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Multivariate Testing In Marketing
In marketing, multivariate testing or multi-variable testing techniques apply statistical hypothesis testing on multi-variable systems, typically consumers on websites. Techniques of multivariate statistics are used. In internet marketing In internet marketing, multivariate testing is a process by which more than one component of a website may be tested in a live environment. It can be thought of in simple terms as numerous A/B tests performed on one page at the same time. A/B tests are usually performed to determine the better of two content variations; multivariate testing uses multiple variables to find the ideal combination. The only limits on the number of combinations and the number of variables in a multivariate test are the amount of time it will take to get a statistically valid sample of visitors and computational power. Multivariate testing is usually employed in order to ascertain which content or creative variation produces the best improvement in the defined goals o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Marketing
Marketing is the process of exploring, creating, and delivering value to meet the needs of a target market in terms of goods and services; potentially including selection of a target audience; selection of certain attributes or themes to emphasize in advertising; operation of advertising campaigns; attendance at trade shows and public events; design of products and packaging attractive to buyers; defining the terms of sale, such as price, discounts, warranty, and return policy; product placement in media or with people believed to influence the buying habits of others; agreements with retailers, wholesale distributors, or resellers; and attempts to create awareness of, loyalty to, and positive feelings about a brand. Marketing is typically done by the seller, typically a retailer or manufacturer. Sometimes tasks are contracted to a dedicated marketing firm or advertising agency. More rarely, a trade association or government agency (such as the Agricultural Marketing Servic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Discrete Choice
In economics, discrete choice models, or qualitative choice models, describe, explain, and predict choices between two or more discrete alternatives, such as entering or not entering the labor market, or choosing between modes of transport. Such choices contrast with standard consumption models in which the quantity of each good consumed is assumed to be a continuous variable. In the continuous case, calculus methods (e.g. first-order conditions) can be used to determine the optimum amount chosen, and demand can be modeled empirically using regression analysis. On the other hand, discrete choice analysis examines situations in which the potential outcomes are discrete, such that the optimum is not characterized by standard first-order conditions. Thus, instead of examining "how much" as in problems with continuous choice variables, discrete choice analysis examines "which one". However, discrete choice analysis can also be used to examine the chosen quantity when only a few distin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Product Optimization
Production optimization is the practice of making changes or adjustments to a product to make it more desirable. Description A product has a number of attributes. 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. Methods Multivariate optimization is one of the most common methods for product optimization. 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 process optimization. More recently companies started to adopt E ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cultural Multivariate Testing
In internet marketing, cultural multivariate testing is multivariate testing performed on an international website in each geographically distinct market for the purpose of website localisation, i.e. finding the best culturally tailored design for the users in that specific location. Similarly to multivariate testing it involves testing combinations of alternative components of a website in a live environment. The number of combinations which can be run at the same time is limited only by the time it would take to collect a statistically significant sample of visitors and computational power. A test is usually designed to measure a specific goal, such as newsletter sign-up or completing an online purchase (so-called conversion Conversion or convert may refer to: Arts, entertainment, and media * "Conversion" (''Doctor Who'' audio), an episode of the audio drama ''Cyberman'' * "Conversion" (''Stargate Atlantis''), an episode of the television series * "The Conversion" ...), wh ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multivariate Statistics
Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to each other. The practical application of multivariate statistics to a particular problem may involve several types of univariate and multivariate analyses in order to understand the relationships between variables and their relevance to the problem being studied. In addition, multivariate statistics is concerned with multivariate probability distributions, in terms of both :*how these can be used to represent the distributions of observed data; :*how they can be used as part of statistical inference, particularly where several different quantities are of interest to the same analysis. Certain types of problems involving multivariate data, for example simple linear regression an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Web Usability
Web usability of a website are broad goals of usability and presentation of information and choices in a clear and concise way, a lack of ambiguity and the placement of important items in appropriate areas as well as ensuring that the content works on various devices and browsers. The end-goal a website creator wants to achieve is to provide the users of the website a better experience. ''˝Unless a web site meets the needs of the intended users it will not meet the needs of the organization providing the web site. Web site development should be user-centred, evaluating the evolving design against user requirements˝'' Web Usability definition and components Web Usability includes a small learning curve, easy content exploration, findability, task efficiency, user satisfaction, and automation. These new components of usability are due to the evolution of the Web and personal devices. Examples: automation: auto fill, databases, personal account; efficiency: voice command (Siri, Al ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fractional Factorial Design
In statistics, fractional factorial designs are experimental designs consisting of a carefully chosen subset (fraction) of the experimental runs of a full factorial design. The subset is chosen so as to exploit the sparsity-of-effects principle to expose information about the most important features of the problem studied, while using a fraction of the effort of a full factorial design in terms of experimental runs and resources. In other words, it makes use of the fact that many experiments in full factorial design are often redundant, giving little or no new information about the system. Notation Fractional designs are expressed using the notation ''l''k − p, where ''l'' is the number of levels of each factor investigated, ''k'' is the number of factors investigated, and ''p'' describes the size of the fraction of the full factorial used. Formally, ''p'' is the number of ''generators'', assignments as to which effects or interactions are ''confounded'', ''i.e.'', ca ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Optimal Design
In the design of experiments, optimal designs (or optimum designs) are a class of experimental designs that are optimal with respect to some statistical criterion. The creation of this field of statistics has been credited to Danish statistician Kirstine Smith. In the design of experiments for estimating statistical models, optimal designs allow parameters to be estimated without bias and with minimum variance. A non-optimal design requires a greater number of experimental runs to estimate the parameters with the same precision as an optimal design. In practical terms, optimal experiments can reduce the costs of experimentation. The optimality of a design depends on the statistical model and is assessed with respect to a statistical criterion, which is related to the variance-matrix of the estimator. Specifying an appropriate model and specifying a suitable criterion function both require understanding of statistical theory and practical knowledge with designing exper ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Optimal Design
In the design of experiments, optimal designs (or optimum designs) are a class of experimental designs that are optimal with respect to some statistical criterion. The creation of this field of statistics has been credited to Danish statistician Kirstine Smith. In the design of experiments for estimating statistical models, optimal designs allow parameters to be estimated without bias and with minimum variance. A non-optimal design requires a greater number of experimental runs to estimate the parameters with the same precision as an optimal design. In practical terms, optimal experiments can reduce the costs of experimentation. The optimality of a design depends on the statistical model and is assessed with respect to a statistical criterion, which is related to the variance-matrix of the estimator. Specifying an appropriate model and specifying a suitable criterion function both require understanding of statistical theory and practical knowledge with designing exper ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Taguchi Methods
Taguchi methods ( ja, タグチメソッド) are statistical methods, sometimes called robust design methods, developed by Genichi Taguchi to improve the quality of manufactured goods, and more recently also applied to engineering, biotechnology, marketing and advertising. Professional statisticians have welcomed the goals and improvements brought about by Taguchi methods, particularly by Taguchi's development of designs for studying variation, but have criticized the inefficiency of some of Taguchi's proposals. Taguchi's work includes three principal contributions to statistics: *A specific loss function *The philosophy of ''off-line quality control''; and *Innovations in the design of experiments. Loss functions Loss functions in the statistical theory Traditionally, statistical methods have relied on mean-unbiased estimators of treatment effects: Under the conditions of the Gauss–Markov theorem, least squares estimators have minimum variance among all mean-unbiased li ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Nobel Prize In Economics
The Nobel Memorial Prize in Economic Sciences, officially the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel ( sv, Sveriges riksbanks pris i ekonomisk vetenskap till Alfred Nobels minne), is an economics award administered by the Nobel Foundation. Although not one of the five Nobel Prizes which were established by Alfred Nobel's will in 1895, it is commonly referred to as the Nobel Prize in Economics. The winners of the Nobel Memorial Prize in Economic Sciences are chosen in a similar way, are announced along with the Nobel Prize recipients, and the prize is presented at the Nobel Prize Award Ceremony. The award was established in 1968 by an endowment "in perpetuity" from Sweden's central bank, Sveriges Riksbank, to commemorate the bank's 300th anniversary. It is administered and referred to along with the Nobel Prizes by the Nobel Foundation. Laureates in the Memorial Prize in Economics are selected by the Royal Swedish Academy of Sciences. [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Daniel McFadden
Daniel Little McFadden (born July 29, 1937) is an American econometrician who shared the 2000 Nobel Memorial Prize in Economic Sciences with James Heckman. McFadden's share of the prize was "for his development of theory and methods for analyzing discrete choice". He is the Presidential Professor of Health Economics at the University of Southern California and Professor of the Graduate School at University of California, Berkeley. Early life and education McFadden was born on July 29, 1937 in Raleigh, North Carolina. He attended the University of Minnesota, where he received a B.S. in Physics, and a Ph.D. in Behavioral Science (Economics) five years later (1962). While at the University of Minnesota, his graduate advisor was Leonid Hurwicz, who was awarded the Economics Nobel Prize in 2007. Career In 1964 McFadden joined the faculty of University of California, Berkeley, focusing his research on choice behavior and the problem of linking economic theory and measurement. In 1974 he ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
