|
Marketing mix modeling (MMM) is a term of art for the use of statistical analysis such as multivariate regressions on sales and marketing time series data to estimate the impact of various marketing tactics (marketing mix) on sales and then forecast the impact of future sets of tactics. It is often used to optimize advertising mix and promotional tactics with respect to sales revenue or profit. The techniques were developed by econometricians and were first applied to consumer packaged goods, since manufacturers of those goods had access to good data on sales and marketing support. The first companies dedicated to the commercial development of MMM were MMA (then Media Marketing Assessment) started in 1990 and the Hudson River Group founded in 1989. Other early pioneer-users of econometric modeling were the ATG group at the advertising agency JWT in the 1990s and later incorporated into MindShare ATG, BrandScience at Omnicom, and the specialist modeling agency OHAL since the late 1980s. These agencies took MMM from being a little-used and academic discipline to being a widespread and common marketing tool. Improved availability of data, massively greater computing power, and the pressure to measure and optimize marketing spend has driven the explosion in popularity as a marketing tool. In the recent times MMM has found acceptance as a trustworthy marketing tool among the major consumer marketing companies. Often in the digital media context, MMM is referred to as attribution modeling. ==History== The term Marketing Mix was developed by Neil Borden who first started using the phrase in 1949. “An executive is a mixer of ingredients, who sometimes follows a recipe as he goes along, sometimes adapts a recipe to the ingredients immediately available, and sometimes experiments with or invents ingredients no one else has tried." (Culliton, J. 1948) According to Borden, "When building a marketing program to fit the needs of his firm, the marketing manager has to weigh the behavioral forces and then juggle marketing elements in his mix with a keen eye on the resources with which he has to work." (Borden, N. 1964 pg 365). E. Jerome McCarthy (McCarthy, J. 1960), was the first person to suggest the four P's of marketing – price, promotion, product and place (distribution) – which constitute the most common variables used in constructing a marketing mix. According to McCarthy the marketers essentially have these four variables which they can use while crafting a marketing strategy and writing a marketing plan. In the long term, all four of the mix variables can be changed, but in the short term it is difficult to modify the product or the distribution channel. Another set of marketing mix variables were developed by Albert Frey (Frey, A. 1961) who classified the marketing variables into two categories: the offering, and process variables. The "offering" consists of the product, service, packaging, brand, and price. The "process" or "method" variables included advertising, promotion, sales promotion, personal selling, publicity, distribution channels, marketing research, strategy formation, and new product development. Recently, Bernard Booms and Mary Bitner built a model consisting of seven P's (Booms, B. and Bitner, M. 1981). They added "People" to the list of existing variables, in order to recognize the importance of the human element in all aspects of marketing. They added "process" to reflect the fact that services, unlike physical products, are experienced as a process at the time that they are purchased. Desktop modeling tools such as Micro TSP have made this kind of statistical analysis part of the mainstream now. Most advertising agencies and strategy consulting firms offer MMM services to their clients. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Marketing mix modeling」の詳細全文を読む スポンサード リンク
|