A consumer behaviour assessment using dimension reduction and deep learning classification

Pragya Pandey and Kailash Chandra Bandhu

International Journal of Information and Decision Sciences, 2025, vol. 17, issue 2, 133-149

Abstract: Consumer behaviour assessment is extremely important for online communities to finding out mindset of customer and changes their views about specific products and services. Customers share their experiences with particular goods, and services on channels and social media, empowered by artificial intelligence for consumer knowledge sharing and acquire new information. In this proposed work, a deep learning model has been developed for statistical tests, statistical analysis using correlation and association testing are performed. The ordinary dimension reduction with principal component analysis and module eigenvalues, followed by a second normalisation phase that maximises the coefficient's size using possible values. The keras library was used on the third layer of the deep learning classification hierarchy with the rectified linear unit and sigmoid activation functions. The average F1-score was 98% accurate and according to the statistics, the proposed strategy had an accuracy of 84% and a recall of 100%.

Keywords: consumer behaviour; artificial intelligence; principal component analysis; PCA; consumer knowledge-sharing; deep learning classification. (search for similar items in EconPapers)
Date: 2025
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