Tag Archives: Geospatial

A brief guide to Geodemographic Customer Profiling

A geodemographic customer profile is a geographic marketing term used to describe the demographic grouping of customers who fall within a pre-defined geographic area, such as a retail location’s catchment area.

The profile should include the demographic fields that are relevant to the brand or product that is being marketed within the geographic area. Therefore a profile for a childrens’ clothing store would include age and life stage classifications in order to understand what portion of the target market are potential customers. Commonly used demographic fields include age, life stage, gender, education level, income groups, occupation types, dwelling types, or LSM fields. The segments chosen are also dependant on the available geocoded or spatial demographic database, ie if geocoded Census data were being used to generate the profile, then the demographic fields would be limited to the available geocoded data from the Census survey.

The resulting profile provides the breakdown of the population within the geographic area per segmentation field. For instance, the gender profile for the majority of geographic areas is 50% male and50% female. Clearly, gender is not particularly useful as a geodemographic segment.


Approximately 85% of all databases have a geographic element. Geocoding is the process of assigning latitude and longitude (x;y coordinates) to individual records of a database based on locational data such as physical adresses. Through this process is geospatial analysis enabled.

A geocoded database can be analysed within the electronic geospatial environment against other relevant sources of information based on geography.  This functionality is what we refer to as location intelligence.

As with all systems, technological or otherwise, the quality of the output is directly correlated with the quality of the input.  The unfortunate bald fact of the matter is that in South Africa,  compromised levels of literacy among the operational staff compliment means that organisational data that is collected at the operational level is often not clean, or easily geocoded.   This is why it is important to assess data collection processes, and if necessary structure them.  This may mean providing operational staff with predefined drop down boxes for the capture of physical address data.

In the meantime dirty data can be cleaned, and geocoding levels adapted to enable the geocoding of less-than-clean data.  The important thing is that organisations dont ignore this source of valuable organisational insights, as its in the internal data that streamlining, cost saving, and wastage eliminating potential is found.

Bespoke web-based GIS solutions damage the GIS industry

Unscrupulous slick sales people are doing damage to the GIS industry.  By selling quick fix smart phone apps claiming GIS capabilities, with no statistically verifiable data, in fact, with no spatial data whatsoever.  These charlatans are providing grossly averaged out findings that claim to be micro geographic.  On closer scrutiny, none of the data is geocoded or micro-geographic.  Neither is the digital marketing database that the said micro-geographic findings entice advertisers to purchase.   
Therefore a retailer looking for location based demographic data relating to their catchment area, are receiving non-geographic averages, and in purchasing “micro-geographic” customer database marketing, ie sms marketing to the consumers living within the vicinity of the store, are actually receiving a database of consumers within the broader geographic area, and can therefore expect little return on their investment, as this spend is not going to bring about a call to action to consumers living 5-20kms from a store, as opposed to a very real call to action that would be created if the consumers did live within 1-3kms of the location as claimed, given a real value proposition.
The advertiser purchasing this campaign may have little knowledge of the capabilities of a true Geographic Information System nor the power of truly geographic data, and micro-geographic marketing.  Then again, the sales people of this product, too, have as little knowledge.  And as there are few real measures of broad digital media effectiveness, it’s difficult to quantify the lack of response to such campaigns.  
 The uninformed advertiser assumes GIS and Location Intelligence cannot provide the solution to getting more bang for their buck.  Do not be mislead and misinformed.  Contact Spatial Insights as we can, in fact, accurately and scientifically profile micro-geographic catchment areas, as well as measure customer response, and target advertising and marketing messages through efficient media channels within the prescribed geographic catchments areas.

A New Perspective

A recent PwC report on the insurance industry has me thinking. The report outlines how Big Data and smart analytics can be used to generate business insights. More specifically, insights which lead to scenarios enabling the development of solutions which generate value.

Gone are the days when businesses thrive by developing products, push these into markets and simply return results. Increasing levels of customisation mean that businesses need to tap into this customer / user trend and deliver meaningful value.

The volume of data being generated by customers and business processes is growing exponentially, this is valuable data which contains useful insights. Michael Porter outlined in his seminal work Competitive Advantage that primary advantage is gained from either cost or product differentiation.

What if we added data insight as a third factor?

This means that seemingly meaningless data is mined and the findings built into the business process. In common practice this means looking at data in unusual ways, using tools not commonly brought into strategic discussions. One such tool is Geospatial Technology.

Geospatial aka “mapping” platforms provide the strategist the opportunity to view data in new ways. The ability to overlay data such as traffic flow, demographic information, disposable income levels, etc, opens a window to generate insights previously invisible. Data which has or shows potential to have a geospatial element can be viewed and manipulated using a geospatial modelling platform such as MapInfo Professional.

The team at Spatial Insights are able to scope any data available which has been generated by value producing processes and assess potential for real insight opportunities. If you have good data, we’ll model it and generate insights. By good data, we mean any data which possesses geospatial or geographic elements.

If you think there is something missing in your decision making and you need a new perspective, give the Spatial Insights team a call.