This time a less practical but a bit more theoretical and hopefully still useful post on GIS or Geographic Information Systems. The audience of this post is the SME owner, the IT manager or the application manager who is not very familiar on GIS and we do stress the fact some of the presented functionality is not entirely new.
Smart selection of nearest objects
We all know we can visualize data on a map and most of us have heard already of a spatial query. Retrieving the nearest objects is undoubtedly the most basic spatial query but to make our selection of customers a bit more intelligent, we decided to work with 2 layers.
One layer represents the nearest object (customer) and a second layer represents the traffic (real time information, available for Belgium, available for Australia). Please note another feature. We allow the end-user to select the customers he’ll visit by drawing a polygon on the map and this information will be fed back in the ERP or CRM system. So to summarize, our sales representative decides to visit two customers, not easily accessible at the moment, another time and the CRM system (being now up to date) will notify the sales accordingly on his next visit.
And to help our sales representative a little more we foresee an interface with Google Places to retrieve the opening hours of every shop and we will guide our sales representative through the communes by providing the walking instructions when he decides to park his car and to walk to the remaining part.
Complex? Not at all! Useful? Quite likely since this functionality is available from every smartphone and consequently available immediately for the sales representative who is actually on the road. Be aware as well one can decide, to enhance the visualized data, to retrieve additional information from the ERP or CRM system (by example additional customer details)!
Heat map and Multiple Layers
Following map is another example of retrieval of nearest objects but location is Sydney and this time we added a heat map. A heat map is a graphical representation of data where the individual values are used to display areas.
So on the one hand we show all our store chains but on the other hand we visualize all the customers with a heat map and we allow to clearly verify where most of our customers are located. Be aware we could, very easily add additional layers like sales by retrieving information from other tables!
Please note, one is able to visualize the areas where most customers are located a different way as well and this by clustering markers:
Please find below another example of a useful map designed with CartoDB. One is able to display, and this with a very limited effort, four different items and this map only shows the very basic available functionality.
So in a nutshell. We believe GIS offers a plethora of possibilities and this …. at a very affordable cost.
Comments or suggestions? Don’t hesitate to inform us. We are pleased to confirm the next article will be covering some other GIS related functionality like optimizing routes, tracking services or the influence of nearby competitive branches on your own local branch (so called location analysis or location analytics) but please make suggestions as well to allow us to elaborate on your ideas. In the long run we plan to write another article on GIS features and will explain concepts like the Voronoi diagram or the catchment area.