Traditional marketing strategies focused on the four Ps (price, product, promotion, and place) to increase market share. The main concern was to increase the volume of transactions between seller and buyer. Volume of transactions is considered a good measure of the performance of marketing strategies and tactics.
In the current era of intense competition and demanding customers, relationship marketing has attracted the expanded attention of many scholars. Marketing scholars are studying the nature and scope of relationship marketing and developing conceptualization regarding the value of cooperative and collaborative relationships between buyers and sellers as well as the relationships between different marketing actors, including suppliers, competitors, distributors and internal functions in creating and delivering customer value.
"CRM is a business strategy that goes beyond increasing transaction volume. Its objectives are to increase profitability, revenue, and customer satisfaction. To achieve CRM, a company wide set of tools, technologies, and procedures promote the relationship with the customer to increase sales". [Sweeney Group, 2000]
[...] A financial institution using its greatest asset—knowledge of the customer—can turn the customer relationship into a key competitive advantage by retaining those customers who represent the highest lifetime value and profitability. Financial institutions develop customer relationships across a broad spectrum of touch points—branches, kiosks, ATMs, Internet, electronic banking, smart cards, call centers, and phones. The shift of focus to all aspects of customer interaction has brought demand for systems that range from marketing and lead generation, to sales process automation, customer information systems, and customer service management. [...]
[...] The detailed data store (DDS) is constructed using pre-built logical and physical data models, along with pre-set metadata definitions, which help banks quickly organize customer data. Extraction, transformation and loading (ETL) logic loads and prepares customer data, based on each bank's specific requirements, for analysis in analytic data marts. These data marts provide data structures for the segmentation, cross-sell or retention analysis that will occur when queried or scheduled by the interface. To view and control the analysis that SAS performs, the customer analytics modules of SAS Banking Intelligence Solutions include customizable, Web- based interfaces that enable business users to view the most important information for particular types of analysis. [...]
[...] With over 1.3 million credit card customers and several firsts to its credit, like the first Global Credit Card, the first Photo card, SCB believes in providing incremental value to its customers and continuously increasing profitability with the customer being the center of focus. With an array of products and services that include cash management, custody, lending, foreign exchange, interest rate management and debt capital markets to corporate and credit cards, personal loans, mortgages, deposit taking activity, wealth management services to individuals and medium sized businesses and mutual funds to retail customers. [...]
[...] To determine if an organization is truly customer centric, the following three-step test can be conducted: 1. No single individual owns the customer No one is accountable for customer profitability (and non- profitability) The company makes little effort to differentiate customers and treat them differently. The SAS Banking Intelligence Solutions can enable an organization to understand the existing product centered approaches, and then assist in developing the business strategies that are needed to become a customer- centered organization. SAS provides an integrated infrastructure and proven technology base to build and maintain the CIS systems required to solve business problems. [...]
[...] In addition to lying at the heart of SCB's customer relationship management strategy SAS solutions are also used to carry out simulations that impact and help the bank to assess its overall profitability and balance its exposures across portfolios. It is critical for to stress test the portfolios and learn about the best case and worst case scenarios. While standard credit risk models provide predictive capability in the normal business environment, stress testing takes care of extreme, adverse situations allowing the management to strategize and plan for them. [...]
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