2. Explain how location-based analytics can help individual consumers.

A Life Coach in Your Pocket Most people today are finding ways to stay active and healthy. Although everyone knows it's best to follow a healthy lifestyle, people often lack the motivation needed to keep them on track. 100Plus, a start-up company, has developed a personalized, mobile prediction platform called Outside that keeps users active. The application is based on the quanti- fied self-approach, which makes use of technology to self-track the data on a person's habits, analyze it, and make personalized recommendations. 100 Plus posited that people are most likely to succeed in changing their lifestyles when they are given small, micro goals that are easier to achieve. They built Outside as a personalized product that engages people in these activities and enables them to understand the long-term impacts of short-term activities. After the user enters basic data such as gender, age, weight, height, and the location where he or she lives, a behavior profile is built and compared with data from Practice Fusion and CDC records. A life score is calculated using predictive analytics. This score gives the estimated life expectancy of the user. Once registered users can begin discovering health opportunities, which are categorized as "mis- sions" on the mobile interface. These missions are specific to the places based on the user's location. Users can track activities, complete them, and get a score that is credited back to a life score. Outside also enables its users to create diverse, personal- ized suggestions by keeping track of photographs of them doing each activity. These can be used for suggestions to others, based on their location and preferences. A leader board allows a particular user to find how other people with similar characteristics are completing their missions and inspires the cur- rent user to resort to healthier living. In that sense it also combines social media with predictive analytics. Today, most smartphones are equipped with accelerometers and gyroscopes to measure jerk, orientation, and sense motion. Many applications use this data to make the user's experience on the smartphone better. Data on accelerometer and gyro-scope readings is publicly available and can be used to classify various activities like walking, running, lying down, and climbing. Kaggle (kaggle.com), a platform that hosts competitions and research for predictive modeling and analytics, recently hosted a competition aimed at identifying muscle motions that may be used to predict the progres-sion of Parkinson's disease. Parkinson's disease is caused by a failure in the central nervous system, which leads to tremors, rigidity, slowness of move-ment, and postural instability. The objective of the competition is to best identify markers that can lead to predicting the progression of the disease. This palticular application of advanced technology and analytics is an example of how these two can come together to generate extremely useful and relevant information