Bayes Forecast sees Quantitative Marketing as a process of building dynamic models that capture market behavior and measure simultaneously a wide variety of effects that influence the market and provide detailed and essential knowledge.

Included among the effects to be explained and quantified are customer behavior, competitive actions, price dynamics, marketing mix, holidays, calendar effects, products and point of sale substitutions, and macroeconomic variables.

Under this perspective, we have acquired a solid knowledge of all the relevant variables required for understanding markets in order to:

• Understand the behavior of a customer or group of customers.
• Understand customer segments, the evolution of their loyalty, their life cycle, and their consumption as a result of the introduction of new products and services.
• Forecast risk levels and the probability of customer defection.
• Increase the success of innovation by estimating potential demand before the introduction of new products and services.
• Understand production costs and the management of cash and stocks.
• Quantify the efficiency of marketing actions by sales channels and kinds of products.
• Determine the effects of advertising on sales, considering media factors such as spot quality, brand, and decay rating.
• Calculate the effects of promotions by intensity, frequency, target, and side effects.
• Optimize the cost of zero stocks and remaining stocks.