Predictive Analysis Of Predictive Analysis, An Integral Part Of Any Business

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Predictive Analysis is an integral part of any business – with its major role in all dimensions of the business decision making processes. Prediction helps in understanding the customer better and managing customer relationships in an efficient way. Understanding the customer is the most important part of the business process as it impacts the potential growth in business and the success of any business decision, be it a drastic or a minor change.
For instance, a product launch can be strategically planned using predictive analytics, if we know our customers better. The sales and the marketing teams work closely with analysts and data scientists to understand how well the historical data can predict the customer potential and possible
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These models are often used to understand customer behaviors in detail.
Businesses want to understand what kind of products the customers are likely to buy, who are the loyal customers who keep coming back for re-purchasing similar or other products, what other products are our loyal customers interested in, what are the potential marketing campaigns which could help us attract customers who are similar to the existing high value customers, and so on.
A few applications of Predictive Models:
The most important customer analytic areas and the state of the art methodologies are as follows.
(1) Customer attrition analysis
Predicting customer attrition is one of the major areas in customer analytics. Businesses have the need to continuously monitor and understand customer behavior and their expectations, in order to have an edge over the competitors. It makes no practical sense to not know whether the customers are staying with the company or do they have a risk of attrition, due to various controllable and uncontrollable factors. It is extremely essential for any business to retain the existing customers and resolving any pressing issues in a timely manner. Retaining a customer is as important, if not more, as attracting new customers.
a. Attrition Risk Modeling:
This is performed to predict the attrition risk for different customers/customer segments. The customers with high risk of attrition are identified using various factors like their
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