Teradata Magazine Online

Stephen Brobst, CTO of Teradata, discusses how Consumer Intelligence benefits the bottom line.

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Feature

Consumer Intelligence

The future of analytics.

by Stephen Brobst

IDC estimates that by 2013, 2.2 billion people worldwide will use the Internet, and 1 billion mobile devices will be used for Internet access. Using smartphones and other mobile devices, consumers have access to anybody and anything on the Internet at all times—no matter where they are. Mobile is becoming the new normal.

Consumer Access Is the Future

The proliferation of mobile devices and a new breed of consumers are driving a revo­lution in requirements for pervasive access to data warehouse content. Historically, data warehouses have been constructed to provide intelligence to business knowledge workers within large enterprises. A new breed of consumers is emerging with a do-it-yourself mindset related to technology and unprecedented sophistication in using data for personal decisions. This change in consumer behavior is creating demand for Consumer Intelligence capability in which direct access to data is required for personal decision making.

This shift toward Consumer Intelligence is the next step in the evolution of pervasive business intelligence (BI). In the early days, data warehouses were built for strategic decision making in the corporate ivory tower. Typical users were in the areas of strategy, finance, marketing and risk management. As data warehouses became “activated” to support operational BI, large numbers of users were added from the front-line support areas of the business. The next step was to push further out into the value chain, across organizational boundaries, and provide data warehouse access to key suppliers and distributors.

Providing data warehouse access to consumers is the natural next step in this evolution of pervasive BI. With generation Y and Z consumers having grown up with technology at their fingertips and instant access to information, it is not surpris­ing that they would demand intelligence services from the enterprises and govern­ment agencies with which they interact. The proliferation of mobile devices fuels these demands further. It is estimated that more than 30 million American adults have used a mobile device to access healthcare data of some kind. Mobile health applications use data and analytics to promote healthier lifestyles by encouraging better eating habits, exercise and adherence to medical advice from physicians.

Cross-Industry Applications

Providing consumers with access to data via enterprise and data.gov initiatives will create opportunities for numerous value-added services across a range of industries:

FINANCIAL SERVICES. Not surprisingly, financial services companies have already started ramp­ing up in the area of Consumer Intelligence. Leading banks, such as Wells Fargo (in the United States), Discover Financial Services (in the United States) and Lloyds Banking Group (in the United Kingdom), have provided capabili­ties on their Internet banking sites to allow retail banking customers to analyze their own data for personal decision support purposes. These sites pro­vide secure access to historical and detailed data, along with analytic applications, to make personal financial planning available 24x7. This is very different from traditional banking, wherein a retail customer would be provided such services via a personal financial consultant in a bank branch dur­ing banking hours.

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HEALTHCARE. Sensor technology will enable consumers to have visibility into rich and diverse data about many aspects of their lives. For example, health­care sensors designed to collect vital signs from the human body, along with next-generation mobile health, or mHealth, applications, will provide consumers with better monitoring of their health status and actions required to avoid critical care situations.

ENERGY. Smart metering on residen­tial homes in regions such as Southern California and Boulder, Colorado, has begun in vigor. These sensor devices will track energy consumption at a detailed level for each consumer household. Moreover, analytic models have been built that allow recognizing the energy consumption “sig­nals” associated with most major household appliances. Providers, such as Southern California Edison, have plans to provide (secure) access to this information directly to consumers over the Internet. Analytic application possibilities involve what-if scenarios to explore poten­tial cost savings associated with options for changing consumption patterns. Visibility into the outcomes associated with green behaviors will encourage replacing older, less efficient appliances with newer, more efficient ones, running air conditioning at less aggressive cooling levels and during fewer hours of the day, and other behav­iors consistent with energy conserva­tion and lower utility bills. The ability to use this data for personal energy consumption planning is yet another example of Consumer Intelligence.

TRANSPORTATION. Commercial vehicles are nearly all configured with sensor devices, and consumer vehicles are likely to come standard with such apparatuses in the near future. The data collected by sensors will allow monitoring and analysis of driving habits so that consum­ers will be able to improve fuel efficiency, safety and even reduce driving insurance costs as a reward for good driving habits.

The level of trans­parency provided to consumers about their actual behaviors (which are often different from perception) via Consumer Intelligence will be enlightening. Access to personal data with well-designed Consumer Intelligence applications has the power to positively influence actions taken in our everyday lives that affect our health, driving, energy consumption, financial management, retail buying patterns and much more. Access to information will evolve to proactive alerting services—such as the cost and usage alerts envisioned by Southern California Edison.

System Requirements

Initially, many of these Consumer Intelligence capabilities will be deployed using browser-based Web and mobile Web imple­mentations. For greater ease of use, these implementations will likely evolve to mobile apps as well. Consumer Intelligence that is used relatively infrequently is probably best implemented using mobile Web technology. For Consumer Intelligence that becomes part of daily life, the mobile app paradigm will be superior.

The service level requirements for a data warehouse to support Consumer Intelligence will be very high. The number of concurrent users issuing queries against a data warehouse for Consumer Intelligence is multiple orders of magnitude larger than for traditional BI. Moreover, the response-time expecta­tions for impatient consumers will be extreme. Availability and data freshness requirements for Consumer Intelligence applications of the data warehouse will also escalate.

Deployment of Consumer Intelligence applications will change the way informa­tion is delivered and used from data ware­houses. The value proposition for both businesses and consumers—across a range of industries—has been demonstrated to be very high. Consumer Intelligence will facilitate more informed decisions for consumers and better retention of these consumers for the businesses that provide these capabilities. The implementation of Consumer Intelligence will demand never-seen-before levels of scalability from the data warehouse infrastructure: tens of millions of queries per day and sub-second or small-single-digit-second response-time expectations. Moreover, service levels for high availability and data freshness will also escalate with this emerging trend.

Stephen Brobst is the chief technology officer for Teradata.