Marketing decision support system

Last updated

A marketing decision support system (sometimes abbreviated MKDSS) is a decision support system for marketing activity. The system is used to help businesses explore different scenarios by manipulating already collected data from past events. It consists of information technology, marketing data, systems tools, and modeling capabilities that enable it to provide predicted outcomes from different scenarios and marketing strategies. [1] [2] MKDSS assists decision makers in different scenarios and can be a very helpful tool for a business to take over their competitors. [3]

Contents

Example

A MKDSS is used to support the software vendors’ planning strategy for marketing products. It can help to identify advantageous levels of pricing, advertising spending, and advertising copy for the firm’s products. [4] This helps determine the firm's marketing mix for product software.

Decision support systems

The concepts involved in decision support systems were first expressed in the early 1970s by Scott Morton. [5] [6] These systems are used to help solve complex problems by using computer technology and can help businesses with decision making. DSS has progressed since it was first developed in the 70's. The main areas of research that DDS has developed from are theoretical and technological.

There are three types of DSS available: 1. available as a software application, 2. bespoke and 3. user-developed.

DSS has many tools [7] that contain different functions such as; sophisticated database management capabilities with access to internal and external data. information, and knowledge; powerful modeling functions accessed by a model management system; and powerful, yet simple user interface designs that enable interactive queries, reporting, and graphing functions.

Although DSS have many different functions, they are very user friendly and easy to use, flexible and have strong graphic capabilities. [8]

Use of decision support systems

DSS are used mainly used before a company invests their money into something. One of DSS's biggest benefits is its ability to predict the outcome of different scenarios, it can help businesses to save money by preventing failures and put them towards a better cause.[ citation needed ]

Decision support systems can help businesses to save time [9] as well. They would not have to waste even a minute in planning and trying to create something which is not going to succeed.

Satisfaction

MDSS would totally satisfy marketing businesses as it would improve the effectiveness of decision making, reduce costs by eliminating completely unsuitable and useless decisions.

DSS helps and improves the performance of decision makers by using a computer system. [10]

One of the most important and useful things about a system like this is that it lets the business look forward instead of being stuck and trying to examine the past to get answers to complex questions. [11]

Related Research Articles

Customer relationship management (CRM) is a process in which a business or other organization administers its interactions with customers, typically using data analysis to study large amounts of information.

<span class="mw-page-title-main">Enterprise resource planning</span> Corporate task of optimizing the existing resources in a company

Enterprise resource planning (ERP) is the integrated management of main business processes, often in real-time and mediated by software and technology. ERP is usually referred to as a category of business management software—typically a suite of integrated applications—that an organization can use to collect, store, manage and interpret data from many business activities. ERP systems can be local-based or cloud-based. Cloud-based applications have grown in recent years due to information being readily available from any location with Internet access. Traditional on-premises ERP systems are now considered legacy technology.

<span class="mw-page-title-main">Knowledge management</span> Process of creating, sharing, using and managing the knowledge and information of an organization

Knowledge management (KM) is the collection of methods relating to creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieve organizational objectives by making the best use of knowledge.

Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis and management of business information. Common functions of business intelligence technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics.

A management information system (MIS) is an information system used for decision-making, and for the coordination, control, analysis, and visualization of information in an organization. The study of the management information systems involves people, processes and technology in an organizational context.

Marketing strategy is an organization's promotional efforts to allocate its resources across a wide range of platforms, channels to increase its sales and achieve sustainable competitive advantage within its corresponding market.

<span class="mw-page-title-main">Business performance management</span> Processes to bring output into alignment with goals

Business performance management (BPM), also known as corporate performance management (CPM) enterprise performance management (EPM), organizational performance management, or simply performance management are a set of management and analytic processes that ensure activities and outputs meet an organization's goals in an effective and efficient manner. Business performance management is contained within approaches to business process management.

<span class="mw-page-title-main">Decision support system</span> Information system that supports business or organizational decision-making activities

A decision support system (DSS) is an information system that supports business or organizational decision-making activities. DSSs serve the management, operations and planning levels of an organization and help people make decisions about problems that may be rapidly changing and not easily specified in advance—i.e. unstructured and semi-structured decision problems. Decision support systems can be either fully computerized or human-powered, or a combination of both.

Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns toward effective decision-making. It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance.

<span class="mw-page-title-main">Computer-aided software engineering</span> Software Quality Engineering Practices

Computer-aided software engineering (CASE) was a domain of software tools used to design and implement applications. CASE tools were similar to and were partly inspired by Computer-Aided Design (CAD) tools used for designing hardware products. CASE tools were intended to help develop high-quality, defect-free, and maintainable software. CASE software was often associated with methods for the development of information systems together with automated tools that could be used in the software development process.

An executive information system (EIS), also known as an executive support system (ESS), is a type of management support system that facilitates and supports senior executive information and decision-making needs. It provides easy access to internal and external information relevant to organizational goals. It is commonly considered a specialized form of decision support system (DSS).

<span class="mw-page-title-main">Business analyst</span> Person who analyses and documents a business

A business analyst (BA) is a person who processes, interprets and documents business processes, products, services and software through analysis of data. The role of a business analyst is to ensure business efficiency increases through their knowledge of both IT and business function.

<span class="mw-page-title-main">Dashboard (business)</span> Aggregate business progress report

In business computer information systems, a dashboard is a type of graphical user interface which often provides at-a-glance views of key performance indicators (KPIs) relevant to a particular objective or business process. In other usage, "dashboard" is another name for "progress report" or "report" and considered a form of data visualization. In providing this overview, business owners can save time and improve their decision making by utilizing dashboards.

<span class="mw-page-title-main">SAP ERP</span> Enterprise software

SAP ERP is an enterprise resource planning software developed by the German company SAP SE. SAP ERP incorporates the key business functions of an organization. The latest version of SAP ERP (V.6.0) was made available in 2006. The most recent SAP enhancement package 8 for SAP ERP 6.0 was released in 2016. It is now considered legacy technology, having been superseded by SAP S/4HANA.

Strategic planning software is a category of software that covers a wide range of strategic topics, methodologies, modeling and reporting.

An intelligent decision support system (IDSS) is a decision support system that makes extensive use of artificial intelligence (AI) techniques. Use of AI techniques in management information systems has a long history – indeed terms such as "Knowledge-based systems" (KBS) and "intelligent systems" have been used since the early 1980s to describe components of management systems, but the term "Intelligent decision support system" is thought to originate with Clyde Holsapple and Andrew Whinston in the late 1970s. Examples of specialized intelligent decision support systems include Flexible manufacturing systems (FMS), intelligent marketing decision support systems and medical diagnosis systems.

Market intelligence (MI) is gathering and analyzing information relevant to a company's market - trends, competitor and customer monitoring. It is a subtype of competitive intelligence (CI), which is data and information gathered by companies that provide continuous insight into market trends such as competitors' and customers' values and preferences.

Collaborative decision-making (CDM) software is a software application or module that helps to coordinate and disseminate data and reach consensus among work groups.

The fields of marketing and artificial intelligence converge in systems which assist in areas such as market forecasting, and automation of processes and decision making, along with increased efficiency of tasks which would usually be performed by humans. The science behind these systems can be explained through neural networks and expert systems, computer programs that process input and provide valuable output for marketers.

A customer data platform (CDP) is a collection of software which creates a persistent, unified customer database that is accessible to other systems. Data is pulled from multiple sources, cleaned and combined to create a single customer profile. This structured data is then made available to other marketing systems. According to Gartner, customer data platforms have evolved from a variety of mature markets, "including multichannel campaign management, tag management and data integration."

References

  1. ↑ B. Wierenga; Gerrit Harm van Bruggen; Gerrit Van Bruggen (2000), Marketing management support systems: principles, tools, and implementation, ISBN   978-0-7923-8615-5
  2. ↑ Nikolaos Matsatsinis; Yannis Siskos (2003), Intelligent Support Systems for Marketing Decisions, ISBN   978-1-4020-7194-2
  3. ↑ Cassie, Claire (1997). "Marketing decision support systems". Industrial Management & Data Systems. 97 (8): 293–296. doi:10.1108/02635579710195000.
  4. ↑ Arinze, Bay (May 1990), "Market planning with computer models: A case study in the software industry", Industrial Marketing Management, 19 (2): 117–129, doi:10.1016/0019-8501(90)90036-U
  5. ↑ Cassie, Claire (1997). "Emerald Insight". Industrial Management & Data Systems. 97 (8): 293–296. doi:10.1108/02635579710195000.
  6. ↑ Shim, J.P.; Warkentin, Merrill; Courtney, James F.; Power, Daniel J.; Sharda, Ramesh; Carlsson, Christer (2002). "Past, present, and future of decision support technology". Decision Support Systems. 33 (2): 111–126. doi:10.1016/S0167-9236(01)00139-7.
  7. ↑ Shim, J.P. (2002). "Past, present, and future of decision support technology". Decision Support Systems. 33 (2): 111–126. doi:10.1016/S0167-9236(01)00139-7.
  8. ↑ Power, Daniel J. (March 30, 2002). Decision Support Systems. Quorum Books division Greenwood. pp.  226. ISBN   978-1567204971.
  9. ↑ Cassie, Claire (1997). "Marketing decision support systems". Industrial Management & Data Systems. 97 (8): 293–296. doi:10.1108/02635579710195000.
  10. ↑ Hoch, Stephen J.; Schkade, David A. (1996). "A Psychological Approach to Decision Support Systems". Management Science. 42: 51–64. doi:10.1287/mnsc.42.1.51.
  11. ↑ Sanders, N.R.; Manrodt, K.B. (2003). "Forecasting Software in Practice: Use, Satisfaction, and Performance". Interfaces. 33 (5): 90–93. doi:10.1287/inte.33.5.90.19251.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.