Data driven big data

A GUIDE TO THE 2013 CONSUMER ELECTRONICS SHOW

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CHAPTER 2 DATA-DRIVEN MARKETING

CH 2 : DATA-DRIVEN MARKETING 29

DAVE MORGAN CEO, SIMULMEDIA

Dave Morgan is the CEO and founder of Simulmedia. He previously founded and ran both TACODA, Inc., an online advertising company that pioneered behavioral online marketing and was acquired by AOL in 2007 for $275 million, and Real Media, Inc., one of the world’s first ad serving and online ad network companies and a predecessor to 24/7 Real Media (TFSM), which was later sold to WPP for $649 million. After the sale of TACODA, Morgan served as Executive Vice President, Global Advertising Strategy, at AOL, a Time Warner Company (TWX). He serves on the boards of the International Radio and Television Society (IRTS) and the American Press Institute (API), and was a long-time member of the executive committee and board of directors of the Interactive Advertising Bureau (IAB).

MATT SPIELMANSVP OF STRATEGY, MOXIE

Matt Spielman is the SVP of Strategy for Moxie, a full-service digital advertising agency within the Publicis Groupe. He heads the digital AOR and leads the strategy and innovation initiatives for L’Oreal USA. Prior to joining Moxie, Spielman spent six years at MTV Networks where he helped build the network’s Client Solutions Division, working with senior marketing clients to develop and deploy marketing initiatives that leveraged the entirety of MTV Networks properties, brands and assets across all media. He also served as Vice President of Business Development and Account Management at IAG Research (acquired by Nielsen). At IAG, he oversaw a research team that advised senior marketing executives and their agencies on the effectiveness of their TV and in-theatre marketing efforts and made recommendations on how to improve their results.

BRYAN SCANLONPRESIDENT, SCHWARTZ MSL AND NORTH AMERICA TECHNOLOGY DIRECTOR, MSLGROUP

Based in Silicon Valley, Bryan Scanlon is the president of Schwartz MSL, a global public relations agency specializing in the technology, health and energy innovations that transform business, preserve the planet and save lives. He also leads the MSLGROUP North America Technology Practice, helping clients move innovation to the forefront of their brands, and specializes in information security, big data and analytics, and data-driven thought leadership and marketing programs. Scanlon has a 20-year track record of building awareness, valuation, sales and brand equity for some of the most successful technology companies. He’s taken many clients from start-up to market leadership and reinvigorated established technology brands. This includes work with Red Hat, Netezza, Symantec, ServiceNow, Hortonworks, Blue Coat, webMethods (now Software AG), Imation, LifeLock, ESET and MicroStrategy. You can follow him on Twitter @bkscanlon.

ROB JAYSONCHIEF DATA OFFICER, ZENITHOPTIMEDIA

Rob Jayson leads ZenithOptimedia’s worldwide data strategy, a role he assumed in 2012. A combination of continual innovation, robust analytics and tools development have allowed him to be instrumental in finding new and exciting ways to approach communications planning. As Chief Data Officer, Rob oversees the agency’s Global Analytics Center (GLANCE), collaborating with ZO entities such as Ninah, Performics and Moxie. He also manages the implementation of the ZO Datamart and reporting tools suite, and focuses on brand-specific data strategies, such as ZenithOptimedia’s “Live ROI.” Most recently, Rob served as President of Strategy for Zenith where he was responsible for developing communication planning methods, ensuring planners led their clients and the industry in creating unique and powerful communication strategies.

31CH 2 : DATA-DRIVEN MARKETING

INTRODUCTION PART 1 : THE RISE OF BIG DATA

The world is awash in data. Every time a consumer uses a credit card, a purchase-history is created. Loyalty programs grant companies and retailers access to consumers’ purchase patterns and preferences. Every mouse click leaves a trail to follow. We know more about consumers than ever before, and they know more about us.

All of this data can be empowering, or it can be daunting. More information means greater insights, smarter thinking and better decisions all around. But with new data coming in every day, we can become subject to “analysis paralysis,” delaying decisions and programs until we get the most information possible, to be sure we’re making the right decisions. The key is for us to recognize that data is not information, nor is information the same as insights. Instead, we have to process data to reveal insights on a timely basis that can be actionable.

Fifteen years into the Information Age, we’re just figuring out what it all means. We have access to more data and information than

ever before, but we’re still trying to figure out what information is good and what is bad. What information is truly effective at increasing our ROI, and what is just more “white noise?” We’re only now beginning to understand what works and what doesn’t. But even as we do, more information is presented to us, sometimes reinforcing our marketing programs. Sometimes, it requires them to change completely, on a moment’s notice. The need to be nimble, agile and flexible has never been greater.

We have reached a point where the art of marketing and the science of data are completely intertwined, and are ever more inseparable. It’s time to learn how to harness the ever-increasing streams of information (mobile and social alone are creating a large number of data sources) and use them to our benefit—just as consumers are doing with the information they get. Rather than making our marketing data-dependent, we need to make it Data-Driven.

Data has always been a centerpiece of marketing. From decades-old techniques such as consumer research surveys, product purchaser panels and customer relationship marketing to newer, financial-market approaches like time-series modeling, chief marketing officers have always looked to data and analytics to drive their decision-making. In the modern age, however, two critical changes are transforming the marketing landscape in ways we could not have imagined. First, there has been a huge increase of available data to track consumer attitudes and behaviors in real time. Second, we as marketers have increased our ability to blend and filter that mass of data into actionable insights that shape marketing campaigns at the strategic and the tactical level.

The explosion in consumer data is massive and exponential. According to the McKinsey Global Institute, the volume of consumer information generated in a year has exceeded six exabytes. That number – one that we cannot even really define – would fill more than 60,000 U.S. Libraries of Congress. It’s more than every word spoken by humans if they were to be digitized as text. 1

That’s what consumers and data companies are producing and storing every year. According to McKinsey, “The increasing volume and detail of information captured by enterprises, together with the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future.” 2

Data, while exploding, is becoming easier to manage, combine and evaluate. Martin Hilbert and Priscila López in Science magazine analyzed global storage and computing capacity, and found that not only is our ability to accumulate and store data growing, but storage capacity has become almost exclusively digital (as opposed to analog). 3

1 McKinsey Global Institute, “ Big data: The next frontier for innovation, competition, and productivity,” June 20112 Ibid.3 Hilbert and Lopez, “The world’s technological capacity to store, communicate, and compute information,” Science, 2011

DATA STORAGE HAS GROWN SIGNIFICANTLY, SHIFTING MARKEDLY FROM ANALOG TO DIGITAL AFTER 2000Global installed, optimally compressed, storage

OverallExabytes

NOTE: Numbers may not sum due to rounding.SOURCE: Hilbert and López, “The world’s technological capacity to store, communicate, and compute information.” Science, 2011

100%=

Digital

Analog

1986 1993 2000 2007

Detail % : exabytes

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This change in capacity and digitization of data storage has huge implications. We now have a window into consumers’ lives and almost every aspect of their relationship that they build with

the brands we market to them. We also have the potential to manipulate, match and manage that mass of data in almost limitless ways. (See Sidebar: Are you prepared?)

We all know the era of Big Data is upon us. Yet, many in the industry are still unprepared. A recent IBM CMO survey showed that – while CMOs understand in no uncertain terms how critical Big Data is to their future success – many admit they have yet to find the correct techniques and management approaches. Forrester, meanwhile, surveyed business decision-makers about what they viewed as their most critical challenge in putting Big Data to use effectively. The responses were all over the map, and the fact that there was little consensus shows that each organization needs to set its own priorities about how to tackle Big Data.

However, no task is more essential than to examine all of the potential

issues that could be resolved with the help of Big Data and prioritize them. The most critical and beneficial step that any brand leader can take, in order to start the process of harnessing the power and insights of Big Data, is to establish a data strategy and a set of key performance indicators (KPIs) that outline in detail the direction of insights that are needed from data analysis in order to increase marketing ROI.

The systems and data priorities that are established will clearly be significantly different if the organization’s top Big Data priority is about the ability of the internal organization to share data in real time as opposed to a primary challenge of not getting access to real-time data at all.

SIDEBAR : ARE YOU PREPARED?

TABLE 2 Biggest challenges to use of “big data” for marketing

0 10 20 30 40 50 60

29%

51%

42%

45%

39%

We have too little or no customer/consumer data

Our data is collected too infrequently or is not real-time enough

The lack of sharing data across our organization is an obstacle to measuring the ROI of our marketing

We are not able to link our data together at the level of individual customers

We aren’t using our data to effectively personalize our marketing communications

50%

PERCENT OF CMOS REPORTING UNDERPREPAREDNESS

71%Data explosion

Social media 68%

Growth of channel and device choices 65%

Shifting consumer demographics 63%

Financial constraints 59%

Decreasing brand by loyalty 57%

Growth market opportunities 56%

ROI accountability 56%

Consumer collaboration and influence 56%

Privacy considerations 55%

Global outsourcing 54%

Regulatory considerations 50%

Corporate transparency 47%


All of this data is being set up for another revolution: the Live Data Stream. With powerful portable devices and always-on connections, consumers are constantly feeding a stream of data—in real time—about brand attitudes, feelings and behaviors.

This data, can be harnessed and turned into actionable insights.

Thanks to smartphones, tablets and other connections, consumers have turned to digital channels to supplement their knowledge, behavior and attitudes to brands. This has dramatically increased the volume of real-time or live data that brand owners and agencies can access to illuminate up-to-the-minute changes in brand metrics. But those metrics aren’t coming to us in the easily defined and “traditional” formats of past consumer behavior. Rather, they are coming in the forms consumers have already embraced, like social media.

Even more is coming. According to an eMarketer forecast, social network growth, although slowing,

will grow to cover more than 50 percent of the North American population through 2014.4 Every “Like” of a brand on Facebook, and every brand-name hashtag on Twitter is another piece of data that can be used to inform marketing, but each comes with its own set of rules and parameters.

Facebook and other social media are not the only sources of live data, and they are not the only cause of the explosion. Smartphones have become

4 eMarketer, “Social Network Users and Penetration in North America, 2011-2014,” February 2012 5 Foresee 2010 Retail Satisfaction Index

PART 2 : THE LIVE DATA STREAM

a constant companion for consumers, and are used during their traditional media experiences. Pew Research shows that 74 percent of smartphone owners use their device while watching

TV for a multitude of purposes. Some use them to multitask, conducting online searches for information. Others post to their social media feeds. Still others use their phones to participate in promotions they’ve seen advertised on television, or through their secondary online browsing. Each one of these data points tells us something different about the effectiveness not only of the message, but of the channel and attitude of the consumer to the brand messaging they’re being exposed to at that very moment. Recommendation engines are a perfect example of how brands have structurally adjusted to the benefits of Big Data analytics to great advantage. Amazon (and most other e-retailers) have developed effective real-time recommendation engines based on analysis of massive amounts of real-time data to engage shoppers without resorting to traditional mass, untargeted pricing and discounting. The ability to create personalized, helpful suggestions for consumers has had a significant impact of customer satisfaction data, and there is clear evidence that satisfied customers are more likely to purchase, be loyal and to recommend a brand.5

SOCIAL NETWORK USERS AND PENETRATION IN NORTH AMERICAmillions, % of internet users and % of population

63.6%

47.2% 49.8%

65.8%

51.4%

66.9%

52.9%

68.0%

163.9

2011

Social network users

% of internet users

% of population

174.7

2012

181.9

2013

189.2

2014

NOTE: Internet users who use a social network site via any device at least once per month; includes Canada and the USSOURCE: eMarketer, Feb 2012

SMARTPHONE OWNERS LEAD THE WAY IN “CONNECTED VIEWING” EXPERIENCES% in each group who have used their phone in the preceding 30 days to...

SMARTPHONEOWNERS (N=904)

OTHER CELL OWNERS (N=1050)

Keep yourself occupied during commercials or breaks in what you were watching

58% 17%

Check whether something heard was true or not

37

6

Visit a website mentioned on TV 35 3

Exchange text messages with someone watching the program

32 13

See what others were saying online about a program you were watching

20 2

Post your own comments online about a program you were watching

19 2

Vote for a reality show contestant 9 4


The data that would allow brands to personalize the experience in real time for consumers is already available, and some brands are finding ways to put it to work. That said, brands are still a long way from being able to deliver on that opportunity. The e-tailing group surveyed 131 mostly large and mid-sized Web merchants in Q3 2011, and found that more than half gave themselves poor marks in their personalization efforts.

To manage this ever-increasing, live-stream of Big Data, organizations must set themselves up internally to respond to the insights available. Brands must adjust their internal processes and marketing plans in ways that will enable them to immediately respond to consumers’ actions as information is received. Consumers have embraced social media and other live interaction opportunities with brands. It is incumbent on the brands to respond in-kind with immediate, personalized responses.

Learning how to harness and manage this data can yield huge returns. Nucleus Research found organizations can earn an incremental ROI of 241 percent by using Big Data capabilities to examine large and complex data sets. These returns are the result of improved business processes and decisions through optimizing the increased types of data available and the ability to monitor the factors that impact a company most, such as customer sentiment, by scouring large external data sources such as social media sites. These abilities are the hallmarks

SOPHISTICATION LEVEL* OF THEIR CURRENT PERSONALIZATION EFFORTS ACCORDING TO US RETAILERS, Q3 2011% of respondents

1-354% 4-6

33%

7-1013%

NOTE: *on a scale of 1-10 where 10 = “very sophisticated” and 1 = “not at all sophisticated”SOURCE: the e-tailing group, “Prioritizing Personalization For Growth,” Nov 11, 2011

PART 3 : FROM AUTOMATED AND TACTICAL TO PREDICTIVE

of a Predictive Company (as opposed to a Tactical, Automated or Reactive one.)

Nucleus Research identified four critical areas of benefit to big data analytics that organizations can realize from the use of Big Data:

1. Big Data solutions that encompass vast data sets enable solutions that link all aspects of the business together. Retailers can link insights about their loyalty program customers with in-store behavior and social behavior.

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PredictiveStrategicTacticalAutomated

2. Big Data accelerates decision-making. Customer churn, for example, can be addressed in real time, rather than only fixing issues that contribute to churn long after a customer has left, live-data analytics can uncover and suggest solutions for better customer retention as they emerge.

3. Combining external data with internal data adds significant value to internal data. Adding geographic, meteorological or other external datasets creates much more sensitive analytics.

4. Big Data analytics is critical to successful online sentiment monitoring. The ability to define meaningful results from “noise” is not really possible without new Big Data techniques.

Yes, these changes are difficult. And it may require years of “unthinking” the practices of the past. But marketers who can make the attitudinal and structural modifications to realize the full benefits of Big Data will reap significant rewards. Moving from a tactical/reporting position to a strategic and predictive approach will generate a measurable increase in marketing ROI, and a significant lift in business. (See Sidebar: Moneyball)


The popular book and film "Moneyball” illustrated how the smart use of data and statistics transformed a 150-year-old sports pastime and business. The same is happening with advertising. For years, baseball had been managed according to gut instinct and near-mythical truisms. In the early 21st century, one outlier, Bille Beane, used data, statistics and financial market-like techniques to bring success to a payroll-challenged team. Beane's use of sophisticated data analysis to identify which player statistics really mattered—a player's on-base percentage rather than batting average, for example—gave him a real advantage in finding players who were undervalued by his competition. These days, the research and insights Beane used have become commonplace among his competitors and all of Major League Baseball.

Marketers must apply the same game-changing insights to the information available to them. For marketers, the data explosion is

not just about online messaging exposure and real-time response. Now, there is real-time behavioral data on our customers, allowing us to figure out their level of interest in our brands, their loyalty and potential for incremental cross- sales. Matching first-party data from brand customers with third-party data from other online and offline sources, can give marketers and their agencies unprecedented insights into the relationship of media and messaging at the campaign and individual spot basis to specific brand customers and their actions.

These Database Management Platforms, where we collect and analyze the Big Data that comes from brand customers as well as other online behavior, offer the potential to make strategic and tactical marketing decisions based on a mass of statistical data and analysis that has never been available before. To stretch an analogy, we can draft new target audiences, never before considered based upon the behaviors we have seen from the data analytics on current customers and potentials.

As media become more digital—and, as a result, more targetable, measurable and accountable—these analytics will be crucial. Even television, which has long resisted change is changing fast as more of it is delivered through digital set-top boxes, over Internet protocol networks or on the tens of millions of new smart, Internet-connected TVs and companion devices that are shipping around the world this year. Not only will these new TVs connect directly to the Internet, but they will run Web-based apps, link new cloud-based streaming services and also produce a treasure-trove of data and direct consumer-viewing measurements, which will open up TV advertising to Billy Beane-like transformation.

This does not mean that the “art” of the media industry will be forever trumped by “science.” However, decisions about which media to buy will no longer be driven by history, comfort and relationships. Data and predictive science will drive more and more media decisions. And the results will solve many of the problems plaguing our industry. Such as:

Wasted frequency. In most mass-awareness TV ad campaigns in the US today, 80 percent of the spots end up being delivered to only 35

percent of the target audience, and a full 30 percent of the desired target receives none. The culprit? Audience fragmentation. Fifteen years ago, that 80 percent was spread to more than 60 percent of the target, and the size of the unreached target was very small. Now, data analysis is being used to determine the exact makeup of a show's audience and to perfectly measure and manage the reach and frequency of TV ad campaigns with online-like frequency capping.

Finding elusive audiences. Trying to find young males outside of sports content? Hispanic audiences within English-language content? Or light TV viewers you can't reach efficiently with broadcast-centric prime-time campaigns? Data will find them. Marketers will discover gold using data to aggregate valuable audiences from unconventional places.

Creative testing. With robust cross-channel data, you can now know which viewers abandon your ads and which viewed them. Not only will we learn which audiences actually like our ads, but we'll be able to test and optimize creative

SIDEBAR : MARKETERS MUST PLAY ‘MONEYBALL’

DATABASE MANAGEMENT

PLATFORM

PLANNINGDATA

3RD

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Becoming a Predictive Company, however, will require changes in the ways many do business, both at the macro and day-to-day levels. In a world soon awash in Big Data and opportunities to use it, one thing is clear: there are not enough people in today’s marketing organizations with the level of experience in using Big Data to make companies successful in the future. And many of these organizations do not have the right tools and processes needed to survive—much less thrive—under the coming tidal wave of information.

In the Big Data-driven world, marketing organizations need to infuse themselves with experts. Mathematicians, scientists, statisticians, software and hardware engineers. All will be important to companies looking to harvest and harness Big Data and turn it into useful, actionable information. It’s a page from the playbook of today’s fastest-growing digital companies. Look at the hiring practices of Google, Amazon, Apple, Microsoft, Facebook and Twitter. Employees in those companies are different from those hired by traditional marketing and media companies. They possess:

TECH-SAVVY LEADERSHIP. Not only are the most successful digital companies well-stocked with engineers, scientists and tech-centric product managers, but technology is the primary skill set of their leaders and their workers. They drive the businesses, the products and the core strategies.

HARD SCIENCE. Many marketing-related companies, particularly in media, still rely on qualitative “social” science in much of their decision-making, not the kind of quantitative sciences needed to exploit Big Data. Yet, hard numbers are the new reality of

units in live environments. Think of the improved efficiency if we can get audiences to stick around and watch ads because the data tells us which ads will stick with them.

Secondary measurement and promises. Nielsen, comScore and panel ratings aren't going away. Macro audience ratings will be with us for a long time. However, those measurements will be supplemented with micro-measures of exact audience patterns, which will be baked

into ad campaign deals. Imagine delivering your Gross Ratings Points with set-top box data-based guarantees of specific audience compositions—such as frequent moviegoers who like dramas, or Coca-Cola brand fans—or guarantees of attributed sales by linking household-level viewing data with actual purchases.

We’ve moved into the “Moneyball” era. Are you ready?

ANALYTICS AND DATA SCIENCE JOB GROWTH

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the advertising and marketing industry. Marketers need cognitive scientists, statisticians, mathematicians and physicists.

DIVERSITY. In fast-growing digital, data-driven companies, diversity is a competitive advantage and a business imperative.

IMPATIENCE. Companies like Amazon, Google and Apple have relatively flat organizational cultures, and their employees have no time or patience for the kind of long, escalator-like ride over decades to reach leadership positions that exist in many non-digital companies. They know what they want and they want it now.

VERSATILITY. In traditional marketing organizations, many folks are “bucketed” into roles and silos during early stages of their careers and find success through focus and unique expertise. Invariably, some of the strongest talents in emerging, digital and data-driven companies have degrees that span both science and arts, work better horizontally than vertically, and take pride in constantly changing gears in their careers.

However, hiring the best is only part of the equation. (And a very difficult piece at that. There is a limited pool of emerging talent with Big Data skills, and competition for the best is intense—much like the competition we’ve seen for computer scientists over the past 10-15 years. It’s a certainty that demand for data scientists will outstrip supply for years to come.) Companies must also adjust, adapt and improve their internal processes and procedures to ensure they’re set up to capitalize on the information and insights created by these streams of Big Data. Among the things they need to keep in mind:

BIG DATA TECHNOLOGY IS GETTING BIGGER, BETTER, FASTER AND CHEAPER. Innovation in analytic tools, systems and platforms has exploded over the past few years, particularly in the open-source community. Open-source data management technologies like Hadoop and pay-as-you-go cloud-based data services like Amazon Web Services and Mongo Database are replacing comparable data management systems from companies like IBM, Oracle and Teradata that cost

millions upon millions of dollars. In many cases, enterprises can build or buy analytic data warehouses that are 100 times bigger than those available 10 years ago - for 1/100 the cost.

This means companies with data technologies that are only five years old will find themselves at significant disadvantages in both capabilities and cost structures to competitors with new technology. Investments in new data technology on a regular basis will be critical for marketing enterprises to remain competitive.

DATA ANALYTICS IS BECOMING MORE BROADLY ACCESSIBLE ACROSS ORGANIZATIONS. Not only can these new data systems store massive amounts of data, but they can also manage unstructured data, giving users far more flexibility in how they organize, manage and query the data. This is helping companies make data much more accessible and available across organizations. Whether it is trying to understand purchase behaviors of target customers or sales attribution to social media, what was once

the domain of the research department is now available to managers at all levels of marketing organizations. (See Side Bar: Trust and Security)

Investing in new employees, technologies and processes to better serve Big Data is not an option. Companies looking for competitive advantages will target these three areas for strategic, competitive and market share growth. Those that do not will be left behind.

The era of Big Data is upon us. Thanks to the tools of the Connection Engine (smartphones, tablets and super-fast, always-on connections), consumers are giving marketers a wealth of actionable information. It’s up to marketers to turn that information into valuable insights and programs that reward consumers based on their needs, information and realities. The data is coming in real time and marketers must react with the same spontaneity. Information moves at the speed of light; marketing programs will have to move just as quickly.


SIDEBAR : BIG DATA: BIG SECURITY NEEDS

Fifty-five percent of CMOs feel unprepared for the privacy considerations in the exploding digital world (Source: 2011 IBM CMO Study).

In March of 2012, the Federal Trade Commission (FTC) published “Protecting Consumer Privacy in an Era of Rapid Change,” delivering basic principles that emphasize awareness, transparency and care in dealing with customer or community information. The report mandates protection at many levels, simple customer-driven options and transparency and disclosure.

“In its guidance and actions, the Federal Trade Commission (FTC) is asking for privacy by design, built from the ground up with consumers getting notice and choice,” says Gary Kibel, a partner in the Digital Media & Privacy Practice Group of Davis & Gilbert. “If you are a brand, you have to look at the whole process of how data flows.”

In addition to stricter privacy guidelines and increased FTC action, another real brand threat emerges: the increasing complexity of keeping data that resides and moves across complex

social, mobile and financial ecosystems safe from security breaches or organized hacks.

Every state has different levels of breach notification and action. With nationwide customer bases, resolution is messy, time-consuming and expensive for anyone experiencing a breach. And according to research done by Imation (see image, right), the strictest states have relatively low bars that trigger mandatory notification of consumers, credit agencies and government entities.

Actual or even perceived violations are a one-way ticket to losing a customer, not to mention fines and potential costs of remediation. There is clear expectation that brands will be careful with personal information, and errors come with a high price. According to ongoing research from PricewaterhouseCoopers LLP, consumers are far more worried about security breaches than privacy, and 61 percent of those surveyed said they’re “not willing to continue to use a company's services or products after it experiences a security [breach].” (Source: http://www.pwc.com/us/en/industry/entertainment-media/assets/pwc-consumer-privacy-and-information-sharing.pdf)


To realize their full potential, organizations must be set up to respond to Big Data insights in real time. Brands will need to adjust their marketing plans to immediately respond to consumers’ actions as they learn about them. Consumers have embraced social and other live-interaction opportunities with brands, and they fully expect brands to respond in-kind with immediate, personalized responses.

It will take considerable change for brands to begin to realize the full benefits of Big Data analytics. But if those hurdles can be overcome, the benefits are clear and significant. Moving from a tactical/reporting position to a strategic and predictive approach will generate a measurable increase in marketing ROI.

The ability to collect and analyze massive amounts of data and the application of predictive science are transforming how marketers and agencies manage media. These insights can help develop strategies and reach new potential target audiences with customized messaging, as well as aid measurement, optimization, attribution and accounting.

Marketing organizations will not be able to exploit Big Data without investing in new types of people, technology and processes. It will be a requirement.

In the Big Data world, security and trust will become brand currency. Strong security and privacy communication can actually strengthen customer loyalty. Trust is good business, and it is (and should be) desired by consumers and the agencies looking to protect them.

Big Data requires a trust reset and close, careful management of data in the new world. But the good news is that consumers are eager to partner on privacy, and the best marketing tackles engagement as a partnership with clear and agreed-upon benefits for all.

Consumers seem to have an insatiable appetite for monetary incentives, trend information and a desire to be part of something broader. According to PricewaterhouseCoopers LLP surveys, “80 percent of respondents said they were willing to share personal information if the company lets them know upfront how they are going to use it.”

Meanwhile, brands are becoming their own news organizations, pushing out data and advice to their customers and markets. But in an age where information saturates, trust is one of the vital filters for consumers to decide

what brands to even pay attention to in the increasing barrage of information.

According to the 2012 “Trust Factor” study by About.com, 84 percent of consumers say “being trustworthy is a requirement before interacting with a brand or info source.” (Source: http://www.advertiseonabout.com/wp-content/uploads/2012/07/AboutTheTrustFactor.pdf)

In the era of Big Data, trust and security will become something as valuable (if not more so) than any other brand attribute. Consumers will be on the lookout for brands that treat the information they’re sharing with respect, rewarding those that value the information in trustworthy and secure manners, and shunning those that do not. Consumer trust and security of their personal information must get the same attention as every other brand attribute.

“CONSUMERS FEEL MORE COMFORTABLE SHARING INFORMATION IF THEY UNDERSTAND THE BENEFITS TO THEM INDIVIDUALLY OR AS PART OF A LARGER GROUP” – PWC SURVEY.

KEY TAKEAWAYSTHINGS TO THINK ABOUT ON THE CES FLOOR

Every new technology will provide you with access to even more consumer information. How will you access it? How will you incorporate it into your current marketing processes? Are you equipped to harvest and harness that data with personnel and/or technological systems? What might you need to add to your internal operations to yield the best information from this data? How will it support and/or work in conjunction with other data streams?