At the core of socio-economic segmentation and the socio economic measure (SEM) cluster model is the precision and agility needed to identify people with the potential to become purchasers or even existing purchasers with the potential to switch brands. This is always a matter of balancing out the promise implied by a higher incidence of purchase and potential volume of purchase.
Incoming ratios in household income
Household income (HHI) provides the most illustrative assessment of purchasing power across the have and have-not divide in South Africa.
The PPP (people, products and platforms) Fusion Study 2020 by the PRC, BRC and Nielsen reports an average HHI of R13,391. At R3,989 the traditional market known as SEM_C1 has the lowest HHI and although it represents 11,4% of all households it accounts for only 3% of the total monthly HHI in South Africa. This converts into a power ratio of ƒ0,3 (total income % ÷ total household %).
There is a progressive increase in earning power, and implied purchasing power, as we track up the SEM scale.
The middle market, referenced as SEM_C3 (R9114) is below and the upper middle market of SEM_C4 (R18,510) above the HHI norm. This relative per capita contribution is reflected in the shifting segment power ratios (SEM_C3 = ƒ0,7 and SEM_C4 = ƒ1,4). With respect to income, the midpoint of inflection for the SEM model occurs at that point where SEM_C3 transitions into SEM_C4: between the 65th and the 66th percentile.
Hyper link between employment and education
There is a strong predictive correlation between employment status and earning power. This module in this Market Segmentation South Africa series applies the broader definition of unemployment as being all those who are not in paid employment or self-employment but who are currently available, rather than the government's narrow definition of unemployment which excludes those who are not actively seeking jobs.
Over 50% of adults in SEM_C1 (traditional market) and SEM_C2 (transitional market) are unemployed and only one in every four adults works full or part time. What is particularly alarming is that when we interrogate the data for youth (age 15-24 excluding learners) 81% in SEM_C1 are unemployed. Compared to a statistic of only 24% youth unemployment in SEM_C5 (elite market). The enormity of this challenge at a household level represents the most pressing task for the South African economy.
The link between education and employment is most evident. In SEM_C5, 85% of adults have completed their schooling and 42% have a post-matric tertiary qualification of some kind. Employment is at its zenith (70%) amongst this well-educated tertiary qualification group. This goes a long way to explaining the unrelenting emphasis on access to University education in less-affluent communities.
As an alternative to full-time or part-time employment, the informal economy dominates many sectors of the market. Only 4,6% of all South Africans are self-employed (9,7% in SEM_C5) but of these 85% operate in the informal sector. In SEM_C1 and SEM_C2 92% of all people who are ‘self-employed’ operate in the informal sector. This informal-sector orientation is also reflected by the low levels of formal banking in SEM_C1 as only 51% of people in SEM_C1 are banked, compared to 92% in SEM_C5.
In the lowest SEM segment one out of every three adults (35%) is dependent on Sassa (South African Social Security Agency) social grants for survival.
Big click to online shopping
A look into current shopping habits confirms the recent impact of online shopping on the local retail market. Almost one in 10 South Africans (8,7%) have shopped online in the past month. At this stage, two-thirds (69%) of all those online shoppers in the country are found in SEM_C4 and SEM_C5, and in this top cluster, 27,9% of people are monthly online shoppers. This has huge implications for advertising and media strategy in 2021.
What we also see in SEM data is that segmentation for media strategy is more often than not a trade-off between targeting wealthy ‘high-incidence’ segments and the middle market that invariably offers the largest volume of purchase. Analysis of a typical household FMW (fridge/microwave/washing machine) appliance mix illustrates this point. SEM_C4 and SEM_C5 will always have the highest FMW incidence but SEM_C3 accounts for 41% of all FMW appliances in South Africa. SEM_C2 accounts for 38% more FMW appliances than SEM_C5.
The implication of such dynamics is that advertising and media strategists need to go beyond the traditional pitch it high and let it trickle down approach. Brand custodians must recognise that there is a highly viable and active market outside of high-end households in Gauteng, Cape Town and eThekwini – and much more emphasis from advertisers should be placed on relative pricing and deep distribution beyond the top two SEM clusters.
It is possible to perfect purchasing power ratios but this needs a media strategy and buying team with the experience to cut through the clutter of substantial market data and pinpoint the best audience fit for a business - as it is only when we reach this point - that we begin to talk about ultimate purchasing power.
In the next segment of this Blog Series For Marketers, we review products in South Africa.
About the Ebony+Ivory Marketing Segmentation South Africa Series
Drawing data and insights from the most recently published industry database Pams_2019 (released April 2020) and the Nielsen Fusion Study 2020 (released November_2020), we interrogate the SEM model through four lenses. People and Places, Purchasing Power, Products and Platforms.