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DIGIgen 2007 - Marketing Institute of Singapore
DIGIgen 2007 - Marketing Institute of Singapore

... DIGIgen 2007: Marketing to the Digital Generation 15th – 16th January 2007 Singapore DIGIgen 2007 is the first ever conference in Singapore focusing on the DIGIgen. Who are the DIGIgen and what are they really about? Be sure not to miss the boat and attend DIGIgen 2007 to find out all about the quir ...
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... Consists of variables controlled by marketing professionals in an effort to satisfy the target market ...
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< 1 ... 673 674 675 676 677

Marketing mix modeling

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.
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