Abstract:

Grocery chain supermarkets, are subject to local conditions which may greatly influence their performance. The marketing function has the responsiblity for investigating the current conditions and the potential for each store. The companies Information System is capable of providing only some of the data needed, usually total volume and number of sales. However, an effective analysis, in terms of marketing, requires accurate estimates of the market. Is it possible to accurately measure the level of cover of a supermarket? Is it possible to estimate the number of its customers and segment them by class of purchase, salary, area, and type of behaviour? Is it possible to estimate the number of non- users? Many supermarkets perform regular customer surveys, in- store, with the intention of evaluating its area of influence, the customers’ perception of its services, and its position with respect to the competition. These surveys have the advantage of being low cost and quickly completed. It is our belief that an accurate use of these surveys, the use of data from internal Information Systems and the estimation of some market variables, allow the data obtained to be utilized much more effectively, without great increasing the resources employed, and estimate very precisely the crucial variables required for the definition of the marketing strategies of the store. The key to the problem lies in the awareness that it isn’t sufficient to analysis the sales statistics separately from the qualitative and quantitive data on the market, but that it is both necessary and possible to estimate the market share, the variables which determines it, the number of customers served and their average expenditure. In this paper, we discuss the principle implications that derive from this approach, also presented are the main results that can be obtained as regards the objectives stated above. With this in mind, the results obtained by the analysis of the customers of 20 grocery supermarkets, of various sizes and from different chains, situated in central Italy, are presented.