Customer Data collection

Customer Data collection

According to Kristin Anderson & Carol Kerr 2002, Data in banking transaction system (e.g. checking, savings, credit) are often organized around "accounts", "products", "channels" or other similar transactional concepts, that limit the ability to identify unique customers and their total relationship to the bank. One of the major goals of an integrated CRM system is to consolidate these "information islands" and separate solutions, to from an open cross-bank system from which all executives, branch employee and business area departments officers, can share the same customer information. The necessary basis of data supply to an integrated banking CRM system can be obtained from:

Operation (contact) sources; Chou, Chou 2000, said that is the customer interaction touch-points (branch, personal contact, ATM, call-centre, internet banking, mobile banking, etc)

Internal sources; according to Professor Constantin Zopounidis 2002, internal sources that is the available information islands, from other bank's product-oriented systems and databases (deposits, cards, loans, investments, etc), meta-data analysis, reliable data mining results and marketing campaign response.

External sources; Professor Constantin Zopounidis 2002, also said external sources that marketing researches, infomediaries etc providing geodemographic, lifestyle and psychographic data, which can help in developing the full customer image.

Customer Data Analysis

Heygate 1998, said that deriving valuable customer insight from the data collected in a central customer warehouse requires simple or more sophisticated analysis techniques. Advanced analytics, including OLAP (Online Analytical Processing) tools and mining techniques, extract relevant patterns or trends in the data.

According to Lawer 2000, key integrated customer management insights provided by customer data analysis are customer differentiation / segmentation, distribution and concentration of customer value, share of purchase / profit, and analysis of strategies that widen / lengthen / deepen customer relationship.

Hawkes 2000, advocated customer data analysis enable the identification of customers profit and customer preferences for specific bank products and services, indicates the most appropriate channels to reach the customers, and assesses the profitability and life time value of every individual.

Furthermore, Delto 1998 said that the future behaviour of the customers can be predicted by analyzing their historical behaviour. Customer statistics, customer profit and segmentation are the main outputs of the analysis stage feeding the marketing strategy planning and execution process. Having easily available information to marketing makes the difference between a successful campaign and a failure.

Marketing Strategy and Programs

Kristin Anderson & Carol Kerr 2002 advocated captured data and results of customer analysis support marketers to refine marketing processes, messages and strategies. Lloyds TSB Bank's marketing decision makers are provided with the tools and processes to discover the true value of data, converting information into usable customer knowledge deployed to enhance marketing decision making and CRM initiatives and campaigns.

Planning, execution and monitoring marketing strategies and action programs that personalize and optimization each customer contact is the goal of marketing automation within CRM.

Bryan Foss 2003 said that, it is critical for bank CRM not only to mine their data resources to uncover patterns and insights but also to operationalise this throughout the bank activities to turn the customer knowledge into value creating action.

Merlin Stone 2003 advocated the results from marketing and CRM activities and strategies continue the process knowledge acquisition enhancing the on-going value of marketing data intelligence, closing the feed back loop. Therefore, the final part of CRM process cycle is the evaluation of the results of campaigns driven by marketing data intelligence. It is critical to measure performance and feed results back into the centre customer data warehouse, in order to deliver greater customer intelligence in the future.

The widespread use of customer relationship management (CRM) applications has provided companies with increasingly detailed insights into the profitability of their individual-level customer relationships. Historically, this information has primarily been used to identify the most profitable customers and to define ways for serving them in an optimal manner. Nowadays, however, companies like Lloyds TSB have become more aware of unprofitable clients, and the fact that these relationships can account for a substantial share of their total customer base. Therefore Lloyds TSB practises a six-step approach for dealing with such unprofitable customers, a framework the Lloyds TSB refers to as the ABCs of Unprofitable Customer Management:Avoid their acquisition in the first place,Bear in mind potential rescue operations,Catch the possibility of abandonment,Draw up a cost-benefit analysis,Ensure familiarity with your environment, andFacilitate biting the bullet.

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