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There are 3 types of analytics namely,
Descriptive– Analytics that helps you understand how things are functioning.
Predictive– Analytics that help you forecast future performance and results.
Prescriptive- Analytics that suggest a prescribed next step or action.
Predictive Analytics is a branch of data mining concerned with the prediction of future trends and probabilities. For example, an insurance company is likely to take into account potential driving safety predictors such as age, gender, and driving record when issuing car insurance policies.
Predictive Analytics can be a game changer and most of the companies have benefited from it. For instance, Best Buy determined 7% of its customers were responsible for 43% of its sales. The company then segmented its customers into several archetypes and redesigned stores. On the other hand, Olive Garden uses data to forecast staffing needs and food preparation requirements down to individual menu items and ingredients.
Churn Prevention and Customer Lifetime Value: When customers stop using your products or services, or if they begin using products of your competitors, this is rightly called as Churn or Attrition. Some of the various topics discussed in the webinar about churn prevention are as follows: