Assessing the Impact of Temporary Retail Price Discounts Intervals Using SVM Semiparametric Regression

Although the marketing literature has found that temporary retail price discounts cause a significant sales increase, little is known about the specific characteristics of deals that influence the magnitude of the sales spike. In this paper, we analyse the impact of the length of temporary retail price discounts periods on the sales increase using scanner-store daily-sales data for two frequently purchased product categories: ground coffee (a storable category) and yogurt (a perishable category).Wedevelop a robust semiparametric regression model based on support vector statistical theory with several previously proposed predictors along with a daily time description. This model also makes i…

Using Daily Store-level Data to Understand Price Promotion Effects in a Semiparametric Regression Model

Though it has been widely reported in the marketing literature that temporary price discounts generate substantial short-term sales increase, the shape of the deal effect curve constitutes a key research topic, for which there are still limited empirical results. To address this issue, a semiparametric regression approach is used to model the complex nature of this phenomenon. Our model is developed at the brand level using daily store-level scanner-data, which allows the study of several nonreported promotional effects, such as the influence of the day of the week both in promotional and nonpromotional periods. The results show that the weekend is the most effective in increasing promotion…

Evaluating temporary retail price discounts using semiparametric regression

PurposeTo analyze the impact of temporary retail price discount on a consumer goods product category using semiparametric regression and considering different promotional price discount characteristics as well as brand characteristics.Design/methodology/approachA semiparametric regression model using Support Vector Machines, which aim to evaluate retailers' decisions about temporary price discounts, has been developed. The model is derived from the analysis of historical sales data, which provide precise evaluation of previous temporary price discounts periods. The model is also consistent with ample empirical evidence showing that historical retail sales data can be used to evaluate the im…

Spatial mapping of price competition using logit-type market share models and store-level scanner-data

This paper proposes a methodology to obtain reliable spatial maps of price competition using store-level scanner data. Specifically, a procedure to obtain a symmetric matrix of similarities between brands considering their substitutability depending on price variations is proposed. The matrix is derived from a market response model where price cross-effects are split into two components. The first component accounts for the fact that price variation in one brand can have different effects to price variation in other brands (ie j → j′≠j′ → j). The second component accounts for the fact that the price of each brand can have different effects across competing brands (ie j → j′≠j → j ″). The ma…

Determination of Optimum Prices in the Commercial Distribution Sector in Spain: Application of an Asymetrical Competition Approach

Teniendo en cuenta la importancia que adquieren las decisiones de precios en la distribución comercial minorista, en este trabajo se propone un modelo de decisión de precios óptimos en el que, a corto plazo, los efectos de los precios óptimos sobre la demanda y los márgenes del distribuidor maximizan la rentabilidad global de la categoría de productos. Tres aspectos fundamentales permiten describir esta propuesta: 1) se basa en una perspectiva agregada; 2) incorpora modelos de cuota de mercado con consistencia lógica -con el fin de aportar mayor robustez a la medición de la demanda- y 3) incluye el papel de la estructura competitiva mediante una modelización explícita de los efectos asimétr…

Using Support Vector Semiparametric Regression to estimate the effects of pricing on brand substitution

Using store level scanner data to improve category management decisions: Developing positioning maps

This paper provides evidence of the usefulness of aggregated point-of-sale scanner data to infer the positioning of competing brands, providing valuable information for category management and hence facilitating decision making. Specifically, the authors propose a methodology to study the internal market structure based on market share models with latent heterogeneity when only macro-level time series data (not individual choices) are available. The proposed approach assumes a multidimensional decomposition, latent in the preference structure that is implicit to these types of models. By empirically applying this approach, the authors (1) simultaneously identify both latent dimensions of co…

Retail pricing decisions and product category competitive structure

This study addresses the use of demand forecasting techniques by retailers to support their decision making. Specifically, the authors propose a pricing decision support model for retailers to estimate optimal prices, whose output depends on the configuration of a supporting measurement model. The measurement model is a demand function that relates sales and prices within the category; optimal prices are those whose effects on demand and retail margins maximize the category's profitability. This investigation focuses particularly on the role of competitive structure, such that the authors consider two types of price competition asymmetries for demand forecasting: those depending on the bran…