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Predictive Analytics

by | Oct 24, 2013 | Blog | 0 comments

Usually predictive analytics provides a tool or predictive model that outputs a score(propensity of the event) that can be used for targeted campaign across the processes like collection, recovery, customer acquisition, cross sell/up sell, customer retention and churn prevention etc.

Predictive Analytics

Predictive Analytics

Predictive analytics is a proven technology and being used by industry successfully for decades. Predictive analytics helps the industry to make smarter decisions. It increases the precision, consistency and speed of the decisions about customers and their prospects.

Some of the examples of usages of predictive analytics in industry are as follows

  • Telecom:  A large US based Telecom Company used our predictive model to identify the customers who are more likely to not clear their dues and eventually get terminated in next six month. They used the scores to design their customer reach program like sending emails to self cure customers.
  • Banking: A leading Indian bank used predictive analytics to cross sell their LAP(Loan against property) to their Current account and saving account portfolio.
  • Retail:  A London based retailer used predictive analytics to forecast their weekly sales product wise and used that information for inventory management.
  • Insurance:  We helped an insurance company to identify the customers who are more likely to churn or not likely to pay premium after minimum lock in period. We used regression analysis (Logistic Model) to solve this problem.
  • Predictive analytics helps to improve every aspect of the business decision. It makes the business decision agile, consistent, precise and very cost effective. Some of the major values that application of Predictive analytics brings to your business are as follows:

    Know your customers

  • Development of Decision system that is scientific and backed by Data
  • Reduction of cost and increase in profit
  • Consistency and Competitiveness in business decision
  • Ability to take complex decision at run time
  • Broadly analytical techniques that are used in predictive analytics can be divided into regression techniques and machine learning. Regression techniques includes linear regression, logistics regression , Discrete choice models, probit regression, time series models , survival or duration analysis etc. Machine learning includes neural network, MLP(multi layer perceptrons, Radial based functions, Naïve bayes etc.

    ScoreData Corporation is a pure play Predictive analytics company focusing entirely on predictive analytics. We use advanced analytical techniques to solve complex business problem. We take pride in providing analytically rigorous solutions in very cost effective manner.