The current emerging and developing markets put almost 70 to 80 per cent of global domestic product by the year 2030. This is on an accounting spree for two-thirds of global growth consumer expenditure which constantly puts forward strong consumer goods companies onto hold. But on the contrary, quantifying several opportunities and strategy building is not an easy task.
Researching and using data from a lot of growing markets, several things come to accounts such as definitions, differences and business environments. When dissecting these, the methodology and standard definition hold a key aspect.
There are processes which one can implement to learn to grow with emerging market research data.
The quality testing.
Data quality can be unreliable at times. The reason can be several, methodologies which are lapsed and even technical aspects affecting the same. Additionally, political bias ideas and corruption even append to the process. Therefore, testing the market research data qualities lessens the risks and further complications, easing the process of decision-making.
Furthermore, comparing different figures in a demographic and economic profile can also be helpful in tacking the values.
When data available from market research portals becomes unrealistic, proxies come to picture to give a detailing on the quality of data. The proxies get a design according to the prevailing context of a particular market. Thus, when the data propelling is not available, one can rely on the proxies for a better idea of the market scenario.
Examples on the proxies include the data on possession of durable, urbanization and education. This serves as a good representative for the income data, specifically sizing different classes of income. Furthermore, annual disposable income can be put on analysis by using the GDP structure and consumer expenditures process.
Proceed with a timeline!
When surveys and market research get on track, they are made to carry out in altogether different intervals. This process puts on a particular problem when one tries to obtain information about fast and evolving emerging market trends. What holds the market stiff within a decade can never be the same in the current market. Thus, when comparing similar countries and data sets, a timeline on varying data can be largely helpful.
Market Research on a Granular level.
There are numerous regional variations which become extreme in certain emerging markets. Trying to find a specific city or region data can be useful when the data is putting an eye on emerging market trends. Since different areas serve altogether varying data structure, city and region-specific will largely help to retaliate the data and move on with realistic figures.
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