Revolutionising retail store planning in SA’s clothing industry

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These stores will often be located in commercial centres and a more recent trend is for clothing brands to use new store models such as using containers that were launched in townships by Mr. Price in 2020.

This they say is because shoppers are increasingly wanting to shop closer to home after the Covid-19 pandemic in 2020. What this store model also does is that it allows Mr. Price to be in close proximity to their customers and provide a store that caters for a niche market.

Another critical development in the clothing industry is the growth of online shopping that caters for a much larger market area. The question that must be asked is – will brands have to rethink their physical store and retail network strategies?

Key online shopping trends in the clothing industry

To do this requires brands to understand the distribution and concentration of online shopping relative to shoppers buying their clothes from physical stores. This information is only available through nationally representative surveys such as the Marketing All Product Survey (MAPS) from the Marketing Research Foundation (MRF).

Although the total online shopping market in South Africa in 2023 is relatively small at close to 18%, adults buying clothes online is at 15%. The bar chart shows that total online shopping has declined since 2020, while the online clothing purchases have increased from 7% in 2020.

This in part can be attributed to the Shein clothing retailer entering the market in 2020 and rising to become the market leader in online children, men’s and women’s clothing.

Figure 1: Total online and cloting online shopping from 2020 to 2023 in South Africa. Image supplied

It is not surprising that the provinces with the largest economically active populations is where there is a higher proportion of online shopping for clothes. Gauteng has 18% of the online clothes shopping market compared to 16% in the KwaZulu-Natal and 15% in Western Cape.

Gauteng is the most urbanised province in the country with the highest number of high per capita income individuals who have greater access to the internet. With people being busy and facing high levels of traffic congestion, online shopping for clothes offers consumers convenient and time saving.

In terms of pure numbers, Gauteng leads with over 500,000 adults buying clothes online with over 200,000 online clothes shoppers in KwaZulu-Natal and Western Cape. The dominance of online shopping for clothes in South Africa remains distinctly in LSMs 9 and 10.

Knowing where these online shoppers reside or work is vitally important in making decisions about where to open retail stores and equally as important, whether they shop online for their brand’s clothes.

When it comes to men's in-store shopping, the three top brands are Markhams, Sportscene and Mr Price. Mr. Price is the outright leader when it comes to women's retail store clothing followed by Truworths. Ackermans leads clothing retailers within stores for children's clothing followed closely by Mr Price. Knowing who is buying your brand's clothing and whether it is instore or online is crucial in making decisions about where to locate new stores. By spatializing the MAPS consumer data, it is possible to get a clear understanding of these factors.

Enhancing retail store planning with advanced analytics and data-driven insights

The use of accessibility modelling to optimally locate retail stores within the clothing industry is needed but is not happening for different reasons.

Firstly, very few clothing retailers have access to data on their instore and online markets for the whole of South Africa and secondly, they don’t have access to this data in a geospatial format at a granular level.

More importantly, access to technology and methods to holistically look at their retail store network considering the location of the existing stores, competitor stores, preferred sites (eg shopping malls) and key attraction points is limited. Furthermore, clothing retailers do not have the necessary approaches to decide if they should expand, optimise, or reduce the store network.

Using a combination of Greenfield and Brownfield approaches it is possible for retailers to make informed decisions as to whether there is sufficient market to expand their store network.
The Greenfields approach uses two key parameters of number of customers required for a store to be financially viable and the minimum travel time to reach the target market. This is needed to define the optimum number and location of retail stores.

In contrast, the Brownfields approach looks at multiple parameters including location of existing and competitors stores as well as preferred sites. Retailers should expand their network when their number of existing stores is below the market potential considering all factors including competition and available floor space.

In many instances, retailers have opened their stores years ago and the market has shifted requiring them to look at relocating existing stores to more optimum locations. With the economic downturn and the difficulties that several clothing brands have experienced in recent years, requires them to make informed decisions about which stores to close to ensure their long term sustainability.

In most instances, the default is to close those stores that are not achieving their target revenues. This is often a consequence of stores from the same brand being opened in close proximity and cannibalising their neighbours market. The closing of retail stores that are optimally located but not achieving their income targets, places significant stress on the entire store network.

Key considerations for retail store planning in the clothing industry

What has been described above is the basics needed to do proper retail store planning in the clothing industry. It requires access to geospatial data on the location of existing stores, their competitors, location of preferred sites for new stores and the distribution of their target market. The use of spatial features such as hexagonal grids, Uber grids or strategic areas to represent market areas and the flow of the consumers from where they live or work to potential store sites using different mode of transport (eg motor vehicle, walk, train) is what makes the use of accessibility modelling unique.

Recent research in the clothing industry has shown that there are distinctive factors that need to be taken into consideration in making decisions about where to locate new stores. This is determined by looking at data associated with existing stores such as their turnover.

Clothing retail stores are often in prime sites when they are clustered with other clothing brands in lifestyle malls where the cost of floor space is reasonable, there are several shopping malls in close proximity and access to those locations is optimum. Two examples of such locations include Woodmead Retail Mart in Gauteng and Kenilworth Access Park in the Cape Peninsula.

Another important parameter is locating near other stores that attract similar customers, which can only be determined through the analysis of consumer data such as that in MAPS.

Economic theory is the basis of what has been described above. Without having this understanding in combination with the data and methods, prevents the sustainable development of retail store networks in the clothing industry. Retailers may argue that they have been planning their retail networks for decades and it has stood them in good stead.

This may be the case but when there is a significant increase in competition in the market or an economic downturn, these methods will not enable further sustainable development of a brand’s store network.