Tag Archives: technologies

This is an excerpt from one of my latest contributions on the use of responsive chatbots by service businesses. The content was adapted for this blogpost.

_{Suggested citation: Camilleri, M.A. & Troise, C. (2022). Live support by chatbots with artificial intelligence: A future research agenda. Service Business, https://doi.org/10.1007/s11628-022-00513-9}

The benefits of using chatbots for online customer services

Frequently, consumers are engaging with chatbot systems without even knowing, as machines (rather than human agents) are responding to online queries (Li et al. 2021; Pantano and Pizzi 2020; Seering et al. 2018; Stoeckli et al. 2020). Whilst 13% of online consumer queries require human intervention (as they may involve complex queries and complaints), more than 87 % of online consumer queries are handled by chatbots (Ngai et al., 2021).

Several studies reported that there are many advantages of using conversational chatbots for customer services. Their functional benefits include increased convenience to customers, enhanced operational efficiencies, reduced labor costs, and time-saving opportunities.

Consumers are increasingly availing themselves of these interactive technologies to retrieve detailed information from their product recommendation systems and/or to request their assistance to help them resolve technical issues. Alternatively, they use them to scrutinize their personal data. Hence, in many cases, customers are willing to share their sensitive information in exchange for a better service.

Although, these interactive technologies are less engaging than human agents, they can possibly elicit more disclosures from consumers. They are in a position to process the consumers’ personal data and to compare it with prior knowledge, without any human instruction. Chatbots can learn in a proactive manner from new sources of information to enrich their database.

Whilst human customer service agents may usually handle complex queries including complaints, service chatbots can improve the handling of routine consumer queries. They are capable of interacting with online users in two-way communications (to a certain extent). Their interactions may result in significant effects on consumer trust, satisfaction, and repurchase intentions, as well as on positive word-of-mouth publicity.

Many researchers reported that consumers are intrigued to communicate with anthropomorphized technologies as they invoke social responses and norms of reciprocity. Such conversational agents are programed with certain cues, features and attributes that are normally associated with humans.

The findings from this review clearly indicate that individuals feel comfortable using chatbots that simulate human interactions, particularly with those that have enhanced anthropomorphic designs. Many authors noted that the more chatbots respond to users in a natural, humanlike way, the easier it is for the business to convert visitors into customers, particularly if they improve their online experiences. This research indicates that there is scope for businesses to use conversational technologies to personalize interactions with online users, to build better relationships with them, to enhance consumer satisfaction levels, to generate leads as well as sales conversions.

The costs of using chatbots for online customer services

Despite the latest advances in the delivery of electronic services, there are still individuals who hold negative perceptions and attitudes towards the use of interactive technologies. Although AI technologies have been specifically created to foster co-creation between the service provider and the customer,

There are a number of challenges (like authenticity issues, cognition challenges, affective issues, functionality issues and integration conflicts) that may result in a failed service interaction and in dissatisfied customers. There are consumers, particularly the older ones, who do not feel comfortable interacting with artificially intelligent technologies like chatbots, or who may not want to comply with their requests, for different reasons. For example, they could be wary about cyber-security issues and/or may simply refuse to engage in conversations with a robot.

A few commentators contended that consumers should be informed when they are interacting with a machine. In many cases, online users may not be aware that they are engaging with elaborate AI systems that use cues such as names, avatars, and typing indicators that are intended to mimic human traits. Many researchers pointed out that consumers may or may not want to be serviced by chatbots.

A number of researchers argued that some chatbots are still not capable of communicative behaviors that are intended to enhance relational outcomes. For the time being, there are chatbot technologies that are not programed to answer to all of their customers’ queries (if they do not recognize the keywords that are used by the customers), or may not be quick enough to deal with multiple questions at the same time. Therefore, the quality of their conversations may be limited. Such automated technologies may not always be in a position to engage in non-linear conversations, especially when they have to go back and forth on a topic with online users.

Theoretical and practical implications

This contribution confirms that recently there is a growing interest among academia as well as by practitioners on research that is focused on the use of chatbots that can improve the businesses’ customer-centric services. It clarifies that various academic researchers have often relied on different theories including on the expectancy theory, or on the expectancy violation theory, the human computer interaction theory/human machine communication theory, the social presence theory, and/or on the social response theory, among others.

Currently, there are limited publications that integrated well-established conceptual bases (like those featured in the literature review), or that presented discursive contributions on this topic. Moreover, there are just a few review articles that capture, scrutinize and interpret the findings from previous theoretical underpinnings, about the use of responsive chatbots in service business settings. Therefore, this systematic review paper addresses this knowledge gap in the academic literature.

It clearly differentiates itself from mainstream research as it scrutinizes and synthesizes the findings from recent, high impact articles on this topic. It clearly identifies the most popular articles from Scopus and Web of Science, and advances a definition about anthropomorphic chatbots, artificial intelligence chatbots (or AI chatbots), conversational chatbot agents (or conversational entities, conversational interfaces, conversational recommender systems or dialogue systems), customer experience with chatbots, chatbot customer service, customer satisfaction with chatbots, customer value (or the customers’ perceived value) of chatbots, and on service robots (robot advisors). It discusses about the different attributes of conversational chatbots and sheds light on the benefits and costs of using interactive technologies to respond to online users’ queries.

In sum, the findings from this research reveal that there is a business case for online service providers to utilize AI chatbots. These conversational technologies could offer technical support to consumers and prospects, on various aspects, in real time, round the clock. Hence, service businesses could be in a position to reduce their labor costs as they would require fewer human agents to respond to their customers. Moreover, the use of interactive chatbot technologies could improve the efficiency and responsiveness of service delivery. Businesses could utilize AI dialogue systems to enhance their customer-centric services and to improve online experiences.  These service technologies can reduce the workload of human agents. The latter ones can dedicate their energies to resolve serious matters, including the handling of complaints and time-consuming cases.

On the other hand, this paper also discusses potential pitfalls. Currently, there are consumers who for some reason or another, are not comfortable interacting with automated chatbots. They may be reluctant to engage with advanced anthropomorphic systems that use avatars, even though, at times, they can mimic human communications relatively well.  Such individuals may still appreciate a human presence to resolve their service issues. They may perceive that interactive service technologies are emotionless and lack a sense of empathy.

Presently, chatbots can only respond to questions, keywords and phrases that they were programed to answer. Although they are useful in solving basic queries, their interactions with consumers are still limited. Their dialogue systems require periodic maintenance. Unlike human agents they cannot engage in in-depth conversations or deal with multiple queries, particularly if they are expected to go back and forth on a topic.

Most probably, these technical issues will be dealt with over time, as more advanced chatbots will be entering the market in the foreseeable future. It is likely that these AI technologies would possess improved capabilities and will be programmed with up-to-date information, to better serve future customers, to exceed their expectations.

Limitations and future research avenues

This research suggests that this area of study is gaining traction in academic circles, particularly in the last few years. In fact, it clarifies that there were four hundred twenty-one 421 publications on chatbots in business-related journals, up to December 2021. Four hundred fifteen (415) of them were published in the last 5 years. 

The systematic analysis that was presented in this research was focused on “chatbot(s)” or “chatterbot(s)”. Other academics may refer to them by using different synonyms like “artificial conversational entity (entities)”, “bot(s)”, “conversational avatar(s)”, “conversational interface agent”, “interactive agent(s)”, “talkbot(s)”, “virtual agent(s)”, and/or “virtual assistant(s)”, among others. Therefore, future researchers may also consider using these keywords when they are other exploring the academic and nonacademic literature on conversational chatbots that are being used for customer-centric services.

Nevertheless, this bibliographic study has identified some of the most popular research areas relating to the use of responsive chatbots in online customer service settings. The findings confirmed that many authors are focusing on the chatbots’ anthropomorphic designs, AI capabilities and on their dialogue systems. This research suggests that there are still knowledge gaps in the academic literature. The following table clearly specifies that there are untapped opportunities for further empirical research in this promising field of study.

The full article is forthcoming. A prepublication version will be available through Researchgate.