EN - Data Analysis of Competitive Strategies

The objective of this study is to provide the answer to a fundamental question of marketing: to what extent do empirical evidence and habit affect the choice of a marketing strategy, as opposed to quantitative findings?

The effective Development of a marketing plan for promotional catalogues requires defining sets of values for over a hundred of variables. How are these choices made? Let’s assume that we plan to increase the number of pages per leaflet from 16 to 24; or, extend the offer’s validity from 6 to 12 days. Would it possible to measure the impact of these changes on the competitive position of our strategy?

Most importantly, is there a way to simulate these changes so that we could identify the optimum values without the necessity to run costly in market tests?

This study also presents a relationship between an adopted catalogue strategy and sales per square metre. So, What characterizes the strategic decisions made by top retailers and stores which reported the most dynamic growth compared to previous year?

Based on a statistical analysis, this study attempts to provides answers to the above questions. Methods applied in the study help underscore dependencies between particular variables and similarities between strategies. They make it possible to extract useful information from large data sets (Big Data Mining).

We present here a 2010 case study of a group of large supermarket chains in Poland. Of course, the study can be conducted on a different group of retailers, for different store formats, in another country and time