Conversational Marketing as a Framework for Interaction with the Customer: Development & Validation of the Conversational Agent's Usage Scale (original) (raw)
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CONVERSATIONAL MARKETING - NEW ROLES OF CONSUMERS
PROCEEDINGS XI INTERNATIONAL CONFERENCE ON SOCIAL AND TECHNOLOGICAL DEVELOPMENT , 2022
Consumer behavior has changed. Everything is gravitating towards customization. The key driving forces without a doubt are technological growth that is developing in a rapid rhythm. Historically, the companies had a one-way communication with the consumers, where the goal was to push broadcast marketing whereas today consumers are becoming producers at the same time. In the new age of consumers, they are more knowledgeable, demanding and they expect unwavering and experiences tailored to the extreme. Emergence of conversational agents is a technology in development that is bringing the topic of conversational marketing to the broader audience through its applicability in various fields thus including the inevitable-e-commerce. A prominent feature of every conversational agent is to engage in personalized one-to-one real-time communication with a consumer and offer availability for 24 hours a day, every day. This paper aims to discuss the opportunities and challenges of conversational marketing and strives to draw the practical ramifications from it. Research method is done through the literature review. The findings clearly indicate that nowadays companies need to align with conversational marketing or they will lag behind. Three main things are the key to consumers: what they are buying i.e. product, from whom they are buying i.e. the brand and the path they take to get there i.e. service.
So what's the Value of Conversational Agents in E-commerce Retailers?
2019
Conversational Agents (CAs) are increasing in popularity very fast. They are used for helping people in many different domains. Recently they started to be used in customer service. Many businesses are already using CAs. However, there is a gap on how much value can these CAs bring to a business and why they should use them. Firstly, we need to understand the effectiveness of current CAs in the industry and identify challenges and limitations that customers are facing. Next we will develop new CAs which will address these challenges and limitations. Finally, we will improve these CAs with new technologies.
A Review of Conversational Marketing
Journal of Positive School Psychology, 2022
This review looks at conversational marketing, a new marketing approach that is focused on replacing staff with technology in order to enhance the overall customer experience. It starts with the introduction of the concept, followed by the foundation theories, benefits, and conclusion. Essentially, this paper has been developed to concisely discuss what conversational marketing is all about and how ventures can incorporate it into their marketing activities.
F1000 Research, 2022
Background: The increasing penetration of smartphones and the Internet in developing countries caused the rise of e-retail. Conversational commerce is highly increasing via interaction through messengers. To extract the benefits of both trends, companies have adopted messenger chatbots. These chatbots use Artificial intelligence and natural language processing to give live responses to the customer and assist online shopping on the messenger interface. This research aims to discover the factors that affect the use of messenger chatbots and their influence on attitude and behavior intention. Methods: The research methodology includes the Technology Acceptance Model (TAM) with the variables of perceived usefulness, perceived ease of use, consumer trust, and anthropomorphism. The authors used an online survey for collecting the responses from 192 respondents and analyzed structural equation modelling. Results: Customer trust has shown the most decisive influence on customer attitude followed by Perceived Usefulness, Perceived Ease of Use. Also, the use of chatbots to make online shopping faster significantly affects the use of messenger chatbots for online shopping in the future. The authors explore various factors resulting in consumers' favor of accepting chatbots as an interface for mcommerce. Conclusions: The findings indicate that organizations should design strategies to improve interaction with the customer by developing messenger chatbots for more trusting conversations. Further Open Peer Review Approval Status AWAITING PEER REVIEW Any reports and responses or comments on the article can be found at the end of the article.
Purchase intentions in a chatbot environment: An examination of the effects of customer experience
Oeconomia Copernicana, 2024
Research background: Chatbots represent valuable technological tools that allow companies to improve customer experiences, meet their expectations in real time, and provide them with personalized assistance. They have contributed to the transformation of conventional customer service models into online solutions, offering accessibility and efficiency through their integration across various digital platforms. Nevertheless, the existing literature is limited in terms of exploring the potential of chatbots in business communication and studying their impact on the customer's response. Purpose of the article: The main objective of this study is to examine how consumers perceive chatbots as customer service devices. In particular, the paper aims to analyze the influence of the dimensions of "Information", "Entertainment", "Media Appeal", "Social Presence" and "Risk for Privacy" on the "Customer Experience" and the latter on the "Purchase Intention", under the consideration of the Uses and Gratifications Theory. Moderations due to Chatbot Usage Frequency for some of the relationships proposed are also analyzed. Methods: An empirical study was performed through a questionnaire to Spanish consumers. The statistical data analysis was conducted with R software through the lavaan package. To test the hypotheses from the conceptual model a structural equation modelling approach was adopted. Findings & value added: The results obtained identify the main characteristics of chatbots that can support brands to effectively develop their virtual assistants in order to manage their relational communication strategies and enhance their value proposal through the online customer journey. Findings demonstrate the contribution that chatbot dimensions make to the online consumer experience and its impact on the purchase intention, with the consideration of the moderating effect exercised by the user's level of experience (novice vs. experienced) with the use of chatbots. Regarding managerial implications, this research offers recommendations for e-commerce professionals to manage chatbots more effectively. The "Entertainment" and "Social Presence" dimensions can be operationalized at a visual (e.g., appearance of the avatar and text box, use of designs aligned with the website) and textual level (e.g., style and tone of voice, use of expressions typical of the target audience) to generate a feeling of proximity with the chatbot and facilitate its adoption. "Media Appeal" requires that the chatbot be easy to use, effective, and accessible, to facilitate its usability. Finally, mitigation of "Privacy Risk" concerns should be achieved by presenting an appropriate privacy policy and requesting permission for the use of customers' private information. Research hypotheses Following the perspective of previous research regarding the Uses and Gratifications model, we propose the conceptual model shown in Figure 1. Key concepts and relationships embedded in this model are detailed below.
A Survey on the Impact of Chatbots on Marketing Activities
Recently, chatbot technology has been employed in several customer services and support roles. These conversational agents have become valuable assets to companies and organizations because of their ability to communicate with humans and process large amounts of data. Furthermore, since most customers are using online shopping to fulfill their requirements instead of traditional methods, they expect to get a full 24-hour service. This survey provides an overview of different studies that used chatbots as a tool to provide customer service and analyzes the techniques applied to it. In this survey, we divided the studies into two parts, the algorithms, techniques used in creating a chatbot, and the influence of the chatbot's use on marketing. Research shows most of the studies used Deep learning techniques for building chatbots. In addition, chatbot provides services that enable customers to have better communication with the brand and affect their long-term relationships.
… , 2004. Proceedings of …, 2004
have been demonstrated their potential for relationship building within e-tailing has been little utilized. In this exploratory paper we consider customer perceptions of what types of ECA are appropriate to retailing websites using data from semi-structured interviews with 30 Internet shoppers. Extrapolating the findings from the advertising literature concerning match-up between endorser and brand, product or retailer we find this will be an important element in the acceptability and viability of ECAs on retail websites. It is apparent that great care has to be taken in matching not only the physical characteristics of the ECA to perceptions of the brand, product or retailer but also to the goals and motivations of potential customers of a website.
Consumers’ behavior in conversational commerce marketing based on messenger chatbots
F1000Research
Background: The increasing penetration of smartphones and the Internet in developing countries caused the rise of e-retail. Conversational commerce is highly increasing via interaction through messengers. To extract the benefits of both trends, companies have adopted messenger chatbots. These chatbots use Artificial intelligence and natural language processing to give live responses to the customer and assist online shopping on the messenger interface. This research aims to discover the factors that affect the use of messenger chatbots and their influence on attitude and behavior intention. Methods: The research methodology includes the Technology Acceptance Model (TAM) with the variables of perceived usefulness, perceived ease of use, consumer trust, and anthropomorphism. The authors used an online survey for collecting the responses from 192 respondents and analyzed structural equation modelling. Results: Customer trust has shown the most decisive influence on customer attitude fo...
Conversational agents in business: A systematic literature review and future research directions
Computer Science Review, 2020
The field of business shows an increasing interest in exploring conversational agents to improve service quality and market competitiveness. Furthermore, the advances in machine learning capabilities leverage the natural language processing towards natural and straightforward dialogue experiences for industries. However, in the best of our knowledge, no literature review outlines conversational agents in the business industry, primarily taking into account computational learning capabilities. This article presents a systematic literature review that encompasses these areas looking through the use of machine learning to improve the field of business. The review followed a guideline for systematic reviews to present the literature of the last decade, emphasizing business perspectives such as domains, goals, and challenges, and computational methods for self-learning, personalization, and response generation of conversational agents. As a result, the article provides the answers of three general, three focused, and two statistical questions to address the role of artificial intelligence in conversational agents applied to business domains. In this regard, the results show that no study combines self-learning, personalization, and generative-based responses for the same business solution. Additionally, the article describes the organization of the state-of-the-art, highlighting the correlation of business perspectives and machine learning methods. The contributions of this review focus on opportunities and future research directions towards human-like conversational agents for business.
AI Based Chatbot Agents as Drivers of Purchase Intentions
The area of e-marketing can benefit from the usage of digital technology like chatbots. This study aimed to determine the impact of chatbots on customers’ purchase intentions. An empirical study was carried out on the impact of chatbot agent’s informational support, Emotional Credibility, and trust on purchasing intentions. The data was collected through an online survey from 223 Delhi-NCR customers who use chatbots while making online purchases. PLS-SEM was used to analyze the data that was collected. The results of structural equation modeling (SEM) showed a significant impact on informational support, emotional credibility, and trust of chatbots on purchase intentions of customers. The results of the study can be used as guidance by marketers to achieve a competitive edge in the changing business environment. The findings of the present study will encourage marketers to use technologies such as chatbots and help customers to get information. The marketers are encouraged to utilize and monitor chatbots efficiently and effectively. This study intends to contribute to the field of e-marketing.