PurposeThe purpose of this survey research is twofold. First, to study and report the process that is commonly used to create and maintain a competitive intelligence (CI) program in organizations. And second, to provide an analysis of several emergent text mining, web mining and visualization‐based CI tools, which are specific to collection and analysis of intelligence.Design/methodology/approachA range of recently published research literature on CI processes, applications, tools and technologies to collect and analyze competitive information within organizations is reviewed to explore their current state, issues and challenges learned from their practice.FindingsThe paper provides executive decision makers and strategic managers a better understanding of what methods are available and appropriate to the decisions they must make and the steps involved in CI undertaking.Originality/valueThe findings of this research provide the managers of CI programs a context for understanding which tools and techniques are better suited to their specific types of problems; and help them develop and evaluate a usable set of tools and best practices to apply to their industry.
Purpose -Advanced analytics-driven data analyses allow enterprises to have a complete or "360 degrees" view of their operations and customers. The insight that they gain from such analyses is then used to direct, optimize, and automate their decision making to successfully achieve their organizational goals. Data, text, and web mining technologies are some of the key contributors to making advanced analytics possible. This paper aims to investigate these three mining technologies in terms of how they are used and the issues that are related to their effective implementation and management within the broader context of predictive or advanced analytics. Design/methodology/approach -A range of recently published research literature on business intelligence (BI); predictive analytics; and data, text and web mining is reviewed to explore their current state, issues and challenges learned from their practice. Findings -The findings are reported in two parts. The first part discusses a framework for BI using the data, text, and web mining technologies for advanced analytics; and the second part identifies and discusses the opportunities and challenges the business managers dealing with these technologies face for gaining competitive advantages for their businesses. Originality/value -The study findings are intended to assist business managers to effectively understand the issues and emerging technologies behind advanced analytics implementation.
This article is directed towards information technology (IT) and marketing managers considering implementation of a customer relationship management (CRM) solution. The goal of this article is not to provide an all‐inclusive tutorial on CRM, but rather to provide a high level insight of the fundamental principles behind CRM and critical aspects of the IT development process. The article begins with an IT manager’s introduction into the basic CRM business and marketing principles. At the heart of the article is a proposed system development lifecycle that highlights the aspects unique or critical to CRM. Finally, it concludes with some final thoughts for long‐term success. After reading this article, the reader will be mindful of the major issues needed for success and be equipped to discuss primary development matters with vendors, staff and management.
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