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Predictive Analytics Attains Strategic Objectives across Business Functions - Objective-Growth



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Another reason for the requirement of predictive analytics is growth.


Predictive Targeting

Grow - Retain Customers and Increase of Sale

Some of the lucky business enjoys the facility of growth where there exist many one-time customers. These companies have large number of customers who never returns and thus the companies are highly benefitted from this.


The question is that how can a company achieve the potentiality of attracting one-time customers. An approach can be pursued in this regard, the approach involves improvement in operations of business, which includes better products, more personalized service etc. So for a significant growth, one needs to make a significant investment in the above mentioned areas. However is there any way to get more or less for a given steady flow of one-time customer.


Predictive Modeling

The answer to the above question is yes, there is a way for capturing all these prospects with small increase in expenses. This can be done by predicting those first time customers who won't return and the customers who may leave with heavy discount are targeted. Like this one can make a progress from the first date to a long-term relationship.


By means of predictive targeting the challenge can be met. There would be a sacrifice in terms of revenue if we do not know ahead of time that which new customers will stay or not. That is to say a problem arises when a rebate is offered to every new customer in their second purchase.


The problem can be solved with the help of predictive modeling. It gives us idea about the new customers that whether they will return or not i.e., the one-timers. The past sales records of a company are collected to create the predictive model, and this is done through the method of data mining. From the predictive model, a predictive score is generated for each new customer.


So, one can target the new customers who will not stay and also the ones who will stay. The numbers works out well enough as one don't waste retention offer for new customers who will return. Risk is not taken with immediate term profits and growth-rate and medium term profits have high potentiality.

Retention Campaigns to Increase Profits

To make the numbers game work predictive analytics plays a very significant role. Without knowing which customer are likely to return one cannot afford for deploying a rebate. However a question arise that how is prediction possible here.


Taking the help of predictive modeling the sales and records of customers can be leveraged, and in this way a distinction can be made between one-time and repeat customers. The core methodology in predictive analytics helps to determine the attributes of a new customer and also a combination of everything observed.


Benefits of Retaining New Customers

It is not a new idea of predicatively targeting retention to the customers at risk. However there remain advantages to target new customers for a given high rate of one-time customers.


  • More Opportunities

  • Repeat customers can be presented with the help of high bandwidth of the one-time new customers. To reduce frequency of faulty tenured customers one uses the wealth of ROI opportunity.


  • More rows of data

  • Corporate experience is represented in terms of data where each row presents each customer. The records include the history of customers i.e. they left or stayed and this is used for creation of predictive models. The benefits of predictive retention can be achieved by retaining new customers.


  • Higher ROI

  • According to marketing retention is less expensive as compared to acquisition. That is to say growth can be raised by retaining the existing customers at lower cost instead of acquiring new customers.


  • More Loyal Customers

  • Instead of acquisition of new customers one can increase the number of long term repeat customers through retention. That is to say loyal customers should be increased. There are many advantages regarding a loyal customer, which includes increase of frequent purchase, higher profits, lower sensitivity etc.


  • More columns of data

  • There exists more information regarding the existing customers who are targeted for retention rather than who are targeted for acquisition. One can make idea about the existing customers, for example billing information, their profiles, buying behavior etc. can be known. All these matters in a column of the database are important to develop an effective and powerful predictive model.


Higher ROI for predictive analytics can be achieved if business goals are well defined. A retailer for example has a goal to increase sales. When goal becomes more specific the sale strategies tend to become more measurable and distinguishable.


Thus predictive analytics plays a vital role in the growth of a company by means of retaining customers and increasing sales.


Methodology

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