Assessing the impact of promotions on sales: A quantitative approach for a large-scale retailer's sales performance

Abstract

American Marketing Association defines marketing as "a system and operational process which includes various interconnected subsystems, harmonising with co-contributor elements to reach maximum efficiency." This thesis seeks to understand and explain the role of the promotional mix, one of the four Ps of the marketing-mix problem. Although sales promotions were acknowledged as a dissolving stock activity by sales management literature until the late 1960s, with increasing competition in the retail sector, it has become a vital instrument to impulse sales both for the long term and short term. However, within three decades, especially after the introduction of the television and online media (proper mediums for transmitting instant offers), the sales promotion activities had become more sophisticated, and their frontiers had outstretched beyond the frontiers of a single chapter to a stand-alone book. In the meantime, technological advances in data storage and computation areas enable scholars to create complex, multi-channel promotion analyses; the literature recognised promotions as an essential element in the marketing system. As a result, the sales promotion domain has become one of the significant divisions of marketing literature. In a modern sense, as a critical element of the marketing mix, the promotion has three main objectives, providing information to consumers and others, increasing demand, differentiating a product or category, stabilising sales, and accentuating a product's value. Therefore, most of the tools used by retailers from the sales promotion toolbox could be taxonomised in the price promotions domain. Price promotions' concrete impulse and response mechanism ease the effort of tracking and understanding effects created by sales trends. However, To accomplish a price promotion task, a company needs a clear understanding of which kind of promotions are working and why? Although current business intelligence applications can reflect the flow of cash and stocks of a company, promotions have complex relationships with various Key Performance Indicators (KPIs) of a business system. This aspect makes distinguishing the next value-added from a promotion a complicated job. This thesis aims to portray a reliable quantitative model to decompose price promotion's effect on sales trends. Most studies in price promotions have only focused on single response mechanisms like category effect, cannibalism, cross-category effects or brand switching. This study aims to contain responses of all courses given above in a single inclusive system of equations. Formulating a complete model system for the pilot category would allow practitioners to replicate results to all product inventory and eases the decision-making process extensively. Regarding the outcome of the studies, managerial relevance can be classified on the timing and nature of the impact created. In modern retailers' daily lives, promotions are critical to sustaining an increase in demand in the long term. On the other hand, retailers expect promotions to act as a balancer on lowering excess stocks in the short term. That promotes current actions and future strategies for sustaining long term increased demand. Therefore, a researcher studying in this field, especially in the business intelligence domain, should be aware that they should provide actionable, essential and meaningful insights for the practitioners. In order to achieve these kinds of outcomes, academic scholars should suggest a decision-making process in which retailers can observe the response of sales trends to their strategic moves, which are mainly classified as exogenous effects. Developing a reliable base for assessing promotions' impact on sales is strongly related to formulating a correctly specified model. Therefore, market response models are beneficial, especially for researchers working on the company's secondary data compiled from the enterprise database. A response model exhibits how one variable depends on other variables. For example, dependent variables could be sales or other KPIs of interest to marketing practitioners. On the other hand, independent variables are assumed to affect the dependent variable. Together these variables constitute a market response model. A response model defined on time series or cross-sectional data as an empirical response model. Accordingly, if a researcher prefers to study the direct and secondary impacts of price promotions on the retail level, market response models extended with exogenous promotion policy variables would be a yielding alternative. On the other hand, it is possible that to solve the true nature of promotions (create academic knowledge) and create insightful managerial relevance (prescriptive analytics), quantitative methods, including econometric response models, are the most efficient way. In this dissertation, I aimed to provide this kind of dual knowledge discovery for academic research and the retail industry. The research is based on three hypotheses which led me to construct two categories /multi-brand promotional effectiveness models. While the first section of the empirical study formulates the variables used in the next part of the study, including volatility modelling to promotion effectiveness has created an alternative approach. The second part of my empirical work was my playground to decompose and analyse net sales effects created by price promotion. The findings concluded that promotional strategy significantly affects the sales quantity of category/brand pairs both in the long and short term. As expected, I concluded that most of the sales bump created through promotions stems from the product's own promotional activity. On the other hand, results provided that promotions applied to competitor brands and categories also cause a significant change in sales trends. This research provides a timely and necessary study of creating pioneering a central promotion effectiveness assessment system for practitioners. By utilising the models produced in this study, the retail executives could organise promotional strategies from a wide-angle.