¶ … data mining?
The foundational elements of data mining are multidisciplinary in nature, encompassing analytics, computer science, database systems integration and management, statistics and artificial intelligence. Often these technologies are used to create a single system of record used for analysis and advanced queries by the enterprises who build them. Data mining is often included in business intelligence (BI) suites and the analytics layer of an enterprise-wide computing system, as each application needs to gain access to the metrics and key performance indicators (KPIs) (Peacock, 1998). The use of data mining has become more pervasive in marketing, sales and service as organizations strive to gain insights from the terabytes of data they have accumulated over years and in some cases decades of operation. Data mining can provide marketers with greater insights into the preferences, needs and wants of customers, in addition to potential new product or service ideas based on a careful analysis of the accumulated data on customer bases (Koh, Kin, 2002).
Data mining also creates a highly effective platform for completing simulations of potential pricing and service strategies, and can serve as a very effective source of product line enhancement ideas (Peacock, 1998). The potential also exists to use data mining as a means to create a highly effective segmentation model based on previous customer purchases and the patterns of services purchased as well. Data mining's greatest potential however is being seen in the precise aligning of pricing and the potential to generate greater profits over time.
2. What is the Value Map?
The foundational elements of a value map is the charting of price and benefits of a given product. This two-dimensional grid is often...
Conger, 2009). Recommendations for Organizations The many factors of data mining and their use for profiling customers and their needs also create opportunities for organizations to build greater levels of trust with their customers as well. And trust is the greatest asset any marketer can have today. The following are a series of recommendations for how organizations can address demographic influences that impact their marketing strategies in light of concerns surrounding
Customer centricity then can also have a significant impact on the perspective an organization has of its market and the opportunities inherent within it and other, tangential and territory market areas as well. This aspect of blue ocean strategies being driven by customer's perspectives, preferences, unmet needs and wants further underscores its inherent value and also its usefulness from a strategy perspective. The ability to find uncontested markets, which
This research proposal looks to determine how the selection of a given cloud platform impacts user intention, satisfaction and long-term adoption. In order to evaluate the contributions of each of these platforms, each is briefly reviewed within the context of this literature review. First, the most commonly used one in start-up cloud database service providers, Amazon Web Services (AWS), is analyzed. AWS is comprised of the following components: Amazon DynamoDB
trouble with Philadelphia's water billing system is a technical problem or a people problem? Why? From the case study it is at first difficult to separate the two and decide whether the issue rests mainly with the people involved or the system. The people who developed the system did not anticipate using it for such a broad application, so they are responsible for not preparing the system for such an
The reward for the effort of learning is access to a vocabulary that is shared by a very large population across all industries globally" (p. 214). Moreover, according to Bell, because UML is a language rather than a methodology, practitioners who are familiar with UML can join a project at any point from anywhere in the world and become productive right away. Therefore, Web applications that are built using
This is one of the greatest limitations of this technology. A second major disadvantage of RDBMS-based systems is their lack of support for image- and spatial-based databases that include Computer-Aided Design (CAD) drawings, 3D rendering and model-based data. Their table-based structure is inefficient in defining the attributes of these data types and lacks the necessary data tagging and data types to manage imaging and CAD-based design files and data
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