Introduction:

The role of the analyst is beyond running predictive models on a given data. Analyst in that case are like researchers, who need to formulate research question, define methodology (passive data analysis or running experiments a.k.a. focus groups studies), conduct data acquisition, analyze data, and then produce the recommendations.

Directions:

In business or research literature find examples of one successfully and one failed new product launch from last 10 years. For example, Google successfully launched Google Echo, and the same company failed launching of Google Glass.

In your initial post discuss how predictive analytics potentially could play a role in successful launch in those two examples. and what analytics could help to avoid failure. For one of the examples you may use a real analytics cases (if you will be able to find them). For at least one example (or both) come up with the concept of a predictive analytics study, that may benefit the case. Be very specific by explaining what data can be used, where or how it can be obtained, what research question(s) can be used, and what predictive analytics methods can provide answers to those questions. For example, to predict how to launch Google Glass successfully, Google may collect data on the smartphone app use, identify clusters of users who are often try new apps, and then link it to the problem domains that may need hands free interfaces by building a predictive (e.g. decision tree) model of using certain apps while walking or driving with an extensive screen use.

In your responses elaborate on the potential data analytics and provide at one additional suggestions to use other data and other models for the cases provided by at least two students student.