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In marketing, a marketing plan is created to guide businesses on how to communicate the benefits of their products to the needs of potential customer. The situation analysis is the second step in the marketing plan and is a critical step in establishing a long term relationship with customers. [3] The parts of a marketing plan are: Introduction
Scenario analysis is a process of analyzing future events by considering alternative possible outcomes (sometimes called "alternative worlds"). Thus, scenario analysis, which is one of the main forms of projection, does not try to show one exact picture of the future. Instead, it presents several alternative future developments.
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.
SWOT analysis evaluates the strategic position of organizations and is often used in the preliminary stages of decision-making processes [2] to identify internal and external factors that are favorable and unfavorable to achieving goals. Users of a SWOT analysis ask questions to generate answers for each category and identify competitive ...
Marketing mix modeling (MMM) is an analytical approach that uses historic information to quantify impact of marketing activities on sales. Example information that can be used are syndicated point-of-sale data (aggregated collection of product retail sales activity across a chosen set of parameters, like category of product or geographic market) and companies’ internal data.
In the same year Lilien G. L. and A. Rangaswamy published Marketing Engineering: Computer-Assisted Marketing Analysis and Planning, [3] Fildes and Ventura [4] praised the book in their review, while noting that a fuller discussion of market share models and econometric models would have made the book better for teaching and that "conceptual ...
The difference between learning automata and Q-learning is that the former technique omits the memory of Q-values, but updates the action probability directly to find the learning result. Learning automata is a learning scheme with a rigorous proof of convergence.
In this scenario, formal planning systems are criticized by a number of academics, who argue that conventional methods, based on classic analytical tools (market research, value chain analysis, assessment of rivals), [2] fail to shape a strategy that can adjust to the changing market [3] and enhance the competitiveness of each business unit ...