Framework for Predicting Customer Channel Preference using Machine Learning

Purpose This study aims to examine how information professionals select a social media channel for information discovery and delivery. This analysis was focused to provide usage based ranking of social media channels for information discovery and delivery. This study has also measured the preference of social media as compared with other information and communication channels such as radio, TV, newspapers, etc., for information discovery and delivery. This study compared the global social media rank with the study rank to record the variances in the light of uses and gratification theory. Design/methodology/approach For this quantitative research study a self-administered survey questionnaire was used to collect data from the participants of the study. Sample of this study was 700 information professionals necessarily user of social media. Findings Findings of this reveals that social media is the most preferred channel for information discovery and delivery among information professionals and study validates the assumption of uses and gratification theory with a view that information professionals are independent and active users of social media and global rank of social media is significantly different from the rank developed in this study. Research limitations/implications The present study is limited to information professionals only and considers social media (only top 20 sites) as an information and communication channel among information professionals. Practical implications This study has determined the preference of social media as an information and communication channel as compared with other information and communication channels and present a ranking based on usage among information professional, which is significantly different from the existing global user based ranking. Social implications Social media provides versatility of information in different forms and large numbers of information professionals are the users of social media around globe. This study shall help information professional to select appropriate channels for information discovery and delivery. Usage based ranking provided in this study shall stream line the social media practices at large. Originality/value This study has developed a usage based rank of top social media. This study elaborated the preference of social media as an information and communication channel.

With the development of the Internet, more and more industries are using digital marketing to advertise, and the automotive industry is no exception. Digital marketing is effective because it finds the most suitable marketing method according to the user profile for accurate positioning, which greatly improves the sales of auto brands and enhances the brand image in users' minds. there are three frequently used marketing strategies in the automotive industry: content marketing, influencer marketing and event marketing. Each one of them can bring a certain amount of increment for the brand. By looking into the strategies, through customer expectations will be acquired, and the market potential will be discovered. However, the analysis of auto industry digital marketing is still to be explored, and the effect of marketing strategies needs to be improved. Based on the online marketing of today's car companies, this paper has made constrictive suggestions including constructive suggestions are made in this paper.

The pet food market has grown significantly amidst the surging pet ownership, driven by diverse consumer demands and demographics. The significance of marketing in this industry lies in attracting new customers, fostering brand loyalty, and adapting to evolving market trends. To achieve this, marketers employ strategies like conducting thorough market research to understand consumer preferences and competitor landscapes. Targeting specific customer segments, such as pet owners and retailers, with tailored messages is crucial. Branding and promotion, involving memorable logos and creative campaigns across digital and traditional channels, help establish a strong brand identity. Diversifying product offerings with innovative formulations and flavors meets diverse pet nutritional needs. Integrating online and offline sales channels ensures widespread reach and convenient shopping experiences. Social media platforms facilitate engagement with customers, offering educational content and leveraging influencer partnerships. Cross-brand collaborations and limited-edition products add novelty and exclusivity. Finally, excellent customer service and post-purchase support foster long-term loyalty. Successful marketing in the pet food industry necessitates a comprehensive understanding of the market, innovative product development, multi-channel outreach, and a focus on customer satisfaction. As the industry continues to expand, staying agile and responsive to evolving consumer needs will be key to maintaining a competitive edge.

Social media: Influencing customer satisfaction in B2B sales

An Analysis of Customer Satisfaction Towards Technical Services in Malaysian Automotive Industries

Social media is rapidly becoming an integral part of modern society. People use social media as a channel of communications with each other, a targeted group or a general public. Concurrently, researchers are studying this channel of communications in an attempt to link the characteristics of the message, such as content, sender-receiver, etc. to the behavior of those using this media. The focus of the research reported herein is to analyze human behavior in response to actionable information in the context of an extreme event. A specific case of actionable information presented in this paper is recommendations to take actions to reduce the chance of harm from the consequences of an extreme event i.e. an alert or warning. Authorized officials via multiple channels of communication issue the warnings to the public. At present, social media is not used universally as an official channel of communication. There is still no clear consensus among emergency management organizations on how the social media can be utilized to disseminate warnings to the public. The first step is to understand peopleâs behaviors on social media in response to actionable information during extreme events. In order to understand peopleâs behaviors on social media, we need to understand the content of their messages and how the messages travel through social media. The paper focuses on identifying hidden key actors (individual/organizations) using advanced social network analysis techniques. Additionally, the paper examines the formation of the cohesive groups in the network and the role of the key actors in those groups. Our conclusion is that the key actors play an important role in diffusion of actionable information. The diffusion begins with central and prominent actors and diffuses through the âgatekeepersâ of information to the rest of the network. The key actors exhibit intentions to take a prescribed action and urge others to do so. Finally, the key actors play in important role of bridging cohesive groups in the network in order to facilitate the diffusion of actionable information.

With the rising growth of the telecommunication industry, the customer churn problem has grown in significance as well. One of the most critical challenges in the data and voice telecommunication service industry is retaining customers, thus reducing customer churn by increasing customer satisfaction. Telecom companies have depended on historical customer data to measure customer churn. However, historical data does not reveal current customer satisfaction or future likeliness to switch between telecom companies. The related research reveals that many studies have focused on developing churner prediction models based on historical data. These models face delay issues and lack timelines for targeting customers in real-time. In addition, these models lack the ability to tap into Arabic language social media for real-time analysis. As a result, the design of a customer churn model based on real-time analytics is needed. Therefore, this study offers a new approach to using social media mining to predict customer churn in the telecommunication field. This represents the first work using Arabic Twitter mining to predict churn in Saudi Telecom companies. The newly proposed method proved its efficiency based on various standard metrics and based on a comparison with the ground-truth actual outcomes provided by a telecom company.

This study is aimed to investigate a theoretical base for examining the customer social media use factors (e.g., social media reviews, satisfaction of products, and operations of services) in service organizations context. In order to find out the efficiency of this association, this study is used simple regression analysis and the correlation analysis technique. Data were collected from 385 respondents use social media frequently, by focusing a convenience-based non-probability sampling technique. The questionnaire was circulated with the help of e-mail and other social media like Facebook, Instagram, IMO, What Sapp, and LinkedIn. Questionnaire was also distributed in educational institute (Students of different universities), insurance companies, and those organizations who offer their services through social media. The data was collected by using the quantitative technique in which customers were asked to fill the questionnaire on a voluntary basis. Results designate an optimistic association of social media factors and customers satisfaction. The results indicated that social media reviews have a strong association with job satisfaction. Further, the findings highlight the importance that product satisfaction has a significant effect on customer satisfaction. Lastly, the researcher findings indicated that operations of services have a significant and positive association with customers satisfaction. Further, this study also discloses the discussion about the accepted hypothesis as well as managerial implications or future research directions for practitioners and academicians. This research is novel for service-providing organizations to understand the behavior of customers.

Telecommunications is a customer-oriented industry in which client satisfaction is crucial for an organization's survival. Social media plays a vital role in customer decisions, acting as both a search tool and a communication channel. On social media platforms, customers can air their grievances, and a company can use these complaints to improve its products and services. During the first quarter of 2022, sentiment analysis was conducted to evaluate customer satisfaction with telecom services in Saudi Arabia. With a machine-learning approach, more than 90K comments were recorded and categorized as positive, negative, or neutral. For the classification, we utilised a support vector machine (SVM) model with an average accuracy of 88%. After that, We utilised thematic analysis of social engagement opinions. We identified seven themes among the comments related to factors affecting efficiency and satisfaction with telecommunications services: product, package, price, promotion, place, people, and public relations. In conclusion, we recommend some solutions to improve efficiency and increase customer satisfaction in the telecom sector.

Customer satisfaction is crucial for any firm. Traditional methods of measuring customer satisfaction, such as customer surveys, are resource‐intensive despite their effectiveness. We develop an innovative approach that leverages social media posts to evaluate customer satisfaction. Specifically, we augment survey data with social media content and propose a supervised topic model to predict customer satisfaction. Method‐wise, our model accommodates texts from various social media platforms, with or without explicit customer ratings. In addition, we address the challenges associated with integrating multiple data sources. To empirically validate our approach, we utilize data from various social media platforms combined with customer surveys from target firms in seven essential industries in Hong Kong. Our model exhibits higher prediction accuracy compared to baseline methods. This research provides a cost‐effective and efficient tool for transforming vast amounts of social media posts into valuable insights on customer satisfaction.

The background of this research is based on changes in consumer behavior when choosing accommodation, where online platforms like Traveloka have become a primary source of information before making a booking. The method used is a quantitative approach with multiple linear regression analysis techniques. Data was obtained through surveys and analyzed using validity tests, reliability tests, descriptive statistics, and regression tests. The results of the study show that Traveloka ratings do not have a significant effect on the decision to stay, indicating that consumers tend to consider other factors such as price and location. On the other hand, Traveloka reviews were found to have a significant influence, reflecting the important role of customer reviews in shaping perceptions and building trust in the hotel. In addition, hotel promotional media also significantly influenced consumer decisions, where visual and interactive content through digital channels proved effective in attracting interest and creating an emotional connection with potential guests. These findings contribute to the development of digital marketing strategies in the hospitality industry, particularly in increasing occupancy rates and customer satisfaction at Hotel Horison Lampung

The banking sector continues to face intense competitive pressures in a global economy where customer satisfaction, customer loyalty, and service quality continue to be critical factors. The aim of this study is to examine the relationship between service quality and customer satisfaction and customer loyalty. Additionally, in order to fill the empirical literature gap, the role of social media has been examined as a moderator. 230 retail banking customers from Pakistan were chosen as a representative sample. Using the structured questionnaire, convenient (non-probability) sampling was employed to gather primary data from the target population. A statistical analysis of the collected data was conducted using Structural Equation Modeling - Partial Least Squares (SEM-PLS). The findings of the study revealed that customer loyalty is significantly influenced by service quality and customer satisfaction. Furthermore, social media also influences the correlations between service quality and customer satisfaction with consumer loyalty. This study will provide retail banking management and strategists with various useful insights about how to manage service quality and customer satisfaction in relation to customer loyalty.

This paper examines the communication strategies employed by small cap firms listed on the Alternative Investment Market (AIM) of the London Stock Exchange. These small cap firms have great discretion in choosing their communication channels with investors and evolve in an environment with few information intermediaries. We investigate the use of three communication channels – press releases, conference calls, and social media – specifically surrounding earnings announcements. Our findings indicate that small cap firms utilize these three communication channels infrequently. However, when announcing positive earnings news, small cap firms are more likely to employ these channels, suggesting that firms communicate opportunistically. We find a positive association between the use of communication channels, particularly of social media, and measures of investor attention. Interestingly, while the use of communication channels is associated with positive stock returns surrounding earnings announcements, social media usage prior to earnings announcements is linked to subsequent stock price reversals. These findings provide insights into the communication practices of small cap firms and their implications for investor attention and market efficiency.

CF (Collaborative filtering) algorithm has the widest and most successful applications in personalized recommendations. However, due to its over-reliance on the users' historical data, it is difficult to avoid data sparseness and cold start issues. The data sparseness and cold start may cause poor recommendation accuracy of the collaborative filtering algorithm. A hybrid optimal collaborative filtering algorithm based on users' characteristics and trust is proposed in this paper. In the process of users' similarity calculation, the age and gender of users' characteristics are introduced to make the determination of nearest neighbor more accurate. Besides, in order to improve the recommendation accuracy of the traditional CF recommendation algorithm, the trust relationship is introduced into the prediction score by measuring the users' trust, and this improvement will be used in the recommendation of new items in order to improve the recommendation accuracy of the traditional CF recommendation algorithm. The experimental results of Movie lens data set show that the improved recommendation accuracy of the recommendation system can be achieved by the proposed algorithm. Also, the problems of cold start and sparse data can be solved effectively.

In the midst of the ongoing industrial revolution and significant technological developments, it is important for every industry to apply the latest technologies to increase the company's growth scale in this intense competition. Customer Relationship Management (CRM) is a technology that has been widely used in various industries to increase user intensity in using products and interacting with users. The purpose of this study is to analyse the effectiveness of CRM implementation using health mobile application in Indonesia. The nature of this research is quantitative and the data collected is through questionnaires which are distributed by purposive sampling technique on social media which is focused on respondents who understand CRM technology in the Indonesian region. This study found that the healthcare applications that will implement CRM tend to increase customer satisfaction. In addition, high customer satisfaction is considered to increase user retention and also studies find that the implementation of a CRM system affects customer retention and satisfaction.