Analysis of Customer Behavior in Online Retail Marketplace Using Hadoop

Garima Shrivastava; Shailesh Shrivastava

Abstract

To provide a modernized technology foundation for transforming the retail experience, retail CIOs and IT leaders need to support the "seven Cs" of customer interaction: connected, continuous, convenient, contiguous, consistent, collaborative and customized [1]. The biggest differentiator of any online marketplace is how well the store understands its customer and provides the personalized experiences. Retailers interact with customers across multiple channels, yet customer interaction and purchase data is often isolated in data siloes. This paper attempts to identify the use cases to accurately correlate eventual customer purchases with marketing campaigns and online browsing behavior. The data used in this analysis was collected from a start- up online retailer in India.

Keywords

Adaptive Retail, Big data, Hadoop, RDBMS.

References

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Cites this article as

G. Shrivastava, S. Shrivastava, "Analysis of Customer Behavior in Online Retail Marketplace Using Hadoop", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-5, no.5, pp.376-380, 2017. Available from: https://doi.org/10.21276/ijircst.2017.5.5.3

Corresponding Author

Garima Shrivastava

Microsoft data scientist, MS Computer Science Former Specialist Data Science and Mining JSS Step, Noida, India

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