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Data sources and databases for retention: An important aspect for an organization is to think what should be the reasons that enhance repeat purchase. On paper it is not possible to make definite strategies to increase customer retention. Hence, retention databases are created to have a wider range of data and information which helps in measuring and analyzing theoretical strategies for modeling customer retention behavior. Database could help in tracking and moderating all the interactions that a customer is indulged in with the supplier. However, the interaction with customers or prospect customers do not generate any revenue for the organization but it important to monitor it as it may return a potential profit in the coming future. This database is normally linked with a CRM system which helps the supplier to identify the reasons for customer defect and also to analyze the possible strategies to overcome it. Take an example of a loyal customer who spends $10,000 per annum with an airline to travel for business reasons. Now this customer is having a bad experience with the airlines due to many delayed or cancelled flights or bad service provided by flight attendants. This customer could be on an urge to defect due to the overall negative experience. |
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If the airlines does not implement strategies to save this defect or identify if the customer is vulnerable for defect then it may decrease customer retention. For overcoming this problem the airline should implement a sophisticated CRM database system to analyze the data and determine the change in buying trend of all the customers. It will also help the organization to identify the dissatisfaction sources of customers so that business tactics could be implemented to retain them efficiently. |
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Decile analysis: Decile analysis method helps in determining profitability and product sales aspects of segmented customers. This type of analysis identifies the most prominent percentage of customers who are responsible for incurring the actual profit. Deciles are nothing but the top grouping of customers which are ranked high according to the purchases they have made in a given period of time. The deciles percentage is normally 10% or 5% or even 1%, sometimes depending upon the organizational strategies. These deciles alone are responsible for 60 % to 80% of sales and profit. Hence, after determining this range of customers it becomes easy for the organization to determine which customers are profitable and which are not. After this, retaining strategies could be implemented to retain valuable customer.
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RFM analysis: RFM technique is the one of the best tool to predict future valuable customers. RFM stands for Recency Frequency Monetary value. Recency means customer purchase in recent time, Frequency means what is the frequency of purchase and Monetary value means how much the customer is ready to spend. These three aspects are determined by creating an RFM matrix and putting all analyzed data and information inside this matrix. This technique is very important to characterize customers according to their buying habits so that according strategies could be implemented to retain them. |
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Targeting defectors: It is painfull for supplier to loose loyal customers as these are the ones who are responsible for the real profit to the organization. If the organizations identify potential defectors before they defect, then retaining becomes feasible. For this, recency sales (RS) matrix is created which is a simple but powerful method to target defectors. This process includes all the customers who have at least bought products for three times. For each of these customers the following three statistics are computed:
- Total time taken by the customer since last purchase. This is called recency.
- Sales per period which the time taken by the customer since first purchase divided by the total number of times he did purchase.
- Total number of periods gone until the customer is supposed to purchase again.
According to the above strong statistics, if the customer recency is more than the first statistic, then the customer is more likely to divert. Hence after identifying this possibility of defection it becomes easy to retain the customers.
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