Perceptual Mapping
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Perceptual Mapping
Perceptual mapping or market mapping is a diagrammatic technique used by asset marketers that attempts to visually display the perceptions of customers or potential customers. The positioning of a brand is influenced by customer perceptions rather than by those of businesses. For example, a business may feel it sells upmarket products of high quality, but if customers view the products as low quality, it is their views which will influence sales. Typically the position of a company's product, product line, or brand is displayed relative to their competition.McCarthy, E. J., McGuiggan, I. R., Perreault, D. W., & Quester, G. P. (2007). ''Marketing: Creating and delivering value.'' Australia, Sydney: McGraw-Hill Perceptual maps, also known as market maps, usually have two dimensions but can be multi-dimensional or use multiple colours to add an extra variable. They can be used to identify gaps in the market and potential partners or merger targets as well as to clarify perceptual probl ...
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Diagram
A diagram is a symbolic representation of information using visualization techniques. Diagrams have been used since prehistoric times on walls of caves, but became more prevalent during the Enlightenment. Sometimes, the technique uses a three-dimensional visualization which is then projected onto a two-dimensional surface. The word ''graph'' is sometimes used as a synonym for diagram. Overview The term "diagram" in its commonly used sense can have a general or specific meaning: * ''visual information device'' : Like the term " illustration", "diagram" is used as a collective term standing for the whole class of technical genres, including graphs, technical drawings and tables. * ''specific kind of visual display'' : This is the genre that shows qualitative data with shapes that are connected by lines, arrows, or other visual links. In science the term is used in both ways. For example, Anderson (1997) stated more generally: "diagrams are pictorial, yet abstract, represen ...
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Multi Dimensional Scaling (in Marketing)
Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a dataset. MDS is used to translate "information about the pairwise 'distances' among a set of n objects or individuals" into a configuration of n points mapped into an abstract Cartesian space. More technically, MDS refers to a set of related ordination techniques used in information visualization, in particular to display the information contained in a distance matrix. It is a form of non-linear dimensionality reduction. Given a distance matrix with the distances between each pair of objects in a set, and a chosen number of dimensions, ''N'', an MDS algorithm places each object into ''N''-dimensional space (a lower-dimensional representation) such that the between-object distances are preserved as well as possible. For ''N'' = 1, 2, and 3, the resulting points can be visualized on a scatter plot. Core theoretical contributions to MDS were made by James O. Ramsay of Mc ...
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Strategic Management
In the field of management, strategic management involves the formulation and implementation of the major goals and initiatives taken by an organization's managers on behalf of stakeholders, based on consideration of Resource management, resources and an assessment of the internal and external Market environment, environments in which the organization operates.qn, date=June 2018 Strategic management provides overall direction to an enterprise and involves specifying the organization's goal, objectives, developing policy, policies and plans to achieve those objectives, and then allocating resources to implement the plans. Academics and practicing managers have developed numerous models and frameworks to assist in strategic decision-making in the context of complex environments and competitive dynamics. Strategic management is not static in nature; the models can include a feedback, feedback loop to monitor execution and to inform the next round of planning. Michael Porter identif ...
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Product Management
Product management is the business process of planning, developing, launching, and managing a product or service. It includes the entire lifecycle of a product, from ideation to development to go to market. Product managers are responsible for ensuring that a product meets the needs of its target market and contributes to the business strategy, while managing a product or products at all stages of the product lifecycle. Software product management adapts the fundamentals of product management for digital products. History The concept of product management originates from a 1931 memo by Procter & Gamble President Neil H. McElroy. McElroy, requesting additional employees focused on brand management, needed "Brand Men" who would take on the role of managing products, packaging, positioning, distribution, and sales performance. The memo defined a Brand Man's work as: * Study carefully shipments of his brands by units. * Where brand development is heavy ... examine carefully t ...
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Product Life-cycle Management (marketing)
Product life-cycle management (PLM) is the succession of strategies by business management as a product goes through its life-cycle. The conditions in which a product is sold (advertising, saturation) changes over time and must be managed as it moves through its succession of stages. Goals The goals of product life cycle management (PLM) are to reduce time to market, improve product quality, reduce prototyping costs, identify potential sales opportunities and revenue contributions, maintain and sustain operational serviceability, and reduce environmental impacts at end-of-life. To create successful new products the company must understand its customers, markets and competitors. Product Lifecycle Management (PLM) integrates people, data, processes and business systems. It provides product information for companies and their extended supply chain enterprise. PLM solutions help organizations overcome the increased complexity and engineering challenges of developing new products for ...
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Multidimensional Scaling
Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a dataset. MDS is used to translate "information about the pairwise 'distances' among a set of n objects or individuals" into a configuration of n points mapped into an abstract Cartesian space. More technically, MDS refers to a set of related ordination techniques used in information visualization, in particular to display the information contained in a distance matrix. It is a form of non-linear dimensionality reduction. Given a distance matrix with the distances between each pair of objects in a set, and a chosen number of dimensions, ''N'', an MDS algorithm places each object into ''N''-dimensional space (a lower-dimensional representation) such that the between-object distances are preserved as well as possible. For ''N'' = 1, 2, and 3, the resulting points can be visualized on a scatter plot. Core theoretical contributions to MDS were made by James O. Ramsay of M ...
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Marketing Research
Marketing research is the systematic gathering, recording, and analysis of qualitative and quantitative data about issues relating to marketing products and services. The goal is to identify and assess how changing elements of the marketing mix impacts customer behavior. This involves specifying the data required to address these issues, then designing the method for collecting information, managing and implementing the data collection process. After analyzing the data collected, these results and findings, including their implications, are forwarded to those empowered to act on them. Market research, marketing research, and marketing are a sequence of business activities; sometimes these are handled informally. The field of ''marketing research'' is much older than that of ''market research''. Although both involve consumers, ''Marketing'' research is concerned specifically about marketing processes, such as advertising effectiveness and salesforce effectiveness, while ''mark ...
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Discriminant Analysis
Linear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics and other fields, to find a linear combination of features that characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification. LDA is closely related to analysis of variance (ANOVA) and regression analysis, which also attempt to express one dependent variable as a linear combination of other features or measurements. However, ANOVA uses categorical independent variables and a continuous dependent variable, whereas discriminant analysis has continuous independent variables and a categorical dependent variable (''i.e.'' the class label). Logistic regression and probit regression are more similar to LDA than ANOVA is, as they also explain a categorical var ...
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Diffusion Of Innovations
Diffusion of innovations is a theory that seeks to explain how, why, and at what rate new ideas and technology spread. Everett Rogers, a professor of communication studies, popularized the theory in his book ''Diffusion of Innovations''; the book was first published in 1962, and is now in its fifth edition (2003). Rogers argues that diffusion is the process by which an innovation is communicated over time among the participants in a social system. The origins of the diffusion of innovations theory are varied and span multiple disciplines. Rogers proposes that five main elements influence the spread of a new idea: the innovation itself, adopters, communication channels, time, and a social system. This process relies heavily on social capital. The innovation must be widely adopted in order to self-sustain. Within the rate of adoption, there is a point at which an innovation reaches critical mass. In 1989, management consultants working at the consulting firm Regis Mckenna Inc. the ...
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Cross Elasticity Of Demand
In economics, the cross elasticity of demand or cross-price elasticity of demand measures the percentage change of the quantity demanded for a good to the percentage change in the price of another good, ceteris paribus. In real life, the quantity demanded of good is dependent on not only its own price (Price elasticity of demand) but also the price of other "related" products. \text = \frac The concept is used to identify the relationship between two goods, they can be: * Complements * Substitutes * Unrelated A negative cross elasticity denotes two products that are complements, while a positive cross elasticity denotes two products are substitutes. If products A and B are complements, an increase in the price of B leads to a decrease in the quantity demanded for A, as A is used in conjunction with B. Equivalently, if the price of product B decreases, the demand curve for product A shifts to the right reflecting an increase in A's demand, resulting in a ''negative'' value for the ...
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Logit Analysis (in Marketing)
{{see also, Logistic regression Logit analysis is a statistical technique used by marketers to assess the scope of customer acceptance of a product, particularly a new product. It attempts to determine the intensity or magnitude of customers' purchase intentions and translates that into a measure of actual buying behaviour. Logit analysis assumes that an unmet need in the marketplace has already been detected, and that the product has been designed to meet that need. The purpose of logit analysis is to quantify the potential sales of that product. It takes survey data on consumers' purchase intentions and converts it into actual purchase probabilities. Logit analysis defines the functional relationship between stated purchase intentions and preferences, and the actual probability of purchase. A preference regression is performed on the survey data. This is then modified with actual historical observations of purchase behavior. The resultant functional relationship defines purchase p ...
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Cluster Analysis (in Marketing)
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis itself is not one specific algorithm, but the general task to be solved. It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include groups with small distances between cluster members, dense areas of the data space, intervals or particular statistical distributions. Clustering can therefore be formulated as a multi-objective optimization problem. The a ...
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