Welcome to the upgraded BRAC University Institutional Repository. We are currently organizing collections after a recent system upgrade. Homepage category counters may temporarily show lower numbers while syncing, but over 27,000 repository items remain safe and accessible. Please use the search bar to find theses, scholarly outputs, and institutional documents.

PerceptiStore: an AI driven intelligent shopper

Loading...
Thumbnail Image

Publisher

BRAC University

Authors

Citation

Abstract

The PerceptiStore: An AI driven Intelligent Shopper project uses advanced AIpowered personalization to improve the online shopping experience. AI-driven personalisation has emerged as a key factor influencing the direction of e-commerce in the current digital environment. Personalized shopping experiences make a difference by customizing information, recommendations, and offers to individual interests, allowing customers to navigate a wide sea of products and possibilities. Beyond merely suggesting products, AI personalisation leverages user behavior, previous exchanges, and purchase trends to anticipate customer needs before they ever become aware of them. Additionally, AI is able to generate highly relevant recommendations that increase the probability of repeat purchases by combining behavioral data with purchase history. This degree of customisation makes the buying experience efficient and pleasurable, which not only increases sales but also cultivates consumer loyalty. E-commerce personalisation fosters closer ties between companies and their clients by providing a feeling of individualized care in an otherwise congested online market. Ensuring security and privacy is essential as AI analyzes more and more personal data. Finding a balance between protecting sensitive information and providing individualized experiences is a challenge. In the end, AI personalisation signifies a profound change in the way that companies and customers communicate, making ecommerce a more dynamic, responsive, safe, and customized experience that meets each user’s specific demands.

Description

Cataloged from PDF version of thesis.
Includes bibliographical references (page 46).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2025.

Publisher Link

Type

Thesis