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Artificial Neural Networks for Enhancing E-commerce: A Study on Improving Personalization, Recommendation, and Customer Experience

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Innovations in Electrical and Electronic Engineering (ICEEE 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1115))

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Abstract

With e-commerce companies, artificial intelligence (AI) has emerged as a crucial innovation that allows companies to streamline processes, improve customer interactions, and increase operational capabilities. To provide tailored suggestions, address client care requests, and improve inventory control, AI systems may evaluate consumer data. Moreover, AI can improve pricing methods and identify fraudulent activity. Companies can actually compete and provide better consumer interactions with the growing usage of machine learning in e-commerce. This essay examines how AI is reshaping the e-commerce sector and creating fresh chances for companies to enhance their processes and spur expansion. AI technology which enables companies to enhance their procedures and offer a more individualized customer experiences has grown into a crucial component of the e-commerce sector. Purpose of providing product suggestions and improve pricing tactics, intelligent machines may examine consumer behavior, interests, and purchase history. Customer service employees will have less work to do as a result of chatbots powered by artificial intelligence handling client queries and grievances. AI may also aid online retailers in streamlining their inventory control by anticipating demands and avoiding overstocking. The use of AI technologies can also identify suspicious transactions and stop economic losses. AI is positioned to assume a greater part in the expansion and accomplishment of the e-commerce sector as it grows in popularity.

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Authors and Affiliations

  1. Department of Computer Science, CHRIST (Deemed to Be University), Delhi NCR Campus, Ghaziabad, India

    Kamal Upreti & Kamal Upreti

  2. Department of Management, ADGITM, Delhi, India

    Divya Gangwar

  3. Department of CSE, SCSE, Manipal University Jaipur, Jaipur, Rajasthan, India

    Prashant Vats

  4. Chitkara Business School, Chitkara University, Rajpura, Punjab, India

    Rishu Bhardwaj

  5. Bhagwan Parshuram Institute of Technology, Delhi, India

    Vishal Khatri

  6. Warwick Manufacturing Group, Coventry, UK

    Vijay Gautam

Authors
  1. Kamal Upreti
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  2. Divya Gangwar
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  3. Prashant Vats
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  4. Rishu Bhardwaj
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  5. Vishal Khatri
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  6. Vijay Gautam
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Corresponding author

Correspondence to Kamal Upreti .

Editor information

Editors and Affiliations

  1. University Center for Research and Development (UCRD), Chandigarh University, Mohali, Punjab, India

    Rabindra Nath Shaw

  2. Department of Management and Innovation Systems, University of Salerno, Fisciano, Italy

    Pierluigi Siano

  3. Department of Electrical Engineering, Swinburne University of Technology, Melbourne, VIC, Australia

    Saad Makhilef

  4. University Center for Research and Development (UCRD), Chandigarh University, Mohali, Punjab, India

    Ankush Ghosh

  5. Department of Electrical Engineering, Punjab Engineering College (Deemed to be University), Chandigarh, Punjab, India

    S. L. Shimi

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Upreti, K., Gangwar, D., Vats, P., Bhardwaj, R., Khatri, V., Gautam, V. (2024). Artificial Neural Networks for Enhancing E-commerce: A Study on Improving Personalization, Recommendation, and Customer Experience. In: Shaw, R.N., Siano, P., Makhilef, S., Ghosh, A., Shimi, S.L. (eds) Innovations in Electrical and Electronic Engineering. ICEEE 2023. Lecture Notes in Electrical Engineering, vol 1115. Springer, Singapore. https://doi.org/10.1007/978-981-99-8661-3_11

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  • DOI: https://doi.org/10.1007/978-981-99-8661-3_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8660-6

  • Online ISBN: 978-981-99-8661-3

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