Posted by David Haertzen
Welcome to the first part of an article series that will show you how to achieve profitable results using analytics. Analytics is an approach that translates data into insights and supports effective decision making through a combination of people processes and technology.
Leading organizations are using analytics to produce profitable results:
- Amazon uses analytics to suggest products to its customers using a Recommendation Engine.
- Netflix uses analytics to suggest content to its customers and to optimize logistics
- CapitalOne uses analytics to attract and retain customers through effective marketing campaigns while at the same time using analytics to detect fraud.
This series describes three types of analytics.
Descriptive Analytics:
The use of analytics methods such as data mining and statistics to better understand data. For example, clustering and affinity analysis can help retailers to better understand customers and the products they buy.
Predictive Analytics:
The use of analytic methods such as data mining and statistics to anticipate future outcomes. For example, predictive analytics may provide insights into future demand for a product or the buying habits of a customer.
Prescriptive Analytics:
The use of analytics methods such as data mining and statistics to make recommendations. For example, a recommendation engine may advise a banking service representative to offer a specific rate of interest a customer.