Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2023
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2023
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Improving Customer Care with ChatGPT: A Case Study

Authors: Azam, Chowdhury Naem;

Improving Customer Care with ChatGPT: A Case Study

Abstract

{"references": ["Chowdhury, Naem & Rahman, Sagedur. (2023). A brief review of ChatGPT: Limitations, Challenges and Ethical-Social Implications. 10.5281/zenodo.7629888.", "Almeida, T., & Haddad, H. (2020). A systematic review of chatbot research in customer service. Journal of Service Management, 31(3), 484-508.", "Baheti, A. R., & Kshirsagar, P. (2021). Chatbot systems for customer service: A review of the literature. Journal of Enterprise Information Management, 34(4), 748-770.", "Chen, J., Liu, X., & Zhao, Y. (2020). Chatbot-based customer service in e-commerce: A literature review. Journal of Electronic Commerce Research, 21(1), 1-22.", "Lu, Y., Chen, S., Xu, H., & Yang, J. (2020). Chatbots in customer service: A review and research agenda. Journal of Service Management, 31(4), 642-668.", "Radziwon, A., & Radziwon, M. (2019). Chatbots in customer service: Current state of the art. Journal of Service Theory and Practice, 29(5), 644-670.", "Shum, H. P. H., & Bove, L. L. (2019). Chatbots and customer service: An exploratory study. Journal of Service Management, 30(5), 675-695", "Yan, Z., Cheng, Y., Lu, X., & Zhang, B. (2020). Chatbots in customer service: A review of literature and future research directions. Journal of Business Research, 118, 253-263.", "Zhang, X., Li, Y., & Liang, H. (2020). The impact of chatbots on customer satisfaction: An empirical study in the hospitality industry. Journal of Hospitality and Tourism Research, 44(5), 765-786", "Zhang, Y., Cui, L., & Hu, W. (2020). Chatbot-based customer service: A systematic literature review and future research directions. Information Processing & Management, 57(5), 102232.", "Zhao, S., Zhang, Y., & Wu, J. (2021). Understanding the impact of chatbots on customer experience: A research agenda. Journal of Service Management, 32(1), 25-51"]}

This case study explores the effectiveness of using ChatGPT, a large language model, to improve customer care. The study focuses on a company in the telecommunications industry, which was struggling to provide timely and accurate responses to customer inquiries. The company implemented a ChatGPTbased system to automate customer support and improve response times. The ChatGPT system was trained on a large dataset of customer inquiries and responses, allowing it to understand the context and intent of customer inquiries. The system was able to provide personalized responses to customers, addressing their specific concerns and providing accurate information. The results of the study showed a significant improvement in customer satisfaction and response times. The company was able to reduce the average response time from several hours to a matter of minutes, and customer satisfaction scores increased by over 30%. The study also revealed that ChatGPT was able to handle a high volume of inquiries without sacrificing quality. The system was able to accurately respond to over 90% of inquiries without human intervention. Overall, this case study demonstrates the effectiveness of using ChatGPT to improve customer care. By automating customer support and providing personalized responses, companies can significantly improve response times and customer satisfaction.

Related Organizations
Keywords

Customer Care, ChatGPT, Automated Customer Support, ChatGPT Case Study, Customer Satisfaction, Customer Service

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 56
    download downloads 69
  • 56
    views
    69
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
2
Top 10%
Average
Average
56
69
Green
Related to Research communities