Analysis of Chatbot Program Features Towards Customer Satisfaction in the Era of Digitalization

Aulia, Fika; U, Chresentia Adviorika; Yuniarty, -; Fahlevi, Mochammad; Prabowo, Harjanto; Muchardie, Brian Garda

doi:10.1109/icimtech53080.2021.9535034

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…This study aims to ascertain how chatbot services affect customer happiness in the current digital era. According to the study's findings, the marketing effort variable's entertainment indicator had the highest loading factor value compared to the others (Aulia et al, 2021).…”

Section: Rq1 How Can Aisa Improve Claim Management In the Insurance S...mentioning

confidence: 93%

Artificial intelligence service agents: a silver lining in rural India

Ravi

Vedapradha²

2023

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PurposeThe study aims to examine the impact of an artificial intelligent service agent (AISA) on customer services to the rural population provided by KAYA, Kotak Life's AI-enabled insurance chatbot avatar that offers quality insurance services.Design/methodology/approachMulti-stage cluster sampling method was adopted to collect the responses from the 707 customers across the rural population of southern states of India. SPSS V.2 and Smart PLS 4 were used to apply simple percentage analysis, multiple linear regression analysis, and structural equation modeling (SEM) to validate the hypothesis. The dependent variables are economic performance and market performance based on the independent variables: efficiency, security, availability, enjoyment and contact.FindingsThe study revealed that efficiency and security are the highest predictors and the most influencing variables in predicting the economic and market performance of the insurance companies in determining the quality of service when rendered through AISA among the customers. Efficiency, security, availability, contact and enjoyment are the critical dimensions of AISA. It has a more significant impact on quality service (claim processing) to the rural population. It improves the economic and market performance among the insurance companies and the rural population.Originality/valueCustomers need convenience when making claims. Even little challenges might lead to stress and unhappiness, depending on the situation. Restrictions on where customers can file claims may not be the most outstanding service insurance firms can offer, given rising travel and commuting costs and widening geographical borders. Customers value proactive communication from service providers about the status of their insurance claims.

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Section: Rq1 How Can Aisa Improve Claim Management In the Insurance S...mentioning

confidence: 93%

Artificial intelligence service agents: a silver lining in rural India

Ravi

Vedapradha²

2023

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“…Huntinghouse et al (2021) acknowledged, how Facebook can target users with appropriate ads using artificial intelligence and machine learning, along with suggestions to improve the framework. More studies from Ngai et al (2021), Prentice and Nguyen (2021), and Aulia et al (2021) bring forth ways to use bots to enhance customer service. Davenport et al (2020) (2021) and Li et al (2021) in their respective studies.…”

Section: Recent Developments In the Field Of Studies Researching Ai I...mentioning

confidence: 99%

“…(2021), Prentice and Nguyen (2021), and Aulia et al. (2021) bring forth ways to use bots to enhance customer service. Davenport et al.…”

Section: Literature Reviewmentioning

confidence: 99%

Artificial intelligence in marketing research and future research directions: Science mapping and research clustering using bibliometric analysis

Thakur,

Kushwaha

2023

Glob Bus Org Exc

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The marketing environment has experienced significant advancements due to the transformative influence of technologies such as artificial intelligence, data analytics, decision sciences, and robotics. These innovations have entirely reshaped the fundamental marketing principles as we know them. This study uses bibliometric analysis to conduct a systematic literature review of research on Artificial Intelligence (AI) in marketing and provides future research directions. It also aims to identify the most influential and productive contributors and progression of research on AI in marketing. The bibliographic data of 317 documents on artificial intelligence in marketing research was extracted from the Scopus database. The bibliometric analysis is performed to comprehensively understand the most influential and productive articles, authors, sources, and the top contributing countries and institutions towards the discipline of AI in marketing research. The results and the publication trend show exponential growth yearly in AI in marketing research. Furthermore, it discovered four main thematic clusters: Data mining and deep learning in decision support systems, big data and generative AI in marketing, AI‐enabled commerce, and chatbots and marketing Tech that represent the recent research being carried out under AI in marketing. The trending topics recognized are marketing algorithms for decision‐making, AI‐enabled marketing, the Internet of Things (IoT) and marketing, natural language processing and customer service, robotic services, and chatbots. This study also emphasizes potential future research areas, building upon the established thematic clusters.

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