Emerging markets present large opportunities for multinational companies. However, uncertainty and high variability pose challenges to developing confident growth strategies.
The Canback special report argues that income distribution data holds the key towards a detailed and nuanced understanding of market dynamics.
With stagnating growth across markets and the recent credit downgrade in South Africa, multinational companies are scaling back their search for growth opportunities in emerging markets. The report notes HSBC’s withdrawal from Brazil and Turkey in 2015, plus Nestlé’s scaling back in Africa in the same year as two notable examples.
“How to identify, quantify and capture market potential in emerging economies is the key question for multinationals,” says Dr Staffan Canback, Managing Director of Canback.
The income distribution data allows companies to accurately assess potential opportunities and prioritise market expansion. While tapping into these opportunities can be challenging, companies can look to income distribution data for a deeper understanding of emerging-market dynamics. The same data can be interpreted to inform risk management and mitigating strategies as well as understanding new customer segments for product reach expansion.
The report shows that subnational differences and the breakdown of different income brackets across geographies play a key role in identifying market opportunity.
Dr Canback says, “We show how predictive models can leverage income distribution data to provide more accurate and actionable results for multinationals looking to convert potential business in emerging markets”.
Quantifying the opportunity
The report’s Triple-A framework provides a guide for companies assessing market opportunities. The triangular approach begins with the addressable market, which contains all consumers within the relevant demographic profile and income bracket. The framework follows with the available market, which is the representation of the market potential in areas where the product is distributed, and concludes with the actual market, which details what people truly consume.
Therefore, to understand market potential, a company needs to be able to quantify the addressable population. Income distribution is more effective than an aggregated income average. In emerging economies, a large subset of the population cannot afford to purchase a product or service regardless of whether they would like to. This contrasts with consumers in affluent countries, who can largely choose to purchase any good if they accept trade-offs.
In addition, the report indicates that emerging countries tend to see a larger income disparity between rural and urban area, with a greater share of higher-income households concentrated in cities.
“Income distribution data is useful for companies seeking to understand how to prioritise and capitalise on market opportunities. The relative growth of different socioeconomic classes can vary greatly from overall economic growth, which profoundly, impacts on market and growth strategies,” says Dr Canback.
Predictive models in emerging markets
Executives and marketers often look to predictive modelling to combine information about trends and achieve a cohesive picture of the market landscape. The models provide a detailed, quantified view of where and when opportunities will arise in the future, providing a springboard for executive action. Income distribution data can be incorporated into predictive models for a more detailed understanding of market dynamics.
“However, these market sizing models can be augmented to include factors outside income. Additional variables come in two layers: the first includes other macro data covering industry and trade dynamics such as category data, marketing spend or distribution coverage and the second covers micro data such as insights generated from consumer surveys, for example, usage and attitude surveys”, adds Dr Canback.
Income distribution data allows companies to identify and prioritize opportunities by providing an accurate view of the addressable population, in terms of both socioeconomic level and subnational distribution. The approach provides insights into changing consumer dynamics within a market, allowing for targeted portfolio strategies. Income distribution data provides the foundation for demand models that then take into account additional macro and micro factors, informing the development of a coherent global strategy, the report concludes.