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Customer CapitalThe value of an organization’s relationships with its customers. Often, it is these relationships that fetch business, not just the quality of the products or services offered by the company. This is also the reason why there is so much emphasis on Customer Relationship Management. (See also: Customer Knowledge) Customer KnowledgeCustomer knowledge consists of the insights collected while dealing with customers. Customer knowledge is useful in understanding customer needs, including those which are unmet and unarticulated. Various sources of customer knowledge can be integrated and analyzed both to serve customers better and to generate ideas for new products and services. Customer knowledge facilitates customer relationship management (CRM). Many IT services companies offer CRM solutions that help their clients in getting 360 degree views of the customers. Information technology (IT) can support ongoing efforts to improve customer identification, conversion, acquisition and retention and to deliver personalized services. IT facilitates high levels of personalization and decision support in a cost effective manner. But customer knowledge initiatives should not be driven by IT alone. Close personal interaction with customers is needed to get deep insights about what customers are really looking for. This is because customers sometimes find it difficult to articulate their needs. Customer knowledge should lead to the following44: Customer Satisfaction: This can be measured as the percentage of customers completely satisfied with existing products / services. Customer Retention: The metric here can be the percentage of customers still with the company compared with the previous year. Product / Service Quality: This can be tracked by computing the percentage of customers complaining about product quality. Average duration of Customer Relationship: This can be measured as the number of months for which an average relationship with customers continues. Repeat Orders: The metric here can be the ratio of volume of business generated by repeat orders to the total business. Growth in Sales of Key Accounts: Both sales and profit growth can be tracked. D
DataA set of particular and objective facts about an event or a transaction; for example, the number of customers arriving at a restaurant every hour. Or the total amount of purchases made at a departmental store during the day. We often have a very simplistic notion that the more the data we have, the better we are equipped to take the right decision. But data collection is the easier part. Indeed, too much data may be collected and distract our attention. And data by itself does not have any meaning. Moreover data can be cumbersome and voluminous to handle. Unless data is processed into information and subsequently converted into knowledge, it adds little value to the business. Data MartsScaled down version of a data warehouse that is tailored to contain information for use by a department. Data marts are also known as local data warehouses. A data mart has the same characteristics as a data warehouse, but is usually smaller and is focused on the data for one division or one workgroup within an enterprise. Whereas a data warehouse combines databases across an entire enterprise, data marts focus on a particular subject or department. For example, marketing data marts may be constructed to capture customer related information. There are three different ways of building data marts: The data warehouse can be first created, combining the information from the various databases which already exist. Specialized data marts can then created not only to serve the unique needs of different departments but also to allow the querying load to be spread among several different computers. This can smoothen network traffic. The data mart can be viewed as the prototype of a data warehouse. The division or group that would most benefit from data-based knowledge is first selected. A data mart is built with that group’s data. Other information is added to the data mart over time till it becomes a data warehouse. Data marts can be built independent of a data warehouse. It is usually quicker and cheaper to build a separate data mart instead of building an enterprise-wide data warehouse and then data marts from within it. The problem here is that the company’s data will not be integrated. There will quite likely be some duplication and inconsistency of data. If there are too many data marts, complexity and costs will increase. (See also: Data Warehousing) Data MiningThe process of identifying commercially useful patterns or relationships in databases through the use of information technology. Analyzing data involves the recognition of significant patterns. Human analysts can see patterns in small data sets. But large amounts of data need specialized mining tools. These tools can perform high level analyses of patterns and trends but also drill down to provide more detail when needed. Data mining can be used to identify the attributes that characterize the customers who account for a bulk of a business. Thus, a consumer goods company may track hundreds of variables about each consumer segment, with scores of possible relationships among the variables. Similarly, data mining software can help retail companies find customers with common interests. Data mining is often misused to describe software that presents data in new ways. The focus of data mining is not to change the presentation of the data, but discover previously unknown relationships among the data. (See also: Data Warehousing) Directory: books books -> The English Arrive in America books -> Active Vocabulary books -> Books we finished XIV books -> The theology of the balaam oracles: a pagan diviner and the word of god books -> The rhetoric of the father books -> Sra: Imagine It!, Themes, Taking a Stand, Ancient Civilizations Ecology, Great Expectations, Earth in Action, Art and Impact, Level 6 books -> You Can If You Try Unit 7 Nonfiction books -> The tregenza family books -> Unconditional hatred Download 0.91 Mb. Share with your friends:
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