This post is a part of an ongoing series about launching Selectivv SaaS solution Viewer 2.0
Go to Selectivv Viewer dedicated website
Catchment area is an influence zone of a particular product, store, service etc. Basically, it means area, from which it attracts a population that uses its services, offers etc. When it comes to physical facility location, catchment area can be defined based upon a number of factors including distance to the store location, actual travel time, geographic boundaries or population within the catchment.
On measuring and analyzing catchment area based on mobile data and proprietary solutions we wrote by the occasion of Galeria Młociny opening (research on its influence on others shopping malls in the capital) or the Congress of Market and Opinion Researchers in Warsaw (research on inhabitants of Krzyki district in Wrocław).
The analysis of the zone of influence continues to be determined from the methods based on customer research to theoretical mathematical models and techniques using elements of GIS. Also, the implementation of the particular solution depends on the context and audience we would like to analyze. The most common ways to determine catchment area are different kinds of customer surveys - eg. collecting postcodes or addresses (eg. based on loyalty programs) while check-out. In the first case we should remember about the range: one zip code - sometimes covers several streets in large cities, in other cases it might be a few small towns. The interesting procedure of simple data collection, with some problems it causes, for analyzing catchment area is described here. Loyalty programs demand user registration. Another interesting method is a license plate recognition system - for consideration to shopping malls rather than particular stores. Other suitable methods are based on analyzing existing infrastructure and transport options, distance, and travel time. There are even more advanced solutions including combination of survey, location parameters, customer demography…
Mentioned solutions have been processed for a very long time. They have been tested on many examples and yes, sometimes they are enough. According to technology development they seemed to be too time and money consuming nowadays. Why to ask user where he comes from? To be very precise we need not only zip code, which covers different area, but also address (street and building number) - not so easy to get from the user. Loyalty program covers only customers who will approve it and make purchase. Basically, we cannot determine users’ working and home zones. Anyway - we are still unable to analyze if they visit our competition… When it comes to methods based on location, distance and travel time - it’s based on location, distance and travel time not on user, his interests and behaviour. Last but not least, time & effort to get & process the data are more significant in this case.
The fundamental information about Selecitvv Viewer 2.0, it's functioning and options are here. Below you can read about determining the catchment area thanks to it.
So, what it looks like when it comes to relying on technology? While having the location to analyze, there are two things to notice: radius (50 / 250 / 500 / 750 m) and time (last year / last quarter / last month / last week).Radius defines the area around typed address from where we want to analyze users. Time range defines period which we are interested in. Other words: when we choose the location “A” with 250 m radius and time range “last year” we will analyze users who were present within 250 meters of the point “A” during the last year.
Choosing the radius depends on few factors like building density, proximity to road infrastructure, general location and purposes. For example, to define potential customers, we don’t have to restrict ourselves to 50 meters radius. A good idea is to consider 500-750 m. Also, the time matters - choosing last year or last quarter we enlarge the database of potential customers getting marketing access to more users. And of course, at this point, in the “analysis” section, we choose “catchment”.
As a result, we receive map with data points marked as red dots. On default in “select hour range” is set up “All day”. It means, that on the map, we receive visualization of the users locations from demanded area during the whole day. Other options we have are: Night (20-8) and Day (8-20). Technically, choosing one of them will cause receiving representation of locations where “our” users are during the night hours or day hours. Including behavioural predictions - we receive their home and working zones.
At this point, we see that Viewer is designed for long-term analysis rather than a one- or two-day event. For short-term purposes, Geotrapping® or Wifitrapping have better performances. By the way, Selectivv Viewer 2.0 allows ordering Geotrapping® for a particular location directly through the dashboard. But on this, as well as application of the tool in different sectors, we will write soon on.
