Analyze Information of Your Points of Sale and Customers in Geographical Form

Analyze Information of Your Points of Sale and Customers in Geographical Form

Summary

In this article we will use the analysis capability of our CRM, especially the GIS module in connection with Virtual Modeler to analyze sales and customer statistics geographically.

In the CRM there is a lot of very important information about customers, points of sale, products sold, business opportunities and much more critical information to improve the commercial performance of each company. To this information we can add other information available in Virtual Modeler Server, such as statistical and census information. With this set of data we can perform analyzes such as the following:

  • Analyze the best areas to open a new branch or franchise
  • Determine if the different zones are underutilized or not correctly distributed
  • Analyze the density of customers and the influence ranges of each point of sale
  • Understand patterns of geographical distribution and consumption of different products and services
  • If you have data, you can analyze the geographical variables of the competition

 

Analysis of Commercial Indicators

Thanks to the flexible and powerful architecture of Virtual Modeler Server </ em> </ strong> and the connector for demographic information, sociodemographic metrics can be used to compare with company-specific indicators.

With this technology you can use demographic variables such as:

  • Population Density (Next Illustration)

  • Income level (Next illustration)

  • Average age of the population
  • Level of building construction
  • Educational level
  • Etc.

Among others and compare them with indicators of the company, such as:

  • Sales per sales point/branch/franchise or zone
  • Utility by area
  • Delivery times
  • Complaints, complaints, quality of customer service
  • Competition coverage
  • Delinquency
  • Etc.

 

Using this tool you can discover geographical patterns, if your geographic coverage is well distributed, you can determine optimal locations for the opening of new own or franchised premises, determine underexploited areas for certain products and any other type of situation arising from the dispersion and geographic analysis of information.

Location Analysis and Geographical Coverage of Franchises

In order to carry out these analyzes we can base ourselves on demographic information as described in the previous point and detect areas where there is high population density and few sales points (or of insufficient size or scope), other demographic data can also be analyzed as a level of income, level of study, quality of housing to determine the economic segment of potential customers of a certain place.

In Figure 3 you can see a map of heat or density, where you can analyze the density of a certain variable, for example, in this case you can analyze the number of customers or the purchase volume of each of them. Other variables can also be analyzed, such as the number of complaints or changes in products due to poor quality.

This information can be combined with graphs indicating the geographic location and average sale level of the points of sale, as can be seen in Figure 4, and intuitively determine areas where the current geographic coverage is insufficient or poorly distributed.

Another very interesting visualization can be achieved with the group or bubble map, as shown in Figure 5, which shows the number of occurrences of a given event within each zone.

This type of visualization allows analyzing information in a way that is impossible to achieve with other analysis tools. Tabular reports only show detailed information line by line and conventional charts can show consolidated and grouped information, but it is very difficult to identify and determine certain common patterns that are only available in a map view. Although some reporting tools allow the visualization of points in a map, no account has the possibility of analyzing several variables at the same time and superimposing several layers of information simultaneously.

Through this technology it is also possible to analyze indicators or composite ratios that facilitate the visualization of complex information and help the correct decision making. For ex. In Figure 6 below, you can see the indicator “Density of Sales per Dweller” that is calculated as a combination of the amount of sales that the company has in each zone, taking into account the number of people and the level of income of each zone.

With these indicators you can determine the optimal locations to position premises or expand geographically.

From the general to the particular

In addition to the capabilities of analysis and general and high-level visualization, Virtual Modeler also allows you to reach the operational and particular detail necessary to make quick and efficient decisions. By zooming the map you can obtain details of individual data, this way it is possible, during the same analysis and without losing the focus, to obtain a general view of the situation on a large scale, as well as detailed information of each case and particular situation (see Figure 7). All this without losing sight of the security of the data and the access allowed for each role of the company.

In the same way and without needing to leave the tool or lose focus of the work that is being done, the software allows to search for information based on any criteria, locate the results of those searches on the map, view individual data of each record and consult related information. For example, as can be seen in Figure 8, a search can be made of all the customers that a Point of Sale serves, see them as a heat map and in this way analyze the coverage and geographical interference that the PV has; and at the same time, access individual information of the Point of Sale and its customers.

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