Artificial Intelligence chatbots in online business impact on customer satisfaction
Manzoor, Kamran; Abbas, Nadeem (2026)
2026
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2026052014500
https://urn.fi/URN:NBN:fi:amk-2026052014500
Tiivistelmä
This thesis discussed the role of AI chatbots in the online business customer satisfaction. The research was aimed at comprehending the experiences of customers when interacting with chatbots and how critical factors in this respect are ease of use, trust, perceived usefulness, accuracy and communication quality. The study was premised on a hybrid-methodology, using both quantitative and qualitative data to present general trends as well as more in-depth information. The quantitative data was gathered by surveying 90 respondents with the help of the Webropol platform, and by collecting the qualitative information with the use of the five semi-structured interviews using Zoom.
The quantitative results indicate that AI chatbots are usually seen positively by users. The findings demonstrate that ease of use has the highest average score (4.0) followed by quick response and usefulness (3.8), which indicates that customers appreciate chatbots due to their effectiveness and convenience in performing routine tasks. The overall satisfaction is also good with an average score of 3.7. The moderate scores in this regard are noted on trust (3.5), understanding (3.6), accuracy (3.6), personalisation (3.6), and comfort in replacing human interaction (3.4). These results suggest that the usefulness of chatbots is not completely accepted by the customers as they are not fully confident in the need to rely on chatbots to have all kinds of interactions.
The qualitative results are conducive to these findings, as they give more in-depth information about customer experiences. The respondents note that chatbots are efficient to perform simple and quick tasks but have some limitations in comprehending complex queries, giving personalised answers, and building trust. Human customer service is favored by many users in those cases when it is necessary to explain something or comprehend something emotionally. The results indicate that chatbot systems are more effective when they are utilized with human support as opposed to their full substitution.
The thesis finds that AI chatbots positively, but insignificantly, influence customer satisfaction in online businesses. They enhance the efficiency of services, their accessibility, and the speed of response, but their effectiveness relies on enhancing trust, accuracy and personalisation.
The quantitative results indicate that AI chatbots are usually seen positively by users. The findings demonstrate that ease of use has the highest average score (4.0) followed by quick response and usefulness (3.8), which indicates that customers appreciate chatbots due to their effectiveness and convenience in performing routine tasks. The overall satisfaction is also good with an average score of 3.7. The moderate scores in this regard are noted on trust (3.5), understanding (3.6), accuracy (3.6), personalisation (3.6), and comfort in replacing human interaction (3.4). These results suggest that the usefulness of chatbots is not completely accepted by the customers as they are not fully confident in the need to rely on chatbots to have all kinds of interactions.
The qualitative results are conducive to these findings, as they give more in-depth information about customer experiences. The respondents note that chatbots are efficient to perform simple and quick tasks but have some limitations in comprehending complex queries, giving personalised answers, and building trust. Human customer service is favored by many users in those cases when it is necessary to explain something or comprehend something emotionally. The results indicate that chatbot systems are more effective when they are utilized with human support as opposed to their full substitution.
The thesis finds that AI chatbots positively, but insignificantly, influence customer satisfaction in online businesses. They enhance the efficiency of services, their accessibility, and the speed of response, but their effectiveness relies on enhancing trust, accuracy and personalisation.