Analysis of catchment areas for the retail trade
Despite developing effective instruments, many companies still overestimate the size and quality of the catchment area of their traditional retail outlets, giving away valuable profits.
Position, location, catchment area – success factor no. 1
One of the basic prerequisites for optimising location decisions and planning market development strategies is knowing where my potential customers are, or, in other words, where the catchment area of my outlet lies.
The fact that the geographical location of a retail outlet has a certain significance for its chances of success is probably undisputed and well known, and not only among experts. Less known, however, is the answer to the question of what makes a location attractive for opening a retail store. No matter what the full answer may be, it will always revolve around the catchment area. The answers to the following questions, such as what kind of households they are, how many consumers and what kind of purchasing behaviour and consumption budgets they have, in which geographical areas my potential customers reside, can also be usefully pursued. When planning marketing measures for the retail business, an analysis of the catchment area is therefore essential. Finally, what is the basis for advertising measures, such as flyer distribution?
Let us start with a test
In order to get a feel for the systematisation range of catchment areas, a basic analysis is recommended. To perform this, take the number of weekly customers and compare it with the number of target households in the catchment area or with the number of weekly leaflets distributed in the catchment area. Run this simple test for all your stores. If the result is similar across all stores, you have a high degree of systematisation. If the factor differs greatly from store to store, it is always necessary to analyse it and carry out a smart systematisation of the store-specific catchment areas. Even after testing, your awareness of whether the identified catchment areas are too large or too small and whether they include their correct target households, is incomplete. However, this test does show whether the definition of catchment areas in your branch network is based on a systematic approach or whether it is defined completely arbitrarily.
How systematically are the catchment areas of your branches defined?
Return on investment – flyer example
But what are the benefits of such analyses and possible catchment area optimisation? Mostly a large portion of savings on missed advertising measures, more customers through more targeted marketing and confident expansion decisions. Many current studies also show that household advertising still has by far the greatest influence on visitor motivation, brand experience and sales. The analysis of catchment areas shows very clearly in which areas household advertising motivates customers to visit shops and in which areas it does not. Often the catchment areas are not optimally defined so that leaflets are distributed in streets and residential areas at high cost but have no effect there.
The IWD carried out over 1,500 analyses of catchment areas in 10 years and was able to save an average of 34% of household advertising costs for retail companies.
Newton, and what happened when the apple dropped
In 1931 William John Reilly published a 75-page paper in New York called “The Law of Retail Gravitation”. Reilly explained spatial shopping behaviour by referring to Newton’s gravitational theory. He attempted to determine the attractiveness of a certain location mathematically and to predict purchasing behaviour of consumers. In his series of empirical studies, it was confirmed that population size and distance are decisive factors for a catchment area. With his “Law of Retail Gravitation”, Reilly developed the first theory of a central theme that has a decisive influence on the success of a traditional retail business or an agglomeration of retail businesses. Several other theories, grounded in maths, followed later, emphasising the same weak points, where a precise calculation of realistic catchment areas is a struggle, unless one assumes that all geographical areas to be examined would be without a differentiated competitive situation, have the same sales areas, similar infrastructure, range of goods and degree of agglomeration. Different consumer preferences and regional purchasing behaviour were not considered in this model.
Catchment area measurement today
A high investment risk of a new retail location as well as considerable scattering losses of the advertising measures, that can occur if the catchment area is not precisely defined, make a systematically valid demarcation procedure for catchment areas in the retail trade based on real values extremely important. So, to stay with Isaac Newton, it was time for another apple to fall.
What approaches have been developed in recent years to delimit catchment areas? The latest version of catchment area analysis is based on the origin polling of customers, using consumer surveys in the shop. For this purpose, various survey forms are currently used.
If the origin of the customers can be recorded in a more targeted manner, catchment areas can be defined more precisely and scattering losses minimised.
The German postal codes record is certainly the most imprecise method, since postal code areas are very large geographically with high household numbers. If this data is utilised for analysis at all, it can only be used by retailers with very large catchment areas, i.e. whose market area extends over several cities and municipalities. This is usually reserved for larger furniture or DIY stores. The situation is different in the UK and the Netherlands, for instance, where postcode areas are relatively small and comprise only a few households.
Another way of recording customer origin is to use individual geographic clusters, which are recorded on a city map. In this instance, a map is graphically prepared with numbered clusters. The customer can indicate directly on the city map, in which of the geographical clusters they live when surveyed in store. This method is already much more accurate than the postal code survey, since the clusters represent smaller area units.
Customer origin record at street level
However, for traditional retail outlets with a medium or small catchment area, which are more common, the IWD recommends that origin enquiries be made at street and street section level. Here, professional geoinformation systems provide street lists and lists of street sections with the necessary data basis to conduct a customer survey. The street and geodata is provided within the questionnaire on a smartphone or tablet, so that street names can be found quickly and recorded as part of the customer survey.
Analysing the catchment area at the street and street section level is very precise, providing a very detailed database even after the data is processed. In this way, geographical analyses of sales or distribution areas for optimising household advertising can be mapped very precisely at a later stage.
Street-specific sales forecast
If the origin data can be matched with other behaviour-relevant indicators, the data allows for a sales forecast that can be calculated for each geographical unit as required – i.e. even for the smallest geographical level, the street or street section level. In other words, by means of this catchment area analysis method, as used by the IWD, the expected turnover can be effectively forecast with a very small margin of error for the retail business concerned per each street where their customers reside.
Street-specific CEV evaluation – determination of characteristic values
The advertising pressure that is exerted on various geographical units affects the sales potential to be capitalised. There are streets and geographical clusters where attractive sales can be achieved even with little advertising pressure. The IWD analyses geographical areas where only 10% of the advertising budget is invested but 70% of the turnover is generated. In this case, the contribution margin, taking into account the advertising media used and the capitalised purchase revenues, is positive. However, the analysis also shows geographical units where significant sales can only be achieved with increased advertising pressure and thus high advertising budgets. These areas tend to show negative contribution margins, as high advertising expenses are disproportionate to the low sales potential. To evaluate the attractiveness of each individual street and their subsequent inclusion into the primary and secondary catchment area, the IWD developed a special characteristic value. The CEV (Cluster Effectiveness Value) enables evaluation of streets, roads or otherwise defined geographical units with regard to their ratio of advertising budget to sales potential. If the CEV is calculated for all streets and street sections from which the store’s customers come, the result is a street ranking in terms of sales attractiveness.
Data basis for future location decisions
The information advantage gained by analysing the catchment areas of existing retail locations serves as a meaningful data basis for further location decisions. If the data on the catchment areas of existing properties is used to generate a standard or, preferably, a GIS database over time, high-quality forecasts for further location evaluations and location planning can be made. In addition, the data allows for significant optimisation in the planning of market development strategies.