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Authors: Jānis Grabis ; Kristina Jegorova and Krišjānis Pinka

Affiliation: Institute of Information Technology, Faculty of Computer Science and Information Technology, Riga Technical University, Kalku Street 1, LV-1658, Riga, Latvia

Keyword(s): Customer Experience, Ambient Conditions, IoT Analytics.

Abstract: IoT data analytics has many potential applications in the retail industry. However, relations among ambient conditions at stores as measured by IoT devices and sales performance are not well understood. This paper explores sensory and sales data provided by a large retail chain to quantify the impact of air quality, temperature, humidity and lighting on customer behaviour. It has been determined that the air quality and humidity have a significant impact and temperature appears to have a non-linear effect on customer behaviour. The data analysis findings are used to configure an IoT data analytics platform. The platform is used to monitor the ambient conditions in retail stores, to evaluate a need for improving the conditions as well as to enact improvement by passing them over to a building management system.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Grabis, J.; Jegorova, K. and Pinka, K. (2020). IoT Data Analytics in Retail: Framework and Implementation. In Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL; ISBN 978-989-758-476-3, SciTePress, pages 93-100. DOI: 10.5220/0010133700930100

@conference{in4pl20,
author={Jānis Grabis. and Kristina Jegorova. and Krišjānis Pinka.},
title={IoT Data Analytics in Retail: Framework and Implementation},
booktitle={Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL},
year={2020},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010133700930100},
isbn={978-989-758-476-3},
}

TY - CONF

JO - Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL
TI - IoT Data Analytics in Retail: Framework and Implementation
SN - 978-989-758-476-3
AU - Grabis, J.
AU - Jegorova, K.
AU - Pinka, K.
PY - 2020
SP - 93
EP - 100
DO - 10.5220/0010133700930100
PB - SciTePress