PREDICTIVE ANALYTICS

This course gives you an understanding of the application of predictive analytics in your field of interest /domain. As you learn the tools (machine learning, statistics e.t.c) its important to understand the application part. Whether you are a manager, newbie, enthusiast, data scientist or a machine learning professional, this course will bring more light on how you can apply predictive analytics in your domain.

PREDICTIVE CUSTOMER ANALYTICS

• Analyzing customer behaviour

• From focusing on segments to focusing on the individual customer

• This has been made possible through technological advancement & data mining tools

• At the highest level of using customer data is predicting customer behaviour

• Why? Lots of data: social media, transaction history, demographic data, e.t.c

PREDICTIVE FRAUD ANALYTICS

• Using predictive analytics in fraud detection & prevention

• Move from detecting fraud after we have already made a loss to detecting fraud behaviour and thus prevent it from happening.

• With tech, we’re trying to go into improving UX & UI such as fewer authentications but that comes with gaps for digital fraud hence the need for predictive fraud analytics.

PREDICTIVE HR ANALYTICS

• We are moving to a data-driven HR function

• Why? HR collects lots of data that can be used ( demographics, salary history, empl history, promotions data, churn data e.t.c )

• Moving from depiction HR dep as a cost function to a strategic partner in the business.

• Decisions like attracting, retaining and managing talent can be backed with data and to add more applying predictive analytics in those decisions.