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Category Management as a Tool for Effective Assortment Management: Evidence from "Pet Food" Category

Student: Sivov Pavel

Supervisor: Dmitry Tretyak

Faculty: Graduate School of Business

Educational Programme: Marketing (Master)

Year of Graduation: 2020

Existing domestic retailers use all possible methods of struggle for the shoppers. In previous periods, retail chains increased their profitability due to a quantitative increase in outlets. Today, the level of competition in the market requires them to fundamentally new approaches to trade by increasing the efficiency of each individual outlet. The relevance of the research topic is dictated by the fact that in the face of growing competition and the deteriorating economic situation in the crisis, retail chains are constantly looking for new ways to increase sales in order to survive in the market. Suppliers also need to constantly work, find new opportunities and sources of category growth, which will be reflected in the business results. One of the most effective management tools is category management. As a result, it has become an important part of the retail business. The object of research is the process of category management. The subject of the research is the application of category management practices in relation to the category "Pet Food". The purpose of the work is to develop specific recommendations for the category management of “Pet Food” in retail. These recommendations can lead to improved business performance and conditions for shopping, as well as increase sales in the category. Research Objectives: 1) To conduct a theoretical review of the literature on category management, classify its definitions 2) To analyze the experience of using market segmentation and the application of clustering in the literature within category management 3) To consider world practices in the application of category management in business 4) To analyze the practice of creating planograms and using cluster analysis in world experience 5) To study the market and the category of "Pet Food" in Russia 6) To apply regression and cluster analysis using secondary data in the category of "Pet Food"

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