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Using Digital Analytics to Create Business Value

📄 Contents

  1. Big Data and Data Science Requires Digital Analytics
  2. Defining Digital Analytics
Judah Phillips introduces his book, which will help you and your business determine how to manage and succeed with digital analytics while minding the gap in analytics talent.
This chapter is from the book

Today’s business organizations must apply analytics to create new and incremental value. A significant and important source of analytical data in 2013 is digital experiences—from websites to social networks to mobile applications and more. Thus, it is critical in today’s economy for businesses to develop and enhance their understanding of how digital data is collected and analyzed to either or both generate new or incremental profitable revenue or reduce cost.

Although digital analytics can significantly maximize profits in today’s competitive global markets regardless of sector or industry, creating and staffing a fully functional digital analytics organization is a complex and multifaceted initiative. Building a digital analytics organization requires rethinking and reengineering the people, processes, and technology used for creating analysis. After all, many companies believe digital analytics is about tools and technology (and data collection, like “tagging”). That belief is not accurate. While the technology and tools that support analysis are critical and necessary, they are insufficient by themselves in creating business value. Simply adding a standard basic JavaScript page tag for a free Web analytics tool to your digital experiences and providing access to reports does not create data-driven decision making or easily yield insights. Some companies believe that to be “data-driven,” they simply need to provide self-service access to business intelligence (BI) tools that provide department-specific reports and dashboards—or the basic, vanilla reporting in free or paid analytics tools.

Both these approaches are helpful to some degree and certainly move the firm toward building a digital analytics organization that considers analyses as part of the decision-making process—both strategic and tactic. After all, providing the business with the tools that collect and report data is, as previously mentioned, definitely critical and absolutely necessary. But tools and reporting are only part of digital analytics operations. Technical work and tool activities, whether used by themselves or together, are entirely insufficient for creating sustained business value through the application of digital data in business context. In other words, all the technology, servers, tagging, and tools can help you count and measure all sorts of digital metrics and dimensions, but do not by themselves (or even with the default installation) provide for any inherent actionability or impact directly delivering business value. The value from analytics is created by humans—alongside machines, tools, and technologies—analyzing data to provide insights and answers to business questions and within established and sustained business processes.

Digital analytics teams enable fact-based decision making and measure the performance and profitability of digital business channels. Data from the digital channel enhances offline data—and the combination of both (called data integration) can yield new insights and opportunities. If your company isn’t forming a team of analysts to address its digital data—whether you have big data or not—then it’s operating at a competitive disadvantage. A lack of data analysis leads to missing enormous business opportunities. A well-resourced, funded, process-oriented digital analytics team backed up by cross-functional teams from IT to marketing to finance can help your business in many ways—from determining ways to reduce costs, improve efficiency, generate new and incremental revenue, improve customer satisfaction, and boost the profitability and impact of the digital business channel. To understand what is involved with digital analytics from the beginning to the end to the beginning of the next project, see Chapter 2, “Analytics Value Chain and the P’s of Digital Analytics.” Before discussing these concepts, let’s dig deeper into what composes digital analytics, the digital analytics organization, and how establishing and evolving deep competency in digital analysis now can bring immediate and future value to the corporation.

Big Data and Data Science Requires Digital Analytics

The need for a digital analytics organization is greater than ever before—for the amount of data available to apply toward solving a business challenge is more numerous and multivariate than at any time in human history. IBM estimates that humanity creates 2.4 quintillion bytes (quintillion is one billion billion) of data every day (see Figure 1.1)—so much that 90 percent of the data in the world today has been created in the last two years alone. Obviously, much of this new data is being created by digital systems or systems linked to the Internet. Because the multitude of digital data is growing exponentially every day, a digital analytics organization is absolutely necessary to generate insights, recommendations, optimizations, predictions, and profits from this data. Whether big data, data science, omnichannel data, media mix modeling, attribution, audience intelligence, customer profiling, or predictive analytics from the applied analysis of digital data, it is essential to create a team accountable and responsible for digital data analysis. This analysis can be used for decision making, business planning, performance measurement, Key Performance Indicator (KPI) reporting, merchandising, prediction, automation, targeting, and optimization. As you read this book, you can learn how to lay solid foundations for building a successful digital analytics organization to make sense of and value from digital data analysis.

Figure 1.1

Figure 1.1 Humanity creates 2.4 quintillion bytes of data every day. That’s the number above: 24 billion billion bytes per day.

The volume of the data being created right now and that will be created in the future is, of course, staggering even beyond IBM’s estimates. International Data Corporation (IDC) projects that the digital universe will double in size through 2020 and reach 40 ZB (zetabytes), which means 5,247 GB for every person on Earth in 2020. The behavioral data—call it the digital behavioral universe currently being and going to be created from the clickstream and the digital footprints of every person across Earth interacting, participating, and behaving with this data—means that exponentially more behavioral data will be created on top of the predicted 40 ZB digital universe in 2020 (see Figure 1.2). Data collected about the human behavior, transactions, and metadata may be many multiples of the size of the site content. In other words, if the average size of a web page in 2013 is approximately 1.4 MB, then the behavioral and transactional data and metadata collected about visitors during their visits could be many hundred megabytes or more—especially when considering data integration from both internal and external data sources, such as advertising, audience, and Customer Relationship Management (CRM) data. The future of analytics will be enabled by innovation on top of all this big data created digitally from websites, mobile sites, social media, advertising, and any other Internet-enabled experience—from interactive TV and billboards to set-top boxes to video game consoles to Internet-enabled appliances to the mobile ecosystem and world of apps.

Figure 1.2

Figure 1.2 It is estimated that by 2020, there could be four times more digital data than all the grains of sand on Earth.

Source: IDC and Wolfram Alpha

According to the Pew Research Center’s Internet & American Life Project, during 2012 in the United States (US), more than:

  • 59 percent of people used a search engine to find information and send email.
  • 48 percent used a social network such as Facebook, LinkedIn, or Google Plus.
  • 45 percent got news online, whereas 45 percent went online just for fun and to pass the time.
  • 35 percent looked for information such as checking a hobby or interest.

Actually, the United Nations claims that more people on Earth have access to mobile phones than restrooms. Six billion of the world’s 7 billion people have access to mobile phones. Only 4.5 billion people have access to working restrooms. Meanwhile, 2.5 billion people don’t have proper sanitation. Big data created from mobile devices is more common than the global infrastructure used for human sanitation.

The volume of digital analytics data being collected about online behavior is already being tapped and mined in 2013 (see Figure 1.3); however, the promise of digital analytics remains still largely unrealized and not demystified. EMC estimates that the majority of new data is largely untagged, file-based, and unstructured data, which means little is known about it. Only 3 percent of the data being created today is useful for analyses, whereas only .05 percent of that data is actually being analyzed. Thus, 99.95 percent of useful data available today for analysis is not being analyzed (see Figure 1.4). By 2020, IDC estimates a 67 percent increase in data available for analysis.

Figure 1.3

Figure 1.3 Growth in digital data per person.

Source: IDC

Figure 1.4

Figure 1.4 The opportunity to create value exists in the 99.95 percent of data available for analysis that is not being analyzed.

Without a digital analytics organization firmly in place, a business will not be able to take advantage of the opportunity in digital data analysis that has resulted from all this data now and the huge surge of audience, media, and consumer data in the future. A business, of course, can only create competitive advantage with data if they can hire talented people who have digital analytics skills. Right now, a huge gap also exists in talented people to analyze and create insights from the data, which is an obstacle to staffing digital analytics teams. As a result of all the big data in the public and private sector, McKinsey estimates that 1,500,000 more “data-savvy” managers (who can understand and use analysis) and 140,000–190,000 new roles for analytical talent are needed to support the growth in big data in the future. The digital analyst and the digital analytics team needed to make sense of all this new data rarely exists and certainly not in sufficient quantities to create value from current and future big data. Actually, the industry faces an acute shortage and huge gap of the talent and technology needed to tag and analyze digital data even though analytical jobs are top-paying, high wage jobs.

It can take months to find a talented digital analyst and even longer to find managers and other analytical business leaders. This fact is precisely why this book can help you and your business determine how to manage and succeed with digital analytics while minding the gap in analytics talent. The need for building your own digital analytics organization is totally real, because you certainly can’t easily or quickly hire even a single analyst and rarely a talented manager and never an entire team of analysts in one shot. This book tells you what you need to know right now to get started building your own digital analytics organization and/or what you can do to take your existing digital analytics organization to the next level.

This business book is as much about building a digital analytics team as it is about building a digital analytics organization. The team exists within the organization, and the organization exists within the business. Thus, this book is about much more than digital analytics. This business book is a truly one-of-a-kind text, derived from real-world, practitioner experience that is about understanding what is truly necessary to create, manage, win, and succeed with digital analytics, while focusing on analytical ideas, methods, and frameworks for generating sustainable business and shareholder value.

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