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  2. Product optimization - Wikipedia

    en.wikipedia.org/wiki/Product_optimization

    For example, a soda bottle can have different packaging variations, flavors, nutritional values. It is possible to optimize a product by making minor adjustments. Typically, the goal is to make the product more desirable and to increase marketing metrics such as Purchase Intent, Believability, Frequency of Purchase, etc.

  3. Retail assortment strategies - Wikipedia

    en.wikipedia.org/wiki/Retail_assortment_strategies

    Assortment strategies are used by retailers in brick-and-mortar and ecommerce to decide on a daily basis how to allocate inventory to their stores as part of their merchandise planning processes. Such strategies are integral for retailers because they directly affect how their customers interact with their merchandise, and therefore, their brand.

  4. Taguchi methods - Wikipedia

    en.wikipedia.org/wiki/Taguchi_methods

    Taguchi realized that the best opportunity to eliminate variation of the final product quality is during the design of a product and its manufacturing process. Consequently, he developed a strategy for quality engineering that can be used in both contexts. The process has three stages: System design; Parameter (measure) design; Tolerance design

  5. Revenue management - Wikipedia

    en.wikipedia.org/wiki/Revenue_management

    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.

  6. Design optimization - Wikipedia

    en.wikipedia.org/wiki/Design_optimization

    Design optimization applies the methods of mathematical optimization to design problem formulations and it is sometimes used interchangeably with the term engineering optimization. When the objective function f is a vector rather than a scalar , the problem becomes a multi-objective optimization one.

  7. Price optimization - Wikipedia

    en.wikipedia.org/wiki/Price_optimization

    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]).

  8. Simulation-based optimization - Wikipedia

    en.wikipedia.org/wiki/Simulation-based_optimization

    Derivative-free optimization is a subject of mathematical optimization. This method is applied to a certain optimization problem when its derivatives are unavailable or unreliable. Derivative-free methods establish a model based on sample function values or directly draw a sample set of function values without exploiting a detailed model.

  9. Dynamic pricing - Wikipedia

    en.wikipedia.org/wiki/Dynamic_pricing

    A changeable prices menu at a fast food stand on Emek Refaim Street in Jerusalem. Dynamic pricing, also referred to as surge pricing, demand pricing, or time-based pricing, and variable pricing, is a revenue management pricing strategy in which businesses set flexible prices for products or services based on current market demands.