The Top five Myths of Big Data Analytics

data-driven
marketing
05.13

The Top Five Myths of
Big Data Analytics
What Every...
data-driven
marketing

The Top five Myths of Big Data Analytics

05.13

Introduction
Big data is big news—and for good rea...
The Top five Myths of Big Data Analytics

data-driven
marketing
05.13

themselves prefer a more targeted approach, reporti...
data-driven
marketing

The Top five Myths of Big Data Analytics

05.13

Myth No. 5: The big data conversation starts with
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Data driven marketing - The Top Five Myths of Big Data Analytics - May 2013

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Data driven marketing - The Top Five Myths of Big Data Analytics - May 2013
What Every Marketing Leader Needs to Know

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Data driven marketing - The Top Five Myths of Big Data Analytics - May 2013

  1. 1. The Top five Myths of Big Data Analytics data-driven marketing 05.13 The Top Five Myths of Big Data Analytics What Every Marketing Leader Needs to Know 1 EB 6787
  2. 2. data-driven marketing The Top five Myths of Big Data Analytics 05.13 Introduction Big data is big news—and for good reason. The numbers are stunning. Global data generated by enterprises is projected to increase by 40 percent annually. And in 15 of the 17 major industries in the United States, more data is stored per company than in the entire Library of Congress.1 And no wonder. Companies are amassing new and different types of information—from sensor data to social media content—at ever-increasing rates. At the same time, global IT spending is projected to grow at just 5 percent annually, leaving IT teams unsure how to accommodate this exponential growth in information emerging from every facet of the enterprise. 2 Marketing leaders may be thinking, “That’s all well and good, but what does it have to do with marketing?” The answer is simple: just about everything. In fact, the rise of big data may be more relevant to marketers than to anyone else in the enterprise—including IT. This paper takes a look at the hard truths and common misconceptions surrounding big data. In particular, it focuses on five common myths about large-scale analytics, then offers a glimpse at the next steps necessary to make big data work for you. Defining ‘Big Data’ The phrase “big data” refers to datasets so large and complex that traditional analysis programs are unable to process them. With help from recent technology advances in big data analytics solutions, marketing leaders are able to better manage these datasets, thus informing their marketing efforts for more targeted, personalized interactions with customers. Big Data Myths By this point, you’ve surely heard a number of conflicting claims about big data. Who is it for? What can it do? And why all the fuss anyway? Here are five of the most common big data myths—and an attempt to separate fact from fiction. 2 EB 6787 “The idea is to drive toward a white-glove customer experience, so that we know you as an individual even if you’ve only come to us three or four times. Now we can have an interaction that is much more personalized.” —Marc Parrish, Vice President of Customer Loyalty and Retention, Barnes & Noble Myth No. 1: Big data is only for IT You might assume that chief information officers (CIOs) have been at the forefront of the big data phenomenon, but that’s not necessarily true. In fact, Forrester Research estimates that more than 45 percent of big data deployments are for marketing. 3 The reason is fairly simple: Your customers’ unique preferences have already been captured in your data. By harnessing that data, rapidly analyzing it for new insights, and using it to create personally tailored marketing campaigns, you can offer customers the best possible experience in every single engagement. This is called data-driven marketing, and it’s one of the most effective ways for organizations to take full advantage of the extensive customer data already in their possession. Myth No. 2: Big data is just hype Marketing leaders are understandably worried that big data represents yet another hype cycle. But the fact is that marketers in every industry are already using big data analytics to increase revenue, reduce the cost of going to market, and improve the accountability of all their activities. By segmenting and targeting prospects based on specific behaviors, marketers can increase open rates by more than 50 percent and increase conversion rates by more than 350 percent. Meanwhile, operating costs go down considerably—as much as 43 percent.4 Customers
  3. 3. The Top five Myths of Big Data Analytics data-driven marketing 05.13 themselves prefer a more targeted approach, reporting that they are 40 percent more likely to purchase from retailers who personalize across channels. 5 In short, the cost of not embracing big data is too great for you to risk—and the risk will only grow. In a recent survey of 2,000 consumers in the United States and United Kingdom, leading management consultant firm Accenture found that 73 percent of respondents prefer to do business with retailers who use personal information to make their shopping experience more relevant.6 Myth No. 3: Big data is unstructured Many people think that big data simply means that data is “unstructured” and further assume it’s too difficult to analyze. But more accurately, big data is “multi-structured,” meaning there is a variety of data types—with some fitting nicely into rows, as in a Microsoft Excel spreadsheet, and other data falling into less easily analyzed formats. Because of this, big data requires some extra work to unify—and technology has advanced to the point where most of that work is automated. The truly multi-structured data is what many marketers have been struggling with for years: weblogs, email content, and social media data, among others. This lack of a common structure becomes more problematic with the rise of multi-channel marketing: Customers engage with “The LinkedIn member uses LinkedIn to get connected to each other, and they drive massive amounts of data. By using this massive amount of data, we derive insight to improve our paid product.” —Simon Zhang, Director of Business Analytics, LinkedIn 3 EB 6787 “CMOs must take greater ownership of the customer experience and assume a leadership role in embracing digital marketing practices, data-driven strategies, and new marketing process integration platforms across their organizations and companies. But they can only do so in close collaboration and partnership with the CIO and IT function.” —The CMO Council8 a brand across multiple channels, expecting a consistent message no matter with which channel they choose to interact. A data-driven marketing solution provides the comprehensive framework necessary to take insights from widely divergent datasets and apply them across those channels, giving marketers the ability to present personalized messaging to every customer, every time. Myth No. 4: Big data is the answer to all your problems Harnessing the power of big data analytics is crucial for moving your business forward—but it’s the execution on those insights that will drive revenue. Properly used, big data analytics of digital channels should be leveraged in conjunction with offline data to generate the deepest possible insights. That means coordinating with an integrated marketing management solution to bring insights to market in a sustainable and scalable way. With a centralized analytic environment to optimize content across both inbound and outbound channels, marketers can take all available online and offline data into account for in-depth discovery and analysis. The results are worth it. According to technology research firm Gartner, companies that develop an integrated marketing strategy will deliver a 50 percent higher return on marketing investment (ROMI) by 2014.7
  4. 4. data-driven marketing The Top five Myths of Big Data Analytics 05.13 Myth No. 5: The big data conversation starts with somebody else A scalable and sustainable data-driven marketing solution requires you and your team to collect and connect large amounts of data, gain real-time insights, and bring those insights to market by way of a tailored campaign. IT can offer the tools and expertise to make that happen—but none of it will be truly effective unless it’s informed by a strategic vision. And the vision starts with marketing leadership. Senior marketing leadership is essential in implementing a data-driven marketing strategy. Marketing leaders will still need to involve the CIO at the business level from start to finish, collaborate on designing a clear roadmap for big data analytics, and address whatever technology gaps may be keeping the company from pursuing its goals. Only then will they gain the tools, technologies, EB 6787 and insights they need to engage more deeply and richly with any customer at any time. Conclusion The rise of big data isn’t strictly an IT challenge. In fact, big data may be more relevant to marketers than to anyone else in the enterprise. With a data-driven marketing solution in place, your organization can increase revenue, reduce the cost of going to market, and improve the accountability of all your activities. But making that strategy into a reality will require proactive leadership—and leadership begins with you. To find out how you can make data-driven marketing work for your organization, visit Teradata.com/ DataDrivenMarketing. Next Steps for a Data-Driven Marketing Solution A true data-driven marketing strategy requires marketing leaders to harness the power of big data. To bring this strategy to life, it needs to meet the following infrastructure requirements: ~~Unify customer data to ensure accurate segmentation and relevant offers. ~~Apply advanced analytics to provide instant insights for generating revenue. ~~Perform marketing planning to digitize the approval and funding of activities. ~~Apply production management to oversee internal resources, maintain compliance, and help ensure brand consistency. ~~Execute campaigns in high volume across multiple channels, with the flexibility to send triggered messages based on customer behavior. ~~Enable reporting capabilities to connect the dots within your organization from planning to revenue. endnotes 1. 2. 3. 4. 5. 6. 7. 8. “Big Data: The Next Frontier for Innovation, Competition, and Productivity,” McKinsey Global Institute, June 2011. Ibid. “Big Insights from Big Analytics Roadshow,” Teradata Aster Blog, January 2013. “Assessing TCO for Best-of-Suite Versus Best-of-Breed Architectures in the Communications Service Industry,” Telecom Advisory Services, LLC, April 2007. “Personalized Marketing Drives Buyer Readiness and Sales,” Marketing Profs, March 2013. “Today’s Shopper Preferences: Channels, Social Media, Privacy, and the Personalized Experience,” Accenture Interactive, November 2012. “Focus on Integrated (Rather Than Enterprise) Marketing Management,” Gartner, October 2010. “Driving Revenue Through Customer Relevance: Aligning the CMO and CIO to Achieve Agile Intelligent Marketing,” CMO Council, October 2010. 10000 Innovation, Drive Dayton, OH 45342 teradata.com Teradata and the Teradata logo are registered trademarks of Teradata Corporation and/or its affiliates in the U.S. and worldwide. Teradata continually improves products as new technologies and components become available. Teradata, therefore, reserves the right to change specifications without prior notice. All features, functions, and operations described herein may not be marketed in all parts of the world. Consult your Teradata representative or Teradata.com for more information. Copyright © 2013 by Teradata Corporation All Rights Reserved. Produced in USA. 4 EB-6787 > 0513

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