Implementing a marketing strategy model in combination with geodatabases

Abstract

This article addresses the relevant issue of using geomarketing tools for spatial market analysis. The authors conducted a study to determine the optimal location for a new retail outlet. Integrating geographic information into marketing research significantly improved its quality. Processing large sets of descriptive data about the object and applying geographic information systems (GIS) accelerated the analysis and enhanced decision-making. The novelty of the article lies in applying the 7P marketing concept to comprehensively process available information about the studied retail outlet, as well as in using GIS to analyze and forecast various spatial data. The focus of the research is the retail market, specifically the “Epicenter” construction hypermarket chain in Kharkiv. The aim of the article is to develop a step-by-step approach for identifying the best location for a retail outlet. The study used system analysis methods to transform discrete data into continuous form for further processing of large geospatial datasets. The research task was to conduct a geomarketing study aimed at identifying the optimal location for an “Epicenter” hypermarket in Kharkiv. To model customer attraction, the authors proposed using the Huff gravity model, as it combines geographic and probabilistic components and allows forecasting customer flows from specific traffic-generating zones. The Huff model also enables refinements by incorporating additional spatial information. As a result, the authors clearly demonstrated the interconnections of geomarketing elements through the 7P concept, analyzed the potential of geospatial analysis methods in geomarketing, and applied spatial data processing tools within QGIS Desktop, including the “Network Analysis” and ORS Tools modules. The findings can support decision-making when choosing the best location for a new retail outlet, helping to minimize risks of revenue loss in a regulated market with spatial constraints.