Running head: MARKETING MANAGEMENT GROUP PROJECT

Nest Learning Thermostat
Liberty University
BUSI 520-B06
October 2012

MMGP: Background Information
Thermostats detect and control temperature changes for the purpose of maintaining the temperature in an enclosed area and generating electrical signals when the temperature exceeds or falls below the desired value (Encyclopedia Britannica, 2012). The U.S. Department of Energy and the Lawrence Berkeley National Lab research, proves that the energy bill for a single family home is estimated at $2,200 annually in which heating and cooling accounts for half of the bill. In an effort to cut energy consumption costs, programmable thermostats were developed in the 1970’s. Since their development, thermostats have proven to be complicated to use and program (Close-Up Media, 2011).
Nest Laboratories, a company based in Palo Alto, California founded by Tony Faddell and Matt Rogers, with the backing of several investors such as, Generation Investment Management, Google Ventures, Intertrust, Kleiner Perkins Caufield & Byers, Lightspeed Venture Partners, and Shasta Ventures, set out to apply advancements in technology to reinvent the thermostat. The team at Nest addressed the programming problem through a combination of sensors, algorithms, machine learning, and cloud computing (Close-up Media, 2011). They came up with a thermostat capable of learning a household’s daily schedule, and personal heating and cooling preferences; naming it the Nest Learning Thermostat. After just one week of consistent use, the Nest Learning Thermostat “knows” when to save energy, and when the house is empty. The thermostat uses six sensors to detect when the family is home, and when the home should be heated or cooled (Close-up Media, 2011). This “high tech” gadget operates with the same interface as the original iPod,