Expanding a retail footprint in South Africa’s dynamic, and as some would say, saturating market requires more than intuition or simple access to population statistics – it demands a deep understanding of consumer insights. Consumer data from the Marketing All Product Survey (MAPS) and datasets from GeoScope South Africa on Living Standard Measures, shopping malls & retail chains, equip retailers with a granular understanding of the market. Armed with these insights, retail and marketing professionals can pinpoint who their customers are, where to find them, what those customers want, and how to find the most optimal locations while outmanoeuvring competitors. This data-driven approach is critical for success in areas ranging from market segmentation and location planning to produce targeted and competitive benchmarking in the South African retail market. The sections below examine why consumer data is crucial for each of these facets and how leading retailers worldwide utilise consumer data to inform their expansion strategies.
Market Segmentation & Targeting
Understanding the diverse South African consumer landscape is the first step in any expansion strategy. Large-scale consumer surveys, such as MAPS (the modern successor to the old AMPS survey), provide a single source and the most comprehensive data on consumer behaviour, covering demographics, product ownership, brand usage, media consumption, and more. This rich data allows retailers to categorise the market into meaningful segments – for example, by income, lifestyle, or media habits – and tailor their offerings accordingly. More importantly, it allows retailers to segment the market more holistically, taking into consideration who buys their product, when and where, and how much they spend and how frequently.
Identifying High-Value Segments
Retailers use data to profile customer groups by factors like age, income, or living standards. In South Africa, the classic Living Standards Measure (LSM) or newer Socio-Economic Measure (SEM) segments are commonly used to distinguish low, middle, and high-income consumers. MAPS data, for instance, provides updated LSM/SEM breakdowns, revealing where affluent shoppers or emerging middle-class pockets are located. This helps companies decide which formats or product lines to deploy in different areas. Major retail chains historically even defined their target markets by LSM group – e.g. Shoprite focusing on mass-market LSM 1–6, Pick n Pay on 1–8, while more premium brands like Woolworths aimed at LSM 6–10. Such segmentation ensures each retail brand speaks to the right audience with the right value proposition.
GeoScope provides detailed data and mapping of South Africa’s Living Standards Measures (LSMs). Historically, LSM was the country’s most widely used consumer segmentation by marketers, advertising agencies, media owners, and service providers. Our LSM data creates a continuum of wealth that clearly shows how the nation’s socio-economic landscape changes from year to year and provides a comprehensive longitudinal view of changes in wealth and poverty at a granular level in South Africa. The map below shows LSM data from the 2023 MAPS data and illustrates how provinces differ from one another, reflecting Impoverished regions of the country and reflecting the dynamics of the country in terms of population concentrations, urban versus rural areas. Using advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques, we estimate the number of households in each of the ten LSM categories at fine geographic levels (such as enumeration areas), which reveals the distribution of these socio-economic groups across local communities, districts and provinces.
As the GIS partner of the Market Research Foundation (MRF), Geoscope sources its LSM data from the nationally representative Marketing All Product Survey (MAPS) each year. Because of MAPS’s rigorous, area-based sample design, it is the only survey that allows LSM data and, more generally, consumer data, to be accurately modelled and mapped at such a granular level. Our LSM dataset includes each area’s dominant LSM group as well as the number and percentage of households in every LSM class. This data is updated annually to provide trend analyses along with comparisons to national averages.
We also offer the latest Socio-Economic Measure (SEM) data at granular geographic levels as an additional dataset for deeper insights into consumer segments. While the LSM focuses on household asset ownership and access to services, the Socio-Economic Measure (SEM) uses broader indicators such as education, income, and living conditions to better reflect social status and inequality in South Africa’s modern context. The SEM map below again shows the dynamics of the population at a provincial level, distinguishing regions from one another and reflecting on the wealth-poverty continuum that exists in South Africa. It also shows how the two segmentations show differing and yet similar aspects of South Africa’s consumer landscape. This information is delivered as geospatial data or through an interactive mapping platform, giving clients a visual view of which LSM or SEM group dominates in each area and allowing them to overlay other datasets such as demographics, income, expenditure, product sales, or even their own customer data. This provides the most comprehensive local market profiling data needed for strategic decision-making.
Tailoring Marketing and Product Strategies
With a clear picture of each segment’s behaviour, retailers can align marketing messages and product assortments to consumer needs. For example, MAPS reveals not just who the consumers are but also what they buy and where they shop. It tracks purchasing behaviour, brand loyalty, and even which retail outlets or malls consumers visit most. A retailer can see if a target segment (say, urban millennials or rural families) favours certain product categories or brands and then emphasise those in stores serving that segment. Media consumption data from MAPS also guides retailers on how to reach each segment – whether via social media, radio, or in-mall advertising. The result is a more personalised, segment-specific strategy that can increase customer resonance in each market niche.
GeoMAPS – Spatialising Consumer Insight for Strategic Decision-Making
GeoMAPS is GeoScope’s advanced geospatial data that transforms MAPS data into spatialized consumer intelligence. By integrating survey data with precise geographic boundaries, GeoMAPS allows users to visualise and analyse consumer behaviour, market demand, and socio-economic patterns across South Africa – right down to the neighbourhood and township level. Using AI and ML techniques, GeoMAPS models MAPS variables to a local area by integrating secondary datasets (such as 2023 demographics) to create a statistical relationship to generate reliable insights even in areas where surveys weren’t conducted.
These results are accessed as geospatial data for use in GIS or displayed in a web mapping environment, where clients can interactively explore thematic maps, filter dashboards, and layer additional datasets such as demographics, income, expenditure, or retail outlets. In essence, GeoMAPS makes marketing and consumer data location-intelligent – empowering retailers, brands, and planners to identify where their target markets live, how they behave, and where the best opportunities lie for retail network optimisation, targeted marketing, and strategic investment
Location Planning & Site Selection
Deciding where to open a new store or branch is one of the most crucial expansion decisions – and consumer data is an indispensable compass for location planning. South Africa’s geography of retail includes everything from high-end malls to informal township markets, and data helps map this terrain so retailers can position themselves optimally. GeoScope specialises in retail network planning that guides retailers on network expansion, relocation, or even rationalising their store network. A data-driven and geospatial modelled approach is used for retail network optimisation, combining demographic, consumer, retail supply points and accessibility modelling to define the optimum size, location, and structure of a client’s retail footprint.
Using trade-area analysis, the company determines customers’ travel time to reach stores of different sizes, types, and in different localities. Trade areas are defined using different approaches, including the geocoding of a brand’s customer data harvested from internal account databases, conducting intercept surveys at retail outlets or using capacity and travel time constraints to define the unique market that outlets serve. A trip-rank analysis is also used to show how many competing outlets customers travel past, and how far they are willing to travel to reach a store. This develops a precise understanding of customer trade areas and the market size. Both Greenfield and Brownfield strategies are employed – the former identifies ideal new store sites in untapped markets. The latter refines existing networks by analysing current outlets, competitor proximity, and financial performance to guide expansion, reduction, or relocation decisions.
GeoScope integrates accessibility modelling and spatial distribution network analysis (SDNA) software to simulate and visualise optimal service coverage, ensuring that each outlet is positioned to maximise market share, accessibility, and return on investment. By fusing GIS intelligence, consumer data, and strategic modelling, GeoScope delivers a comprehensive, spatialised solution that empowers retailers to build efficient, profitable, and customer-centric networks across South Africa.
In conclusion, South Africa’s retail expansion success increasingly depends on how effectively data is spatialised, analysed, and applied. International best practice shows that global leaders like Walmart, Tesco, and Carrefour rely on geospatial analytics, consumer segmentation, and machine learning models to drive store placement, assortment optimisation, and market entry – the same principles now being applied locally through tools such as GeoScope’s GeoMAPS and retail network optimisation frameworks. By combining the Marketing All Product Survey (MAPS) with advanced AI- and GIS-based modelling, GeoScope translates national consumer insight into actionable local intelligence, pinpointing not just who the consumer is, but where opportunity lies. This fusion of consumer data, spatial analytics, and strategic foresight empowers South African retailers to move beyond intuition and toward precision retailing – building networks that are efficient, profitable, and aligned with evolving consumer realities. In an era where data is the new retail currency, those who map their strategies with intelligence will define the next wave of sustainable growth across South Africa’s retail landscape.
