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Customer Relationship Management




                    Notes          By the way, using  customer behaviour to predict  the relative Lifetime Value  and loyalty of
                                   customers is a 40 year old technique still used by mail order and TV shopping companies today.
                                   Large sites with CRM analytics are using this technique, known as RFM, to predict customer
                                   value and response to promotions.

                                     


                                     Caselet     Calculating the Customer Lifetime Value: SECOR

                                          ECOR assisted a large European mobile telephony operator with the definition and
                                          project management  of a  Customer Lifetime Value (CLV) strategic solution. The
                                     Sobjective was to establish a company-wide system for CLV calculation and analysis
                                     utilizing all relevant revenues and costs from across the organization. The system was
                                     intended to underpin the company’s CRM strategy providing the foundation for activities
                                     such as:

                                         Ad-hoc segmentation and data analysis for data driven marketing
                                         Automation of decisions against customer requests such as handset upgrades
                                         Targeted retention activities and decisions to ensure retention effort is aligned to
                                          CLV
                                         Identification of customers for cross-selling and up-selling
                                         Development of product portfolios aligned to high CLV customers
                                         Alignment of customers to appropriate channels by CLV
                                     The benefits of the project were identified as being in excess of £3m!

                                   Source:  http://searchcrm.techtarget.com/feature/CRM-case-studies
                                   Let’s say you’re not satisfied with using relative Lifetime value as a proxy for absolute Lifetime
                                   Value. You’re a glutton for punishment, or your boss wants a hard number. No problem. Here
                                   are a few issues we need to put on the table when discussing the calculation of LTV:
                                   1.  If you haven’t been in business long enough to know the Lifetime of a customer, just put
                                       a stake in the ground by looking for defected best customers. Look at customers who have
                                       spent or visited the most with you and then of these, look at the ones who haven’t made a
                                       purchase or visit in some time (6–9 months, for example). In all likelihood, the last purchase
                                       or visit was the end of the Lifecycle when considering best customers who have stopped
                                       buying or visiting. When best customers stop, they’re usually all done. Then look at first
                                       purchase or visit date for these customers, calculate your Lifetime, and use this length of
                                       time as the “standard” customer LifeTime, realizing  the average lifetime is  probably
                                       much shorter.
                                   2.  Frequently, a customer will defect for a few years and then come back. This is cool, and
                                       normal. Their life changed somehow and they left, and now they need you again. Most
                                       offline marketers would call a  customer who has had zero activity  for over 2 years a
                                       defected customer. Online, it’s more like 6 months for the average customer, unless you
                                       are in a classic seasonal business. If the customer starts up again, they would be a “new
                                       customer”, for marketing and modelling purposes. They will more likely behave like a
                                       new customer than a  current customer.  The behaviour  will ramp  and fall  off all over
                                       again, just like it did in their previous Lifecycle with your business.







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