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Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. Marketing provides services to satisfy customers.
The business needs analysis contributes tremendously to the re-engineering effort by helping the BPR team to prioritize and determine where it should focus its improvements efforts. [21] The business needs analysis also helps in relating the BPR project goals back to key business objectives and the overall strategic direction for the organization.
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Six Sigma (6σ) is a set of techniques and tools for process improvement.It was introduced by American engineer Bill Smith while working at Motorola in 1986. [1] [2]Six Sigma strategies seek to improve manufacturing quality by identifying and removing the causes of defects and minimizing variability in manufacturing and business processes.
These analytics help improve customer service by finding small problems which can be solved, perhaps by marketing to different parts of a consumer audience differently. [20] For example, through the analysis of a customer base's buying behavior, a company might see that this customer base has not been buying a lot of products recently.
Business intelligence (BI) consists of strategies, methodologies, and technologies used by enterprises for data analysis and management of business information. [1] Common functions of BI technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text ...
Workforce management (WFM) is an institutional process that maximizes performance levels and competency for an organization.The process includes all the activities needed to maintain a productive workforce, such as field service management, human resource management, performance and training management, data collection, recruiting, budgeting, forecasting, scheduling and analytics.
The difficulty in ensuring data quality is integrating and reconciling data across different systems, and then deciding what subsets of data to make available. [ 3 ] Previously, analytics was considered a type of after-the-fact method of forecasting consumer behavior by examining the number of units sold in the last quarter or the last year.
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