Analysis of Consumer Behavior in Bigdata Insights

DOI

10.2991/978-94-6463-298-9_47How to use a DOI?

Keywords

Consumer Behavior; Consumer Preference; Big Data analysis

Abstract

The importance of consumer behavior research in big data analytics is becoming increasingly prominent. By analyzing big data on consumer preferences, changing demands, behavioral patterns, and trends, businesses can make more accurate decisions, optimize product design and marketing strategies, and enhance their market competitiveness. Consumer behavior research aims to explore the behaviors, motivations, and decision-making processes exhibited by consumers in the process of purchasing goods or services, in order to understand and explain the underlying psychological, social, and cultural factors. This research helps uncover the factors and processes involved in consumer decision-making, including need recognition, information search, evaluation, and choice. Understanding consumer decision behavior is crucial for businesses and marketers as it guides them in formulating more effective marketing strategies. Consumer behavior research also provides guidance for marketing strategies. By gaining a deep understanding of consumer psychology and behavior, businesses can better target markets, optimize product design, develop differentiated marketing strategies, establish brand awareness, and provide personalized products and services. Additionally, consumer behavior research helps uncover consumer needs and preferences, providing guidance for product innovation. Consumer behavior research examines the effects of social and cultural factors on consumer behavior, to gain a deeper understanding of the reasons behind consumer behavior and how marketing efforts shape and influence consumer behavior.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Huangyi Qiu
AU  - Yuhang Shan
AU  - Runlei Song
PY  - 2023
DA  - 2023/11/30
TI  - Analysis of Consumer Behavior in Bigdata Insights
BT  - Proceedings of the 2023 International Conference on Finance, Trade and Business Management (FTBM 2023)
PB  - Atlantis Press
SP  - 429
EP  - 438
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-298-9_47
DO  - 10.2991/978-94-6463-298-9_47
ID  - Qiu2023
ER  -