How did we create impact?

The purpose of the track was to develop concrete solutions to make use of the large amount of data that is already available on BoP markets. The integrated solution aimed to combine existing BoP market data from public research projects with a large set of different data sets that are collected by companies in developing and emerging markets every second. 

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What can artificial intelligence do for market research?

Artificial intelligence provides algorithms to automatically identify relevant information on the internet and analyze its content for specific uses. It enables enterprises to make better informed business decisions and develop services or products that exactly meet the needs of their target group. It can complement or even save businesses costly and time-intensive market research.
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Who attended?

The artificial intelligence for BoP market track brought together: 

  • Inclusive energy businesses that collect millions of data points on spending and consumption patterns of their customers every year
  • Public sector agencies commissioning BoP market research
  • Artificial intelligence experts from the academic and corporate world
  • Market research institutes that could market the data
  • Investors, banks and businesses that are interested in aggregated data for BoP markets

Why do we need BoP market data?

Companies and investors still cite the lack of market data as one of the major impediments to investing in low-income markets. Without a solid understanding of the income and spending patterns, preferences and challenges of the low-income target group, it is difficult to calculate a robust business case, find the appropriate price point, or identify the best market segment. As a result, companies either stay away from the market, or face high upfront costs for market research that they may not be able to recuperate if they don't find the expected market demand. 

At the same time, data on low-income markets already exists. Public organizations like the World Bank or national governments commission hundreds of reports each year that highlight earnings, spending and consumption patterns of people living at the BoP. This data, however, is often difficult to access and too high-level. In addition, inclusive businesses have started to collect data on their customers. Energy companies, for example, have already reached around 440 million households at the BoP with their services. Many of them regularly collect detailed data as part of their customer interactions, including via mobile transactions. They are keen to monetize this valuable data, but so far no means to market it effectively. 

Combining the data sets of public and private players would make the BoP market a lot more transparent and accessible for companies and investors.