Leveraging Chatbots for Better Customer Engagement in E-Commerce
- Pratichha S.
- Jul 13
- 5 min read
E-commerce has brought about a modern revolution within the fields of e-commerce and marketing. It has improved both the buyer and dealer experiences, sparing both time and cash. Currently, 52% of people say they prefer online buying rather than going to a store in person (Daggar, 2025).
Introduction
The use of chatbots in e-commerce has gathered a lot of attention in recent years due to their capacity to improve customer interaction and hierarchical ampleness. Chatbots are computer programs that utilise text or voice insights to recreate human discussions. They can be integrated into e-commerce systems to provide customised assistance, respond to inquiries, and guide clients through the purchasing process (Piyush et al., 2016, p.322(2)). Check out how the use of chatbots in e-commerce is revolutionising the e-commerce industry.
Justification for the Proposed Research
Working on research into chatbots' applications in e-commerce for customer engagement is being done for a few reasons:
As online shopping gets more popular, businesses use chatbots in e-commerce to interact with their customers. As a result, there is an increased demand for effective customer engagement strategies that will supply customers with customised offers to help and advance their buying experience (Nishihara et al., 2017, p.325(2)).
Chatbots can supply 24/7 client help, cut response times, and give clients personalised proposals and advancements. In any case, the observational inquiry is required to survey their value in boosting consumer engagement and commerce execution.
Designing a chatbot is complicated since consumers must receive customised service, and chatbots must be built to look like human communication. Research must be done to determine the terminology, tenor, and communication style that will produce a positive client experience.
Limited investigation, even though there has been research on the use of chatbots in e-commerce, we still don't fully grasp how effectively they engage customers. The most efficient methods for creation and development, as well as the use of chatbots in the e-commerce ecosystem, must be determined through further research.
Why Use Chatbots in E-commerce: A Literature Review
Customer satisfaction has been demonstrated to increase when chatbots are used to provide personalised service, handle several inquiries at once, and decrease wait times. They might increase sales by advertising clients' personalised product proposals and promotions. On the other hand, chatbots have disadvantages, such as a disposition to provoke and distract consumers when dealing with complex issues that call for human interaction.
The use of chatbots in e-commerce is conveying a favourable customer experience because customers favour chatbots that can react to their questions accurately and make use of pleasant, conversational language. It has been demonstrated that the application of Natural Language Processing (NLP) and Machine Learning (ML) innovation improves chatbots' capacity to offer individualised proposals and support them (Landim et al., 2021, p.200(2)).
Clients favour a hybrid approach in which chatbots react to scheduling questions and real individuals offer more involved support. Research about chatbots in e-commerce illustrates that chatbots have the potential to be a significant tool for expanding client interaction and e-commerce deals, but their integration with human specialists and organisations must be appropriately explored (Piyush et al., 2016, p.322(2)).
It has also been evaluated that chatbots are smarter, compared to customer service manual representatives, and so, chatbots do not provide a long waiting queue or response time, which helps in increasing customer experience. Being a chatbot, the natural language processing and artificial intelligence embedded programs help the customers resolve their issues faster while making sure there is service access related to issues in websites, mobile apps, social media, etc.
The use of chatbots in e-commerce helps increase the revenue and financial profits of the firm while receiving good feedback from customers. Not only revenue-making, but chatbots are also helpful in leading the organisation while reducing the response time and increasing the loyal customer base (Ho, 2021, p.16(1).
A chatbot named SuperAgent has been demonstrated in another journal paper, stating that the following chatbot is effective to be used for the e-commerce websites. According to the details of the system, the following e-commerce website chatbot has been created so that it could answer specific product information in detail specified from the page number, which is discussed with the hey customer. In the system detail section, it was described that the SuperAgent answers the questions through the system search, operated by the crawler.
According to the system definition, it has been stated that first, the customer asks a question, and for the product ID, the crawler searches the overall product database while checking all the FAQ searches and discussions to find a relevant answer and options. All the responses are gathered to provide the most appropriate response back to the customer. The following image describes the functioning of a e-commerce chatbot- SuperAgent (Cui et al., 2017, p.98(3)).
It has been observed that chatbots are efficient in managing customer experiences while increasing customer satisfaction for the business or organization. Another paper surveyed 299 people to assess whether they trust talking with chatbots and whether their user experience has been enhanced or not. A series of questions were asked in the paper, and it was found that people were friendly as well as empathetic with the chatbot. People reported that they could trust the chatbot and communicate with it in a friendly manner. It was also found that even after some of the tasks and questions are complex for the chatbot system to resolve, the customer's trust and empathy with the system are not disrupted. From another question response, it was stated that the customer’s trust and reliance are not being influenced by the negative responses provided by the system (Cheng et al., 2021, p.508,509(2,3,4).
According to the global data, the use of chatbots in e-commerce has increased in different continents, specifically for customer service purposes. It was observed that in most countries, AI chatbots have been used for customer service facilities, mainly in the finance and hospitality sectors. Maximum of the studies indicate that the use of AI chatbots has increased to resolve problems, while the other purpose of deployment of an AI chatbot is to answer specific questions asked by the customer, other than resolving a problem.
It has also been found that the use of chatbots in e-commerce has increased in several countries and is significant in resolving problems related to different industries and sectors. It was also observed that after communicating with a chatbot, the customers feel that they have love for the brand, while other customers found that their relative customer communication experience with the business or organization has been positively enhanced. The study also indicates that the customer experiences could either be positive or negative based upon the chatbot capabilities and dataset, whilst it was also stated that people trust and enjoy communicating with technology-based chatbots (Nicolescu and Tudorache, 2022, p.17(4.2.2).
References
Chen, J.-S., Le, T.-T.-Y. and Florence, D. (2021) ‘Usability and responsiveness of artificial intelligence chatbot on online customer experience in e-retailing’, International Journal of Retail & Distribution Management, ahead-of-print(ahead-of-print). Available at: https://doi.org/10.1108/ijrdm-08-2020-0312.
Kamal, S.A., Shafiq, M. and Kakria, P. (2020) ‘Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM)’, Technology in Society, 60, p. 101212. doi:10.1016/j.techsoc.2019.101212.
Landim, A.R.D.B. et al. (2021) ‘Chatbot design approaches for fashion E-commerce: an interdisciplinary review’, International Journal of Fashion Design, Technology and Education, 15(2), pp. 1–11. Available at: https://doi.org/10.1080/17543266.2021.1990417.
M Rakhra, G Gopinadh, NS Addepalli, G Singh, S Aliraja, VSG Reddy, MN Reddy (2021), E-Commerce Assistance with a Smart Chatbot using Artificial Intelligence, 2021 2nd International Conference on Intelligent Engineering and Management (ICIEM), https://doi.org/10.1109/iciem51511.2021.9445316.
N Piyush, T Choudhury, P Kumar (2016), Conversational commerce a new era of e-business, IEEE Xplore, https://doi.org/10.1109/SYSMART.2016.7894543.
Y Nishihara, M Ikuta, R Yamanishi, J Fukumoto (2017), A Generation Method of Back-Channel Response to Let a Chatting Bot Be a Member of Discussions in a Text-Based Chat, IEEE Xplore, https://doi.org/10.1109/IIAI-AAI.2017.68.
Daggar, J. (2025, February 14). Ecommerce Statistics: 200+ Online Shopping / Packaging Facts. GWP Group. https://www.gwp.co.uk/guides/ecommerce-statistics/
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