scholarly journals Restaurant Review Classification Using Naives Bayes Model

2021 ◽  
Vol 23 (08) ◽  
pp. 646-656
Author(s):  
Kothapally Nithesh Reddy ◽  
◽  
Dr. B. Indira Reddy ◽  
Keyword(s):  
Customer Service ◽  
Confusion Matrix ◽  
Test Sample ◽  
Growth Strategy ◽  
Purchasing Decisions ◽  
Bayes Model ◽  
Customer Care ◽  
Machine Learning Model ◽  
Product Service ◽  
Meal Quality

Numerous restaurants fight for the best quality for clients in the increasingly competitive restaurant sector. A restaurant is a business that demands more attention to customer care through continually enhancing customer service. The situation has an effect on the restaurant’s brand image, which is shaped by whether or not consumers are happy. Restaurant patrons may choose to benefit from others’ experiences by evaluating restaurants based on a range of factors, including meal quality, service, ambience, discounts, and deservingness. Users may leave reviews and ratings of companies and services, or just comment on other reviews. From one standpoint, bad (negative) reviews may influence how potential consumers make purchasing decisions. Sentiment analysis is a technique for determining the emotional content of a text that may be used to evaluate product/service reviews. Additionally, we may categorise them as positive or negative emotions. Understanding how the general public feels about various entities and products enables more relevant marketing, recommendation systems, and market trend research. Prepossessed data is collected, and then categorization is performed using a confusion matrix. This study enables us to create a report on the public’s perception of a particular restaurant. We developed a machine learning model and trained it using Bernoulli’s Naive Bayes classifier. Additionally, we evaluated the classifier’s performance on the test sample using evaluation matrices such as prediction, accuracy, recall, and F1 score. Customer review research has a significant influence on a business’s growth strategy.

THE IMPACT OF CUSTOMER SERVICE OF MEXICAN COMPANIES BASED ON CUSTOMER CARE

ATLAS JOURNAL ◽  
2018 ◽  
Vol 4 (8) ◽  
pp. 200-214
Author(s):  
Jose G. VARGAS HERNANDEZ
Keyword(s):  
Customer Service ◽  
Customer Care ◽  
The Impact

scholarly journals Analysis of Perceptions of Milk Consumption and Customer Service in the City of Riobamba, Province of Chimborazo

2021 ◽  
Author(s):  
O. Parada Gutiérrez ◽  
J. Vasco ◽  
C. Delgado
Keyword(s):  
Customer Service ◽  
Service Level ◽  
Level Of Service ◽  
Purchasing Decisions ◽  
Probabilistic Sampling ◽  
Palabras Clave ◽  
Para Determinar ◽  
Quality Of Products ◽  
Past Experiences ◽  
The City

The customer has become a source of strategic information about the quality of products and services. For this reason, the objective of this research was to analyze the level of service and mental processes of clients in making decisions to consume milk in the province of Chimborazo. Non-probabilistic sampling was used and data were collected from 50 clients and 75 representatives of small- and medium-sized companies in the city of Riobamba which participated in the Production Exhibition, Macají, Riobamba 2019. An electroencephalogram was used to determine whether the purchasing decisions were made at the unconscious level by reading brain waves. Three brands of milk that are sold locally were used. The study revealed that there were representative differences in stimulating people to different perceptions (visual, olfactory, gustatory) that influence the appreciation and purchasing decisions of milk. Similarly, it was found that there are decisions that the consumer makes unconsciously based on memories and past experiences that influence their present behavior at the time of consumption. The study also revealed the need to improve the level of service. Keywords: neuromarketing, perception, strategies, service level. Resumen El cliente se ha convertido en una fuente de información estratégica sobre la calidad del producto y del servicio. Por este motivo, el objetivo del artículo científico fue analizar el nivel de servicio y los procesos mentales del cliente para la toma las decisiones de consumir leche en la provincia de Chimborazo. El estudio se realizó mediante un muestreo no probabilístico con informaciones de 50 clientes y 75 representantes de pequeñas y medianas empresas de la ciudad de Riobamba que participaron en la Exposición de Producción, Macají, Riobamba 2019. Se utilizó el electroencefalograma para determinar si las decisiones de compra se realizan a nivel inconsciente mediante la lectura de ondas cerebrales. Para ello se utilizaron tres marcas de leche que se comercializan en la localidad. El estudio reveló que existen diferencias representativas al estimular a las personas a diferentes percepciones (visual, olfativa, gustativa) que influyen en la apreciación y decisión de compra de la leche. De igual modo, se constató que existen decisiones que realiza el consumidor de manera inconsciente basada en los recuerdos y experiencias del pasado que influyen en su comportamiento presente al momento del consumo. Asimismo, el estudio reveló la necesidad de mejorar el nivel de servicio. Palabras clave: neuromarketing, percepción, estrategias, nivel de servicio.

Artifical Intelligence and CRM

2022 ◽  
pp. 92-114
Author(s):  
Shailja Dixit
Keyword(s):  
Customer Service ◽  
Data Analytics ◽  
Business Models ◽  
Big Data Analytics ◽  
Digital Transformation ◽  
Disruptive Technologies ◽  
Artifical Intelligence ◽  
Customer Lifetime ◽  
Customer Care ◽  
Transformation Potential

Disruptive technologies such as IoT, big data analytics, blockchain, and AI have changed the ways businesses operate, with AI holding immense marketing transformation potential. AI is influencing marketing strategies, business models, sales processes, customer service options, and customer behaviors. AI-CRM's improving ability to predict customer lifetime value will generate an inevitable rise in implementing adapted treatment of customers, leading to greater customer prioritization and service discrimination in markets. CSPs are working through the challenging process of digital transformation, driven by the need to compete with fast-moving OTT and consumer tech players. CSPs need to move quickly and can advance digital transformation with solutions that leverage AI which can drive value across the business from network optimization and data analytics through to customer care and marketing engagement. The chapter tries to identify how AI is impacting the CRM in the telecom industry and leveraging the benefits of this technology for better customer management and growth.

scholarly journals A Study of Prisoner’s Dilemma Game Model with Incomplete Information

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Xiuqin Deng ◽  
Jiadi Deng
Keyword(s):  
Incomplete Information ◽  
Hash Table ◽  
Game Problem ◽  
Multiplayer Games ◽  
Total Income ◽  
Bayes Model ◽  
Bayes Formula ◽  
Machine Learning Model ◽  
Prisoners Dilemma ◽  
Novel Method

Prisoners’ dilemma is a typical game theory issue. In our study, it is regarded as an incomplete information game with unpublicized game strategies. We solve our problem by establishing a machine learning model using Bayes formula. The model established is referred to as the Bayes model. Based on the Bayesian model, we can make the prediction of players’ choices to better complete the unknown information in the game. And we suggest the hash table to make improvement in space and time complexity. We build a game system with several types of game strategy for testing. In double- or multiplayer games, the Bayes model is more superior to other strategy models; the total income using Bayes model is higher than that of other models. Moreover, from the result of the games on the natural model with Bayes model, as well as the natural model with TFT model, it is found that Bayes model accrued more benefits than TFT model on average. This demonstrates that the Bayes model introduced in this study is feasible and effective. Therefore, it provides a novel method of solving incomplete information game problem.

scholarly journals Sensory nutrition: The role of taste in the reviews of commercial food products

2019 ◽  
Author(s):  
Danielle. R. Reed ◽  
Joel D. Mainland ◽  
Charles J. Arayata
Keyword(s):  
Customer Service ◽  
Food Product ◽  
Food Products ◽  
Data Sets ◽  
Product Reviews ◽  
Purchasing Decisions ◽  
Consumer Review ◽  
Sensory Responses ◽  
Taste Experience

AbstractMany factors play a role in choosing what to eat or drink. Here we explored the role of sensation to explain these differences, drawing on consumer reviews for commercially available food products sold through an online retailer. We analyzed 393,568 unique food product reviews from Amazon customers with a total of 256,043 reviewers rating 67,553 products. Taste-associated words were mentioned more than words associated with cost, food texture, customer service, nutrition, smell, or those referring to the trigeminal senses, e.g., spicy. We computed the overall number of reviews that mentioned taste qualities: the word taste was mentioned in over 30% of the reviews (N= 142,768), followed by sweet (10.7%, N=42,315), bitter (2.9%, N=11,424), sour (2.1%, N=8,252), and salty (1.4%, N=5,688). We identified 38 phrases used to describe the evaluation of sweetness, finding that ‘too sweet’ was used in nearly 0.8% of the reviews and oversweetness was mentioned over 25 times more often than under-sweetness. We then focused on ‘polarizing’ products, those that elicited a wide difference of opinion (as measured by the ranges of the product ratings). Using the products that had more than 50 reviews, we identified the top 10 most polarizing foods (i.e., those with the largest standard deviation in ratings) and provide representative comments about the polarized taste experience of consumers. Overall, these results support the primacy of taste in real-world food ratings and individualized taste experience, such as whether a product is ‘too sweet’. Analysis of consumer review data sets can provide information about purchasing decisions and customer sensory responses to particular commercially available products and represents a promising methodology for the emerging field of sensory nutrition.

scholarly journals A Study of Customer Service Agent’s Pragmatic Identity Construction in Complaint Responses

2021 ◽  
Vol 4 (3) ◽  
pp. p89
Author(s):  
Cheng Huang ◽  
Ping Liu
Keyword(s):  
Identity Construction ◽  
Customer Service ◽  
Care Center ◽  
Management Strategies ◽  
Management Theory ◽  
Rapport Management ◽  
Customer Care ◽  
Complaint Handling ◽  
New Ideas ◽  
Research Questions

Positioned within rapport management theory proposed by Spencer-Oatey, this article investigates the customer service agent’s pragmatic identity construction in complaint response calls. Drawing on data of 42 complaint handling recordings from the customer care center of a Chinese airline company, this study tries to address these three research questions: 1) What types of pragmatic identities do the customer service agents construct in complaint response calls? 2) How are these pragmatic identities constructed through rapport management strategies? 3) What interpersonal functions do these pragmatic identities perform? By adopting a qualitative research method, this study has found that the agents mainly construct three default identities and one deviational identity in complaint response calls by employing nine rapport management strategies from four rapport management domains. These different pragmatic identities mainly perform three kinds of interpersonal functions: support face needs, support sociality rights and obligations, and support interactional goals. The findings further validates the feasibility of rapport management theory in the study of identity construction, and provides new ideas for future study on pragmatic identity construction in institutional communications.

Administrative Efficiency and E-government in the Greek Educational Sector

2020 ◽  
Author(s):  
Georgia Prokopiadou
Keyword(s):  
Public Administration ◽  
Customer Service ◽  
School Environment ◽  
Economic Value ◽  
Minimum Cost ◽  
Modern Technology ◽  
Information And Communications Technology ◽  
Electronic Government ◽  
Customer Care ◽  
Ict Adoption

Public organizations in Greece have been facing the challenges of electronic government since early 2000. Information and communications technology(ICT) adoption in public administration is a necessity and an unnegotiable need, taking into consideration the internationally recognized benefits. The main aim of e-government is to shape efficient and effective provision of services through the effective use of ICT. The modernization of public administrations is the key to transforming and generally improving the level of customer care (front office) as well as the level of internal administrative processes (back office). Modern technology provides improved information tools for e-services with minimum cost that facilitate transparency and lead to a democratic and effective transaction system. In the school environment, an effective and efficient administration is closely linked with the provision and delivery of improved and interconnected services that offer its users (parents, students, educational staff, etc.) the opportunity of direct and reliable customer service, effective transactions with the school, and accessibility to available administrative information. The development and formation of interconnected and decentralized services not only almost eliminates geographical and time limitations but also enhances users’ rights in terms of access to information and participation in public administration. The execution of administrative and school transactions in real time through the Internet and interconnected services ensures a speedier flow of information, allowing for a more economical use of time and resources. Thus, ICT facilitates and enhances the efficiency, connectivity, and effectiveness of services while reinforcing users’ direct and reliable access to available information. Information is closely linked with economic factors and has a major economic value. Technological means and tools reduce notably the cost of the delivery services and provide for instant and efficient transactions. Thus, given that there have been limited public economic resources in recent years, ICT provides the means of developing innovative platforms for administrative transactions that improve efficiency and productivity while at the same time reducing transaction costs. Beyond its reference to the process of producing quality public (and hence educational) services with less cost, it also provides an indicator of how public resources are used, particularly the extent to which the public services delivered actually meet users’ needs, at least to a certain level of satisfaction.

scholarly journals Salespeople Performance Evaluation with Predictive Analytics in B2B

2020 ◽  
Vol 10 (11) ◽  
pp. 4036
Author(s):  
Nelito Calixto ◽  
João Ferreira
Keyword(s):  
Performance Evaluation ◽  
Customer Relationship Management ◽  
Predictive Analytics ◽  
Confusion Matrix ◽  
Customer Relationship ◽  
Base Line ◽  
Customer Base ◽  
Bayes Model ◽  
Freight Forwarding ◽  
A Company

Performance Evaluation is a process that occurs multiple times per year on a company. During this process, the manager and the salesperson evaluate how the salesperson performed on numerous Key Performance Indicators (KPIs). To prepare the evaluation meeting, managers have to gather data from Customer Relationship Management System, Financial Systems, Excel files, among others, leading to a very time-consuming process. The result of the Performance Evaluation is a classification followed by actions to improve the performance where it is needed. Nowadays, through predictive analytics technologies, it is possible to make classifications based on data. In this work, the authors applied a Naive Bayes model over a dataset that is composed by sales from 594 salespeople along 3 years from a global freight forwarding company, to classify salespeople into pre-defined categories provided by the business. The classification is done in 3 classes, being: Not Performing, Good, and Outstanding. The classification was achieved based on KPI’s like growth volume and percentage, sales variability along the year, opportunities created, customer base line, target achievement among others. The authors assessed the performance of the model with a confusion matrix and other techniques like True Positives, True Negatives, and F1 score. The results showed an accuracy of 92.50% for the whole model.

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