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Why Do Brands Need Predictive Modeling?

Why do brands need Predictive Modeling?

Predictive Modeling refers to a process wherein a statistical Model is created or used so as to forecast the likelihood of an outcome. The model is chosen such that when fed with a certain amount of input data, it tries to predict the probability of a result. There are various existing models that organizations may choose from. It is essential for brands to use Predictive Modeling in order to aid the calculation of an outcome of certain campaigns or plans. Market data is collected for these relevant predictors, models are created and validated as additional data becomes available.

Risk management and Pricing: With the help of data mining tools, predictive modeling can aid in automatically foreseeing risk as well as pricing at an individual level. Brands require risk management so as predict any uncertainty in a program that is scheduled to be deployed in the future.

Direct marketing: The main reason why brands need predictive models other than to calculate the outcome of a campaign is so that they can foresee prospective customers who are likely to buy their products. It helps in chalking out customer data and segmenting them based on certain characteristics.

Customer retention: Through predictive model and analytics, it makes it easier for brands to find out the probability of a consumer switching to a competitor. Finding out such relevant data also aids in taking corrective action in order to retain customers.

Staffing: Other than calculating the outcome of a specific program, predictive modeling should be implemented by brands in order to gauge the staffing requirements on changing demands for products and services.

Cross selling opportunities: Rather than creating clear-cut product lines and selling them via traditional channels, markets or traders, predictive modeling helps identify opportunities to cross sell.

Helps make decisions and RoI: In order for marketers to make an informed, unbiased decision, these models are of great help as they provide the exact outcome based on the kind of historical data that the model is fed with. While a lot of marketers go with their gut feeling to make decisions that affect future results, predictive models help in providing facts and figures so as to help, not only to build a brand, but also to sustain it in the long run to yield ample returns.

It is essential for brands to use Predictive Modeling in order to aid the calculation of an outcome of certain campaigns or plans. Looking for user friendly outputs which can be played around with must be the aim of such a model. Predictive modeling is powerful, has a lot of potential and if used correctly, it can produce great results.

This post first appeared on Predictive Modeling, please read the originial post: here

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Why Do Brands Need Predictive Modeling?


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