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EMAC 2019 Annual Conference


Data-driven discovery of digital channels for detecting sales prospects in emerging markets
(A2019-9464)

Published: May 28, 2019

AUTHORS

Lili Aunimo, Haaga-Helia University of Applied Sciences; Heli Hallikainen, University of Eastern Finland

KEYWORDS

emerging economies; automated discovery of sales prospects; machine learning

ABSTRACT

This study applies machine learning methods to find sales prospects in emerging markets, i.e. economies that are radically different from the Western, educated, industrialized, rich, democratic economies. The research goal is twofold. First, using interviews, the study identifies digital channels and data sources that are currently used by the B2B marketing and sales people. Second, the study applies a machine learning based method to discover new data sources, to be utilized in detecting potential new sales prospects in the emerging markets wherein data sources, in general, are scarcer compared to developed economies. We describe a case study and find out that publicly available data sources in digital channels are important for companies and can provide useful information when entering new markets. Additionally, we demonstrate how machine learning methods may be used to find new digital channels with potential sales prospects in an emerging market.

REFERENCES

This work was supported by the BIG-research program, funded by TEKES (Finnish Funding Agency for Innovation) no 2710/31/2016.