The fast-moving consumer goods (FMCG) sector has a significant share in the consumer goods market. It might seem that selling household chemicals is a so-called “sure thing,” a mechanism that works efficiently, mainly thanks to retail chains that have dynamized the sales of these items. However, this is not always the case, and often the manufacturer must take matters into their own hands to avoid being left with high inventory levels. Imagine a manufacturer of household chemicals offering 10 different products: four different laundry detergents, a cleaning emulsion, a toilet cleaner, a scouring powder, and three types of shampoos. These products are sold in selected retail chains in one of the large cities in Poland. To improve sales results, it was decided to introduce changes in product distribution, both at the retail chain level and in individual stores. But how to do it? It is possible. Very simply and quickly! Such changes are most easily carried out based on data collected by Claritas Polska using the National Product and Service Questionnaire. This nationwide questionnaire is the largest and most accurate address database in Poland, containing 1.9 million households, which is 5.2 million consumers. To improve the sales results of our manufacturer, it was decided to introduce changes in product distribution, both at the retail chain level and in individual stores. The changes were carried out based on data collected in the National Product and Service Questionnaire.
Using information about purchased brands and chosen retail chains, the degree of product usage by all residents of the hypothetical city and by customers of individual chains was compared. If, after calculations, a given product achieved a score above 120 points in a chain, it meant that among the people who shop at that chain, there are many of its users. It could therefore be assumed that it would sell well in that chain.
In this way, the attractiveness of the chain for all products was estimated, and then, for each of them, the attractiveness of individual stores in the chain. This time, the percentage of users of a given product in the entire city was compared with the percentage of its users among the customers of individual stores, considering people living within their reach as store customers.
It turned out that – in the case of chain A – it can be assumed that laundry detergent No. 1 will sell well in all stores, but best in the branches on Abc, Hij, Prs, and Xyx streets. Detergent No. 3, intended for a different group of customers, should be directed only to stores on Def and Tuw streets. Similarly, the attractiveness of individual stores of all chains for all products was determined.
In this way, the analysis of data from the questionnaire provided the household chemical manufacturer with precise information allowing for the best use of the “purchasing potential” of people living in the area of interest.
However, it is not only manufacturers who can use the services of Claritas; the company will also point the right direction for retailers, for example. One large retailer was planning to reorganize its two chains. The larger one included about 150 discount-type stores across Poland, the smaller one – exclusive delicatessens. A detailed analysis of the potential of individual stores was to help in choosing which outlets from the cheap chain would be profitable to convert into more expensive stores – and perhaps vice versa.
The selection of stores targeted for profile changes was made by following the micromarketing data provided by Claritas. The geographical division into “Claritas Micro Kosmos” areas was used, each of which covers an average of 400 households and can be analyzed in terms of the number of residents, their age, and wealth. CMC areas located around stores belonging to both chains were used for the analysis.
The first step is to determine the reach areas of individual outlets. These areas are determined by the walking distance to the store (it is known that 80% of customers walk to do their shopping). The attractiveness of the store and obstacles such as rivers, busy roads, or railway tracks are also taken into account.
Next, two parameters are determined that define the value of individual outlets. These are: the “customer potential index” of each store, based on population density in the reach areas and the wealth level of residents, and the “competitiveness index” – the number of competing stores in the reach area of each outlet, taking into account the attractiveness of the competition.
After combining these two indicators, four groups of stores were obtained: low customer potential and high competitiveness, low customer potential and low competitiveness, high potential and high level of competitiveness, high potential and low competitiveness.
The last group consisted of stores whose profile could potentially be changed from a discount type to a luxury supermarket. For selected stores, an additional analysis of the age of customers living in the store’s reach area is carried out. This information is used to develop development plans for individual outlets. It is known that if a given area is inhabited by many families with small children, the assortment and shelf space allocated for a given product will be planned differently than if older people predominate among the residents.
As can be seen from the above example, the information available to micromarketing can be used both at the strategic level, when making decisions about store locations or decisions regarding the structure of retail chains, and at the operational level, facilitating the management of individual outlets.