Enhanced Portable Customer Experience Using Community Computation in Offline Retail

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Abstract

Seeking out customer reviews has become such standard part of the buying process for people these days that every retailer needs to be thinking about them. But often customer reviews are found extensively in online shopping sites such as Amazon, Flipkart etc. and social media sites such as Facebook, twitter etc. But when a product is purchased from a retailer offline, these reviews are usually unattended and mining for the exact review will be time-consuming. Also, in large super-markets, the customer interaction is not as much as in online shopping so as to provide with details such as related products, what products were also purchased by the product who purchased the particular product etc. All these drawbacks are erased with our proposal to enhance customer interactivity through a smartphone application. Our proposed system uses a unique concept of ‘community-computation’, a variation of distributed systems for processing. The results of the proposed system show that by implementing such a real time system, the shopping experience of a normal customer can be enhanced and also the same will pave way for next-generation shopping.

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APA

Kuriakose, B., Mathai, V., Baby, A., & Jose, J. (2019). Enhanced Portable Customer Experience Using Community Computation in Offline Retail. In Lecture Notes on Data Engineering and Communications Technologies (Vol. 26, pp. 15–22). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-03146-6_2

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