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In this method, multiple product attributes are specified and then tested with consumers. Due to complex interaction effects between different attributes (for example, consumers frequently associate certain flavors with packaging colors), it is problematic to use mathematical methods, such as Conjoint Analysis, typically used in industrial ...
Assortment plan is a trade-off between the breadth and depth of products that a retailer wishes to carry. Assortment optimization refers to the problem of selecting a set of products to offer to a group of customers to maximize the revenue that is realized when customers make purchases according to their preferences.
Often considered the pinnacle of the revenue management process, optimization is about evaluating multiple options on how to sell your product and to whom to sell your product. [5] Optimization involves solving two important problems in order to achieve the highest possible revenue. The first is determining which objective function to optimize.
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A product strategy sets the direction for new product development. Companies utilize the product strategy in strategic planning and marketing to set the direction of the company's activities. [1] The product strategy is composed of a variety of sequential processes in order for the vision to be effectively achieved.
Yield management (YM) [4] has become part of mainstream business theory and practice over the last fifteen to twenty years. Whether an emerging discipline or a new management science (it has been called both), yield management is a set of yield maximization strategies and tactics to improve the profitability of certain businesses.
Product profitability; Customer profitability; Capital expenditures; Manufacturing operations; Supply chain; Business processes (human and information-based) Business policy; Market demand curves; Competitive strategy; All of the above can be summarized as Enterprise Optimization use cases . These are however to be seen as use cases only.
Price optimization utilizes data analysis to predict the behavior of potential buyers to different prices of a product or service. Depending on the type of methodology being implemented, the analysis may leverage survey data (e.g. such as in a conjoint pricing analysis [7]) or raw data (e.g. such as in a behavioral analysis leveraging 'big data' [8] [9]).