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  • Digg it UP - Frequency & Monetary Analysis For Subscription Based Services

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    Below are some behavioral interview techniques that you'll find useful: 1. Be prepared for the interview by analyzing and making an educated guess as to which skills are most desired by the employer. You can study the job description of the position or go to some job boards to review requirement sections of related jobs. 2. Compile a list of skills that are relevant to the position you are applying.here. These service usage transactions are executed by millions of Customers very frequently and may be producing a huge number of service usage records on a monthly basis. Therefore, in order to execute F and M in these industries, substantial computational & storage capacity is often needed.

    Specifically, usage information should be extracted from the operational systems into a datawarehouse, which shall store the historical information on usage and periodically produce F and M scores for the Customer base and sort the Customers in F and M quintiles. Moreover, it can perform

    Secrets of Fundraising
    How many times have you seen a non profit making a heap of non profit fund and using it for some creative community work? Probably you also wanted to create a big fund like your competitor? You may also ask yourself, how on the earth did that non profit pooled so much fund. Well, it is not too difficult! This big pool of fund was possible only due to some tricks or secrets adopted by that non profit. If you want to colle
    Frequency (F) and Monetary (M) analysis, form together with Recency (R) the framework of RFM analysis. Though recency is the strongest predictor of future behavior, frequency and monetary analysis act in a complementary mode (to recency), to create a complete picture of the Customer behavior. There are many cases in which Recency analysis not coupled by Frequency & Monetary analysis, can give a misleading picture. For example, a new subscriber is very recent, but appears to have a low monetary value because she started using the service recently. The Business cannot tell, whether this new Customer will be profitable (will use the service a lot). On the other hand, an old Customer can be ranked low in R but high in F and/or M. This is probably a valuable Customer who is late in interacting with the Business. This is probably one of the candidate cases for a retention plan. In general F is a stronger predictor to M. If the service usage is producing a relatively stable monetary value, then M does not yield substantial additional insight to F. However there are exceptions. Should a Business try to offer an expensive service, the M predictor has an increased power. Those that spend a lot on a service are more likely to spend on an expensive additional service, than those who spend less. Subscription based services involve the continuous usage by a Customer, often based on a contract.

    Common examples are: bank accounts, credit cards, fixed & mobile telecommunication services, internet access service. In the case of subscription based services, the frequency of use can be easily derived, since each service usage is recorded. In the case of bank accounts or credit cards, each account or card transaction is recorded. These transactions are handled by banking systems in order to produce monthly balances or Customer invoices. In the case of fixed & mobile telecommunication services, each phone call is captured in a CDR record (call detail record) along with details about the call (calling & called number, time of day, duration, cost band). These usage records are processed by the billing systems, in order to produce Customer invoices. Therefore the banking and telecoms industries, capture rich information on service usage in order to bill Customers. Thus the information for the execution of an F and/or M analysis, is there. These service usage transactions are executed by millions of Customers very frequently and may be producing a huge number of service usage records on a monthly basis. Therefore, in order to execute F and M in these industries, substantial computational & storage capacity is often needed.

    Specifically, usage information should be extracted from the operational systems into a datawarehouse, which shall store the historical information on usage and periodically produce F and M scores for the Customer base and sort the Customers in F and M quintiles. Moreover, it can perform

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    his new Customer will be profitable (will use the service a lot). On the other hand, an old Customer can be ranked low in R but high in F and/or M. This is probably a valuable Customer who is late in interacting with the Business. This is probably one of the candidate cases for a retention plan. In general F is a stronger predictor to M. If the service usage is producing a relatively stable monetary value, then M does not yield substantial additional insight to F. However there are exceptions. Should a Business try to offer an expensive service, the M predictor has an increased power. Those that spend a lot on a service are more likely to spend on an expensive additional service, than those who spend less. Subscription based services involve the continuous usage by a Customer, often based on a contract.

    Common examples are: bank accounts, credit cards, fixed & mobile telecommunication services, internet access service. In the case of subscription based services, the frequency of use can be easily derived, since each service usage is recorded. In the case of bank accounts or credit cards, each account or card transaction is recorded. These transactions are handled by banking systems in order to produce monthly balances or Customer invoices. In the case of fixed & mobile telecommunication services, each phone call is captured in a CDR record (call detail record) along with details about the call (calling & called number, time of day, duration, cost band). These usage records are processed by the billing systems, in order to produce Customer invoices. Therefore the banking and telecoms industries, capture rich information on service usage in order to bill Customers. Thus the information for the execution of an F and/or M analysis, is there. These service usage transactions are executed by millions of Customers very frequently and may be producing a huge number of service usage records on a monthly basis. Therefore, in order to execute F and M in these industries, substantial computational & storage capacity is often needed.

    Specifically, usage information should be extracted from the operational systems into a datawarehouse, which shall store the historical information on usage and periodically produce F and M scores for the Customer base and sort the Customers in F and M quintiles. Moreover, it can perform

    Easy Steps to Designing the Perfect Fundraising Campaign
    Designing the perfect fundraising campaign is simple if you follow a few key steps to success. No matter what cause you are trying to raise money for you need a solid fundraising plan of action. This article will outline some basic steps you can follow to develop a fundraising campaign that should prove to be a huge winner.Step One - Pick a Theme for Your Fundraising CampaignBefore you can have a successful
    er. Those that spend a lot on a service are more likely to spend on an expensive additional service, than those who spend less. Subscription based services involve the continuous usage by a Customer, often based on a contract.

    Common examples are: bank accounts, credit cards, fixed & mobile telecommunication services, internet access service. In the case of subscription based services, the frequency of use can be easily derived, since each service usage is recorded. In the case of bank accounts or credit cards, each account or card transaction is recorded. These transactions are handled by banking systems in order to produce monthly balances or Customer invoices. In the case of fixed & mobile telecommunication services, each phone call is captured in a CDR record (call detail record) along with details about the call (calling & called number, time of day, duration, cost band). These usage records are processed by the billing systems, in order to produce Customer invoices. Therefore the banking and telecoms industries, capture rich information on service usage in order to bill Customers. Thus the information for the execution of an F and/or M analysis, is there. These service usage transactions are executed by millions of Customers very frequently and may be producing a huge number of service usage records on a monthly basis. Therefore, in order to execute F and M in these industries, substantial computational & storage capacity is often needed.

    Specifically, usage information should be extracted from the operational systems into a datawarehouse, which shall store the historical information on usage and periodically produce F and M scores for the Customer base and sort the Customers in F and M quintiles. Moreover, it can perform

    Self Confidence Building for Job Hunters
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    e handled by banking systems in order to produce monthly balances or Customer invoices. In the case of fixed & mobile telecommunication services, each phone call is captured in a CDR record (call detail record) along with details about the call (calling & called number, time of day, duration, cost band). These usage records are processed by the billing systems, in order to produce Customer invoices. Therefore the banking and telecoms industries, capture rich information on service usage in order to bill Customers. Thus the information for the execution of an F and/or M analysis, is there. These service usage transactions are executed by millions of Customers very frequently and may be producing a huge number of service usage records on a monthly basis. Therefore, in order to execute F and M in these industries, substantial computational & storage capacity is often needed.

    Specifically, usage information should be extracted from the operational systems into a datawarehouse, which shall store the historical information on usage and periodically produce F and M scores for the Customer base and sort the Customers in F and M quintiles. Moreover, it can perform

    Your Logo Speaks a Thousand Words
    Close your eyes and think about logos that you associate with products. All of us can name several such products in just a few seconds. The most popular logos for me are the golden arch of McDonalds and the Chevy emblem. Both have stood the test of time, allowed the company’s to change with market demands, and stay imprinted in the minds of consumers all over the world. Coming up with a logo for your business can be very
    here. These service usage transactions are executed by millions of Customers very frequently and may be producing a huge number of service usage records on a monthly basis. Therefore, in order to execute F and M in these industries, substantial computational & storage capacity is often needed.

    Specifically, usage information should be extracted from the operational systems into a datawarehouse, which shall store the historical information on usage and periodically produce F and M scores for the Customer base and sort the Customers in F and M quintiles. Moreover, it can perform time-series analysis on FM scores. Finally, in order to produce an F or M score for any Banking or Telecom Customer, the Business has to aggregate Customer behaviour from all accounts this Customer holds. Prerequisite for this, is to have a Customer-centric data structure. If the Business operates on unlinked accounts of the same real Customer, then it may be unable to carry out an accurate F or M analysis. Copyright 2006 – Kostis Panayotakis

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