people who are alarmed by the idea of their every digital move being tracked. In April 2015, the U.S. Federal Trade Commission announced that it plans to examine privacy issues related to advertising and marketing companies that track consumers across devices connected to the Internet. 12 One question the FTC is exploring is how companies can make their tracking more transparent and give customers more control over it. The desire for privacy is already fueling the development of new apps online. Wickr, Whisper, Cyberdust, Snapchat and Rewind are examples of apps built on making content more private and ephemeral. Research has predicted this trend: a study by the University of Colorado at Boulder, published in late 2013, found that average smartphone users are willing to pay up to $5 extra for a typical app that won t monitor their locations, contact lists and other personal information. 13 Companies that rely on big data to track their customers can go too far. Customers can begin to feel uncomfortable about the degree to which their digital lives are tracked and probed. The result? Customers, unhappy at the personal invasion, abandon brands. One example is Facebook s controversial Beacon feature, first introduced in late The feature, which at first was implemented by default, tracked users activities online, outside Facebook, and reported back to Facebook on members activities on third-party sites like Travelocity.com, TheKnot.com and Overstock.com. A major part of Facebook s Ads platform, Beacon tracked the activity of Facebook users on dozens of participating websites. That activity was then broadcast to the user s Facebook friends unless the user explicitly chose not to do so. One consequence: holiday presents purchased by users were being broadcast to friends and family. It turned out, Facebook quickly learned, people don t want to automatically let the world know what they re buying online. More than 50,000 Facebook users signed a petition protesting Beacon. By late November of 2007 Facebook backed off, company founder Mark Zuckerberg issued an online mea culpa, and the social media company made Beacon an opt-in program that sought explicit approval from users every time they purchased something at a third party site before activating the Beacon feature. The program nevertheless sparked several lawsuits, and by 2009 Facebook discontinued Beacon altogether. In another big data marketing innovation gone awry, statisticians at Target noticed 10 of 17

11 that women were buying lots of unscented lotion around the beginning of their second trimester. One analyst noticed that during the first 20 weeks of pregnancy, pregnant women bought vitamins like calcium, magnesium and zinc. Target began sending coupons for baby items to customers based on their pregnancy scores. 14 An angry man outside Minneapolis, Minn. complained to a Target manager because his teenage daughter had received coupons for baby items in the mail. Target knew about the pregnancy before the girl s father did. In the end, the father, embarrassed by the episode, acknowledged to a manager that he didn t know about his daughter s pregnancy and apologized. Very quickly, Target was forced to rethink how it uses the data it collects about its customers. Customers are happy to share their data, but only if companies don t exploit it in ways that violates their privacy. GETTING TO THE WHY Big data can reveal much about what s going on, when it happens and where it happens. But we haven t really arrived at the day when big data can reliably tell us why customers behave in a certain way. As computing advances and analytical tools progress, we may get to that point. Companies had inflated expectations of what big data can offer. They now see big data can be an important tool alongside other tools to achieve more effective customer engagement But for the foreseeable future, big data is only one tool in the marketer s toolbox. Customer intelligence that involves more direct human-to-human interactions with consumers remains vital. Big data will only take us so far, and at some point a human perspective needs to join the effort. For insight departments to derive value from big data, they must get better at leveraging social science, data analytics and consumer insight. Understanding the nuances of customer behavior the motivations, or the why behind behaviors gives us true insight. And that cannot come from a centralized and isolated big data department. Computer technology, the Internet, cable entertainment and other technological advances have led to empowered customers who have more access to information, more choices, more demands on their time and, in many cases, less allegiance to individual brands and companies. At the same time, customers spend more of their lives and their shopping hours online. When it comes to buying, customers have unprecedented access to information about companies and the products they sell. Big data surely has a role to play in gaining insight into the behavior of these empowered 11 of 17

12 achieve more effective customer engagement and ultimately higher levels of innovation and productivity. Let s look at a few examples: 1 NetflixThis company is said to account for an astonishing one-third of peaktime internet traffic in the United States. 16 In early 2015, it announced it had 62 million subscribers around the globe. Netflix has expanded its intelligence over customer tastes in recent years, adding numerous data points to better understand customer preferences. All these data points feed into big data analytics at Netflix to progress toward the comcustomers. But as we ve discussed, big data doesn t have all the answers. Companies need to respond quickly to identify changes in customer behavior and take action to address their concerns. Big data can offer some answers, but continual human-to-human connections are required to fully understand the rapidly evolving marketplace. HUMANIZING DATA In an important report on big data published in April 2015, Forrester Research declared, Businesses are drowning in data but starving for insights. Worse, they have no systematic way to consistently turn data into action. This can t continue. Demanding customers and competitive pressures require firms to treat insights not just data as a business asset. 15 The report cites Ford Motor, General Electric, USAA, Netflix and LinkedIn among those companies that are effectively combining people, processes and technology to close the gap between insights and action. Stories of how these and other companies are moving toward real customer insight that is, moving from big data to meaningful, actionable information are becoming more common. They now see big data as an important tool alongside other tools to 12 of 17

13 pany s holy grail: predicting what customers will want to watch next. But the company has also moved from passively collecting data to directly engaging customers to better understand what they want. Netflix asks some customers to apply characteristic-identifying tags to movies and TV shows. The company then suggests that those customers watch other films that were similarly tagged. This direct engagement with customers through tagging has led to actionable insight: Netflix has identified nearly 80,000 new microgenres of films, which helps the company to better serve its customers. 2 LinkedIn If you re a LinkedIn user, you know all about the Who s Viewed Your Profile feature. The highly successful professional networking website has had the profile views feature for a while, but in the spring of 2014 it began to show its users the viewer s profession, company, and industry; what region the viewer lives in; the keyword searches they used to reach them, and other insights. 17 All users have the ability to limit what information another user sees. Beyond this, LinkedIn offers its users tips on how to gain more profile views. In these ways, LinkedIn is not only learning more about its own customers through big data, it s also directly engaging customers in ways that empower them to manage the connections they make. And that gives LinkedIn insight about how to make a better product and keep its customers happy. 3 USAA This Texan financial services company is well-known for its customer service which comes from an effective mix 50,000 Facebook users signed a petition protesting a program that tracked their online behavior The most effective omni-channel marketing is built on real human interactions between companies and customers. No computer algorithm can give you that of big data intelligence and direct customer engagement. Five years ago, USAA brought together its services and sales teams, its digital and mobile commerce teams, and its marketing team to become a single integrated unit. 18 In this sense, USAA has embraced an idea we already discussed that big data assets should not operate in isolation. True customer insight is gained through an integration of data experts and marketing professionals. USAA is a powerful example of how companies directly engage their customers on a regular basis. Wayne Peacock, USAA s head of member experience, has described it this way in an interview with Information Week: We re serving our members from the time they re teenagers and young adults all the way through the adult years and leaving a financial legacy, so we thought it would make a lot of sense to have them talk to us about what s going on in their financial lives. Peacock talks about technology as a great enabler ; 90 percent of USAA s interactions with its customers are through digital means. However, technology alone doesn t drive the beginning and the end of customer interactions. USAA engages with customers directly through its online platform and contact centers. 13 of 17

14 continuous, picking up on one platform where another left off. The most effective omni-channel marketing is built on real human interactions between companies and customers. Real and natural conversations build brand loyalty and create happy customers. No computer algorithm can give you that. Big data, in short, should be used hand-inhand with your customer insights team. As we ve seen, it s the melding of data scientists, who know how to gather, organize and analyze data, and insight professionals, who can interact with real-live customers and add a human perspective to big data, that will create true insight. These are but a few examples of how companies are leveraging big data with direct customer engagement to achieve actionable insight. Big data offers much promise, we shouldn t rely on it to the extent that human engagement is taken out of the equation. Big data presents us with correlations; one set of facts is correlated with another set of facts and conclusions are made about the relationship between the two. But we don t know if one set of facts actually causes another. In a world in which data governs so much of our lives and drives decisions, engaging directly with customers becomes ever more vital. This is especially true for omni-channel marketing, where the best customer relationships are fostered by conversations that are CONCLUDING THOUGHTS The big data revolution is upon us. With it comes tremendous insight into customers daily lives, their needs and desires, their personalities, and their rapidly evolving tastes and loyalties. The digital world we live in has sped up everything, and it s hard to keep up. We re only human, after all. While big data and smart analytics can help us understand our customers, it can t yet provide a complete picture. And that s where human intelligence comes in human-to-human connections that provide a company with insight it can get nowhere else. 14 of 17

15 END NOTES 1 The Rise of Big Data: How It s Changing the Way We Think About the World, by Kenneth Neil Cukier and Viktor Mayer-Schoenberger, Foreign Affairs, May/June 2013 https://www.foreignaffairs.com/articles/ /rise-big-data Humanizing Big Data, by Colin Strong, published by Kogan Page, things you need to know about big data, by Jamie Hinks, techradar, April 9, techradar.com/us/news/world-of-tech/future-tech/5- things-you-need-to-know-about-big-data A Very Short History of Big Data, by Gil Press, Forbes, Press cites the article by Denning, which can be found at: 3 Data, data everywhere, Interview with Keith Cukier, The Economist, Feb. 25, economist.com/node/ Facebook Users are Uploading 350 million new photos each day, Cooper Smith, Business Insider, Sept. 18, Five unusual ways businesses are using Big Data, SmartDataCollective, April 17, Five unusual ways businesses are using Big Data, SmartDataCollective, April 17, Big Data: The Management Revolution, by Andrew McAfee and Erik Brynjolfsson, Harvard Business Review, October https://hbr.org/2012/10/ big-data-the-management-revolution/ar 8 How Big Data Is for Marketers, by Larisa Bedgood, SmartDataCollective, April 16, how-big-data-marketers 9 56% of Enterprises Will Increase Their Investment In Big Data Over The Next Three Years, by Louis Columbus, Forbes, March 22, forbes.com/sites/louiscolumbus/2015/03/22/56-of- enterprises-will-increase-their-investment-in-big-dataover-the-next-three-years/ 10 Using Big Data And Machine Learning To Enrich Customer Experiences, by Kurt Marko, Forbes, April 8, big-data-machine-learning_customer-experience/ 11 You May Not Need Big Data After All, by Jeanne W. Ross, Cynthia M. Beath and Anne Quaadgras, Harvard Business Review, December https://hbr.org/2013/12/you-may-not-needbig-data-after-all 12 FTC to examine privacy issues with cross-device tracking, by Mark Pribish, The Arizona Republic, April 10, Smartphone users value their privacy and are willing to pay for it, CU-Boulder, Dec. 10, smartphone-users-value-their-privacy-and-are-willingpay-it-cu-boulder 14 How Target figured out a teen girl was pregnant before her father did, by Kashmir Hill, Forbes, Feb. 16, Digital Insights Are the New Currency Of Business, Forrester Research, April 2015 https://www. forrester.com/digital+insights+are+the+new+currency+of+business/fulltext/-/e-res The Amazing Ways Netflix Uses Big Data To Drive Success, by Bernard Marr, LinkedIn, March 26, 2015 https://www.linkedin.com/pulse/amazing-waysnetflix-uses-big-data-drive-success-bernard-marr 17 How LinkedIn uses big data to increase visibility and enhance your brand, by Caitlin Zucal, Investment- News, March 5, article/ /blog09/ /how-linkedinuses-big-data-to-increase-visibility-and-enhance-your 18 USAA Develops Cross-Channel Capabilities to Improve Customer Experience, by Bryan Yurcan, InformationWeek, Dec. 13, banktech.com/channels/usaa-develops-cross-channel-capabilities-to-improve-customer-experience/d/d-id/ ? 15 of 17

16 ABOUT THE AUTHOR Tyler Douglas, chief marketing officer of Vision Critical, is a seasoned leader and entrepreneur with a proven track record. Tyler co-founded and led IronPoint Technology, a market leader in web content and collaboration software, through to its acquisition by the Active Network. Staying on at the Active Network, Tyler helped drive the company from a $30 million to a $300 million organization, including a successful IPO on the New York Stock Exchange in Tyler s success is rooted in an enduring commitment to deep customer insight and the competitive advantage that quality customer intelligence delivers. 16 of 17

17 LEARN MORE AT Vision Critical s Cloud-based Customer Intelligence Platform enables companies to build customer communities that provide ongoing, rapid feedback and insight to enable smarter decision-making. DEVELOP Better Products IMPROVE Customer Satisfaction INCREASE Customer Loyalty

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