Robust Geospatial Data for Socio-Economic Analysis of Townships

Geospatial data sets provide granular information for the analysis of the socio-economic character of townships. The wealth of geospatial data available for townships includes media coverage, demographic estimates, income, shopping malls & retail outlets, crime data, economic, etc. This data allows for an understanding of each township’s characteristics and the development of targeted policies and market strategies.

Comprehensive data on consumer behaviour, demographics, and consumer expenditure is available for South Africa’s townships that covers over 4,000 square kilometers and includes 19 million adults in 532 major townships. Soweto, Tembisa, and Umlazi are three of the larger townships in South Africa with significant population growth and economic activity. Soweto is home to about 1.7 million people with 69% of the population being economically active. Tembisa is the second largest township in Gauteng, and Umlazi is the largest in KwaZulu-Natal and the sixth largest in South Africa.

The socio-economic characteristics of townships continues to change with a decline in household size and growth in single households, as an example. Marketers can look at data for multiple townships individually or in combination, instead of just one township, to understand market potential. Data can be used to develop and deliver to these markets, reaching the consumers in all townships.

Significant development is happening in townships with new luxury housing situated next to RDP style houses. Government in partnership with the private sector should seize the opportunities to develop schools, water projects, healthcare facilities, and retail centres, as an example.

The ShisaNyama market in South African townships has seen its expansive grow by 11% compared to the general South African increase of 7.6%. Marketers should find ways to develop and deliver to these markets, reaching the consumers in the townships, and using data to improve their offerings based on different areas of the country.

Data sets provide a comprehensive understanding of the socio-economic geography and consumer behavior in South African townships. Our township data is especially important to understanding the state of youth unemployment in the townships across South Africa. The data can be used to develop policies and interventions as well as deliver to these markets by understanding the interrelationship between supply, demand, accessibility, and consumption.

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