We are sorry but we currently do not allow our content to be printed
This option will become available at a later date

Special: Big Data and Customer Analytics

Customer analytics pay off, driving top-line growth by bringing science to the art of marketing

Businesses today have a plethora of customer data available from an increasing number of sources. While most organizations certainly appreciate the potential benefits such data can reap, many face difficulties effectively turning information into actionable insights. However, an effective customer analytics strategy can help drive top-line growth, avoid unnecessary costs and increase customer satisfaction. To help organizations in their pursuit for deeper customer insight, we have identified four stages of organizational capabilities and associated customer analytics strategies.

Every day consumers and enterprises create 2.5 quintillion bytes of data. In fact, 90 percent of data in the world today has been created in the last two years. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos posted online, point of sale (POS) data, transaction records of online purchases, e-mail content and cell phone GPS signals – just to name a few. Thanks to affordable Internet-enabled devices and cloud services, the world has gone from connected to hyperconnected, generating more customer-related data than ever and doing it in shorter and shorter time frames.

Today, most business executives understand the value of collecting customer-related data. However, many struggle with the challenges of leveraging the insights from this data to create smart, relevant and proactive pathways back to the customer. They are unsure how to effectively use their customer data to make decisions that turn insights into sales growth. Business analytics makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling and fact-based management to drive smarter decision making in today's complex environments.

In this research paper, we combine expertise gained through years of experience with quantified research and case studies to provide our point of view on some of the more effective customer analytics strategies. Organizations can deploy these strategies as a competitive differentiator and as an engine for sales growth.

For this perspective, we employ a conceptual framework that describes four stages of organizational capabilities and how they are enabled by four customer analytics strategies (see Sidebar: Navigating the stages of the analytics framework).