Customer Demographics Research Articles

Enhancing Customer Satisfaction

Customer satisfaction is crucial for the sustained success of e-commerce platforms, necessitating effective Customer Relationship Management (CRM) strategies to bolster relationships and overall performance. While existing research provides insights into factors like payment methods, shipping times, and customer demographics that influence satisfaction, significant gaps remain in fully understanding these dynamics, particularly within specific contexts such as Olist, a prominent Brazilian online marketplace. This study aims to address these gaps by leveraging advanced machine learning techniques on a comprehensive dataset comprising 100,000 orders spanning 2016 to 2018. Through meticulous analysis, which includes rigorous feature selection and the application of predictive models like logistic regression, decision trees, and random forests, we pinpoint crucial determinants of customer satisfaction. Our findings underscore the pivotal role of operational efficiencies in shaping customer experiences and offer actionable recommendations for enhancing e-commerce performance. By bridging these research gaps, this study not only contributes to the existing body of knowledge but also informs practical strategies for optimizing customer satisfaction and guides future research endeavors in the realm of e-commerce and CRM.

Optimizing Customer Relationship Management with Surprise Program: A Quantitative Approach

This research explores the implementation of customer relationship marketing strategies through the a program launched by PT XYZ. The program was designed to enhance customer loyalty with personalized special offers and exclusive promotions. This study employs quantitative methods and the data were obtained from the analysis of company reports and customer demographics, geography, behaviour, and psychology. Using K-means clustering, this study analyses data collected from XYZ's CRM surprise program, focusing on customer interests in video, games, and music, as well as their payment methods (prepaid or postpaid). The findings reveal significant variations in digital content consumption between prepaid and postpaid users. This segmentation enables XYZ to tailor its service offerings more effectively. The study highlights the potential for increasing customer satisfaction and loyalty through personalized offers, underscoring the importance of behavioural and psychographic data in optimizing service delivery.

Data Visualization of Bike Store Sales in Europe

This paper presents a comprehensive analysis of bike sales and customer demographics in Europe based on a dataset obtained from Kaggle.com. The dataset covers the period from 2011 to 2016 and includes information on customer age, gender, product categories, order quantities, unit costs, unit prices, profit, and revenue. The analysis utilizes data visualization techniques to identify key trends, including the top-selling products, customer purchasing power across different age groups and customer genders, and product profit margins. The findings suggest opportunities for retailers to target specific customer segments and product categories to maximize profits. Additionally, the report highlights the growing popularity of cycling as a sport and a healthy lifestyle choice, indicating a potential for increased demand in the bike retail market. Overall, the insights provided in this report aim to assist retailer chains in developing effective strategies to capitalize on the opportunities presented by the European bike sales market.

An Analytical Study on Account Holders' Perceptions and Satisfaction with reference to Banking Service Quality Post Merger of selected Public Sector Bank in India

Public Sector Banks in India have undergone significant mergers, which enable them to expand their activities, develop further, and strengthen their position as a key sector in the economy. Despite challenges such as rising non-performing assets, increasing frauds, political interference, and favouritism, mergers and acquisitions are graceful to benefit the newly formed banks, the economy, and the industry as a whole. This study examines the impact of recent bank mergers on customer awareness, perceptions, and satisfaction levels, focusing on four major public sector banks: Bank of Baroda, Canara Bank, Union Bank of India, and Indian Bank. Data were collected using structured questionnaires and personal interviews, incorporating 16 variables measured on a five-point Likert scale. The reliability of the data was confirmed with a Cronbach's Alpha value of 0.816, indicating high internal consistency. Analysis using One-Way ANOVA and descriptive statistics revealed significant variations in service quality perceptions across different age groups and bank affiliations, while awareness, digital banking, product/service efficiency, and trust/confidence showed consistent perceptions. The study highlights the positive reception of technological improvements post-merger and provides insights for banks to tailor their communication and service strategies to different customer demographics.

Parameters and barriers affecting the marketability of energy efficient residential buildings: a case study in Turkey

ABSTRACT The data indicate that merely improving energy efficiency within energy-efficient buildings (EEBs) is insufficient to significantly reduce the energy demand of the building sector. To achieve substantial reductions, strategies must also focus on increasing the number of EEBs within the existing building stock. However, research in this area remains limited. Therefore, this study aims to explore the current market demand and barriers for EEBs, examine the impact of various design decisions on housing prices, identify the factors influencing the marketability of residential buildings, and analyze customer purchasing decisions in Turkey (Türkiye). For this purpose, a comprehensive literature review was first made. It was observed that factors such as macroeconomic conditions, sales price, housing opportunities, location, brand, customer demographics, energy efficiency, housing features, and aesthetics were frequently discussed in the literature. Based on the literature review and preliminary study results, among other factors, aesthetic appreciation is considered the most applicable design strategy, and windows and balconies are identified as building components that can simultaneously affect energy efficiency, marketability, and aesthetics. Then, as a preliminary study to determine major marketing strategies, the housing marketing strategies were surveyed and analyzed from the real estate sector in different cities as provided in the advertisements posted on their websites. Furthermore, a comprehensive e-mail survey was conducted with 351 different real estate companies amongst 22 cities of Türkiye. Based on the findings, enhancing architectural designs could potentially elevate the perceived value of energy-efficient homes by up to 18% among consumers and this can increase the marketability.

Proposed Business Strategy to Increase Sales

Opening a coffee shop is one of Indonesia's most popular business ventures, driven by the nation's growing coffee culture. However, coffee shop owners face challenges in developing effective strategies to sustain their businesses, ensuring consistent revenue, positive customer feedback, and steady product sales. Bagi Kopi has quickly expanded its presence with multiple branches across various cities. Despite its rapid growth, there is a significant disparity in sales performance between branches, with the Yogyakarta branch underperforming compared to Bandung. This study aims to propose a business strategy to boost sales at Bagi Kopi, focusing on the Yogyakarta and Bandung branches. Utilizing a comprehensive root cause analysis through internal and external tools. The study employs a mixed-methods approach, integrating both quantitative data from customer questionnaires and qualitative insights from semi-structured interviews with Bagi Kopi stakeholders. The findings indicate that differences in customer demographics, preferences, and market conditions between Yogyakarta and Bandung significantly impact sales outcomes. Based on these insights, the study proposes targeted strategies for Bagi Kopi in Yogyakarta, focusing on enhancing customer engagement, improving service quality, and leveraging local market opportunities. The proposed strategy includes specific actions such as marketing initiatives, regular staff training, and effective facility management to align the Yogyakarta branch’s performance with that of Bandung.

Application of data mining technique for customer purchase behavior via Extended RFM model with focus on BCG matrix from a data set of online retailing

This study explores the integration of data mining, customer relationship management (CRM), and strategic management to enhance the understanding of customer behavior and drive revenue growth. The main goal is the use of application of data mining techniques in customer analytics, focusing on the Extended RFM (Recency, Frequency, Monetary Value and count day) model within the context of online retailing. The Extended RFM model enhances traditional RFM analysis by incorporating customer demographics and psychographics to segment customers more effectively based on their purchasing patterns. The study further investigates the integration of the BCG (Boston Consulting Group) matrix with the Extended RFM model to provide a strategic view of customer purchase behavior in product portfolio management. By analyzing online retail customer data, this research identifies distinct customer segments and their preferences, which can inform targeted marketing strategies and personalized customer experiences. The integration of the BCG matrix allows for a nuanced understanding of which segments are inclined to purchase from different categories such as “stars” or “cash cows,” enabling businesses to align marketing efforts with customer tendencies. The findings suggest that leveraging the Extended RFM model in conjunction with the BCG matrix can lead to increased customer satisfaction, loyalty, and informed decision-making for product development and resource allocation, thereby driving growth in the competitive online retail sector. The findings are expected to contribute to the field of Infrastructure Finance by providing actionable insights for firms to refine their strategic policies in CRM.

Text Mining Based Approach for Customer Sentiment and Product Competitiveness Using Composite Online Review Data

We aimed to provide a realistic portrayal of customer sentiment and product competitiveness, as well as to inspire businesses to optimise their products and enhance their services. This paper uses 119,190 pairs of real composite review data as a corpus to examine customer sentiment analysis and product competitiveness. The research is conducted by combining TF-IDF text mining with a time-phase division through the k-means clustering method. The study identified ‘quality’, ‘taste’, ‘appearance packaging’, ‘logistics’, ‘prices’, ‘service’, ‘evaluations’, and ‘customer loyalty’ as the commodity dimensions that customers are most concerned about. These dimensions should therefore serve as the primary entry point for improving the commodity and understanding customers. A review of customer feedback reveals that the composite reviews can be divided into three time stages. Furthermore, the sentiment expressed by customers can become increasingly negative over time. The product competitiveness based on the composite review can be characterised by four regional quadrants, such as ‘Advantage Area’, ‘Struggle Area’, ‘Opportunity Area’, and ‘Waiting Area’, and merchants can target these areas to improve product competitiveness according to the dimensional distribution. In the future, it will also be possible to take customer demographics into account in order to gain a deeper understanding of the customer base.

SUSTAINABLE FINANCE AT THE GRASSROOTS: INSIGHTS FROM KARNATAKA'S GREEN BANKING LANDSCAPE

In addition to global environmental challenges, sustainable finance has emerged as an important tool for reducing environmental risk and promoting economic growth. The study examines the development of sustainable finance at the grassroots level through an analysis of green banking initiatives in Karnataka, India, with special focus on Vijayapura district. The main objective of this study was to reveal the complex interplay between sustainable finance and community engagement through consumer knowledge and perception of green banking practices in the local context of Karnataka. Using mixed methods, the study combined quantitative surveys with qualitative interviews to critically examine the state of green banking awareness among consumers in Vijayapura district. The survey had collected data on customer demographics, knowledge of green banking principles, and attitudes towards a sustainable economy. In-depth interviews further clarified the factors affecting consumer participation in green banking schemes. Preliminary findings indicate that consumers in Vijayapura district differ in their awareness and understandings of green banking principles. While some respondents show a keen interest in sustainable finance and are willing to participate in green banking activities, others express limited knowledge or skepticism about its benefits about factors such as education; income and access to information emerge as significant determinants of customer perceptions and behaviors towards green banking. This study contributes to the evolving discourse on sustainable finance by providing insights into the implementation of green banking systems on the ground in Karnataka, India. By highlighting the opportunities and challenges associated with community engagement in the sustainable economy, the findings connect policymakers, financial institutions, and communities seeking to promote the environment the norms of sustainability and inclusive economic growth.

Customer personality analysis and clustering for targeted marketing

A customer’s personality has been stated to be a key determinant in his or her purchasing behavior. Therefore, in today's highly competitive market, understanding customer behavior and preferences is very important for businesses aiming to stay ahead. This research presents a customer personality analysis and clustering of consumers using machine learning into different consumer groups, this kind of clustering is key for targeted marketing strategies. The machine learning technique used in this work is the k-means machine learning clustering algorithm which divides a set of n observations into k clusters with the aim of designating each observation as a representative of a cluster. The model revealed insightful patterns and correlations between customer characteristics and their purchasing behavior. Through comprehensive data analysis and feature engineering, the model identifies key personality traits such as extroversion, openness, conscientiousness, agreeableness, and neuroticism, based on customer interactions, demographics, and psychographic data. The dataset that was used for this work was obtained from kaggle, it originated from different sources such as customer relationship management (CRM) systems, e-commerce platforms, social media platforms, surveys. The dataset comprises information on "people," "products," and "promotion," aiming to understand customer behavior, preferences, and responses to various marketing efforts. The output of this work provides businesses with actionable insights to tailor marketing campaigns and product offerings to individual customer preferences, thereby enhancing customer satisfaction and maximizing profitability.

Optimal decisions for green products with advanced payment scheme and selling price‐dependent demand under interval uncertainty

In the current competitive market, green products are becoming more and more in demand across all customer demographics due to environmental contamination. Consequently, this has a direct impact on the notable rise in product demand. Conversely, a product cannot be used or repurposed if its maximum useful life has already elapsed. Therefore, the product's maximum lifespan plays a crucial role in inventory management. Advance payment is a critical component of the supplier–retailer relationship for a seasonal product with high demand. By integrating these issues, an inventory model for perishable goods is created, wherein the demand for the good is impacted by both its selling price and its green level. The model also includes linearly time‐dependent holding costs. According to this model, product greenness has an increasing effect on per‐unit costs. Different numerical examples are studied for supporting this model. Optimality of the objective function is shown graphically as well as numerically with the help of MATHEMATICA software. Finally, a fruitful conclusion is reached after performing a sensitivity analysis and visually depicting the impact of changing various factors.

Understanding the Factors Affecting Trust and Security in Online Transactions for Maid Service Websites

In today's digital landscape, trust and security hold significant importance, especially in the realm of online transactions, particularly on maid service websites. This paper delves into the complex factors that influence users' perceptions of trust and security when engaging with these platforms. Through a thorough examination of existing literature and empirical analysis, this research identifies the key factors that shape users' perceptions of trust and security during online transactions within the maid service industry. The study explores various aspects, including website design, encryption protocols, payment gateways, privacy policies, and customer reviews, among others, to understand their impact on users' trust and security perceptions. Additionally, it investigates how factors like customer demographics, previous online experiences, and awareness of cybersecurity threats contribute to shaping these perceptions. Furthermore, the research delves into the strategies and best practices adopted by maid service websites to enhance trust and security. This includes implementing secure payment gateways, transparent communication channels, and robust data protection measures. The insights gained from this study provide a deeper understanding of the dynamics influencing consumer trust and security in the context of maid service websites. These findings offer valuable implications for industry practitioners to improve trust-building strategies and strengthen security measures, ultimately creating a safer and more trustworthy online environment for users. Keywords: MaidIn, Maid Service, Maid Jobs, Maid Service near me, Maid Service Project, Maid Service full Stack Web Development

RFM Segmentation Analysis for Determine Online Marketing Strategy: the Soul Coffee Mate Case Study

This study explores the impact of digital marketing on a cafe named The Soul, located in Jakarta. The cafe experienced a recent decline in sales attributed to factors such as new competitors, closures of nearby establishments, diminishing trends in working from cafes, and changes in customer demographics. Recognizing the need for a robust online marketing strategy, researchers aim to analyze customer segmentation using the RFM model, focusing on Recency, Frequency, and Monetary aspects of transactions over the past 11 months. The goal is to understand customer behavior, design effective online marketing strategies, and ultimately boost the company's revenue. The RFM analysis results identified eight customer segments for The Soul: Soulmate, Loyal Customers, Potential Loyalists, Promising, New User, At Risk, Can't Lose Them, and Hibernating. Proposed strategies include personalized promotions for different customer segments, such as monthly appreciation for "Soulmate" customers, discounts for loyal customers, and targeted communication for new or inactive users. These strategies aim to enhance customer engagement, loyalty, and satisfaction through digital promotions and personalized interactions. Keywords: Cafe Business, Customer Behavior, Customer Segmentation, Customer Loyalty, Digital Marketing, Online Promotion, RFM Model, Sales Analysis

IMPACT OF PACKAGING DESIGN ON CONSUMER PURCHASING DECISIONS

Packaging design is becoming more important in today's competitive marketplace as items compete for consumers' attention in a sea of choices. The complex world of package design and its influence on customer behavior is the subject of this master's thesis. The purpose of this study is to decipher the complex relationship between the visual appeal, practicality, and consumer psychology of packaging by drawing on a review of relevant literature, survey data, and real-world examples. Aspects of visual design, including color, typography, and images, as well as structural components, including size, form, and material choice, are investigated in the research on packaging. It takes a look at how these factors affect various product categories and customer demographics in terms of perceptions, preferences, and intents to buy. In addition, the study explores how packaging conveys brand values, identity, and product qualities, which in turn affects consumer perception and loyalty to the brand. Keyword : Packaging design, consumer behavior, aesthetics, functionality, consumer psychology, visual elements, color, typography, imagery,

A Machine Learning Based Approach to Predict Customer Churn in Airline Industry : The Case of India

This research addresses the challenge of customer churn in the airline industry by leveraging machine learning (ML) techniques to predict and understand the factors influencing customer attrition. Drawing on a comprehensive dataset encompassing customer demographics, flight history, and service interactions, we employed rigorous data preprocessing techniques and evaluated various ML algorithms

AI-INFUSED CHATBOTS FOR CUSTOMER SUPPORT: A CROSS-COUNTRY EVALUATION OF USER SATISFACTION IN THE USA AND THE UK

As organizations increasingly integrate artificial intelligence (AI)-infused chatbots into their customer support strategies, understanding user satisfaction becomes paramount. This abstract provides an overview of a cross-country evaluation that examines user experiences with AI-driven chatbots for customer support, drawing insights from both the USA and the UK. The evaluation explores the deployment of AI-infused chatbots in customer service scenarios, focusing on how users in these two regions interact with and perceive the effectiveness of chatbot interactions. The study considers the impact of cultural nuances, linguistic variations, and user expectations on the overall satisfaction with AI-driven customer support. In the USA, a market known for its technological adoption and diverse consumer landscape, the evaluation investigates how AI-infused chatbots contribute to enhancing customer experiences. It explores factors such as response time, accuracy, and the adaptability of chatbots in addressing diverse customer queries. In the UK, with its unique cultural and linguistic characteristics, the study examines how AI-driven chatbots align with customer expectations and preferences. It considers the role of chatbots in streamlining customer interactions, providing timely resolutions, and maintaining a high level of user satisfaction. Through a comparative analysis, the evaluation aims to identify patterns, disparities, and commonalities in user satisfaction with AI-infused chatbots in customer support between the USA and the UK. It delves into the challenges faced by chatbots in understanding and responding to regional linguistic nuances, cultural sensitivities, and the adaptability required for diverse customer demographics. The abstract encapsulates the essence of the cross-country evaluation, shedding light on the evolving landscape of AI-driven customer support and its implications for user satisfaction in distinct markets. Insights from this evaluation contribute to the ongoing discourse on optimizing AI-infused chatbot experiences for diverse customer bases, offering valuable considerations for businesses seeking to enhance their customer support strategies on an international scale.. Keywords: Ai-Infused Chatbots, Customer Support, USA, UK, Cultural Nuances, Technological Landscapes.

Factors Influencing Customer Decision-Making In Choosing E-Cab Services Over Traditional Taxis In Calabar Metropolis

This research study aims to investigate the factors influencing customer choices between e-cab services and traditional taxis in Calabar, focusing on service quality, operational efficiency, pricing strategies, and customer incentives. Addressing gaps in existing literature, the study explores the unique preferences and decision-making criteria of customers in the Calabar metropolis when selecting transportation services. Employing a cross-sectional, descriptive design, the research utilized a structured questionnaire to collect data from 463 adults who have used both e-cab and traditional taxi services. The questionnaire was developed by the researchers, validated by experts and trial-tested for reliability purposes. The reliability coefficient was estimated at .93 using the Cronbach alpha reliability estimate. Collected data were subjected to analysis using descriptive statistics, relative important index, independent t-test and analysis of variance. The analysis revealed that the key factors influencing customer choices in Calabar between e-cab services and traditional taxis include convenience, cleanliness, ride comfort, safety, and cost-related incentives; Customer demographics such as age, gender, and income level did not significantly influence preferences between e-cabs and taxis in Calabar and that service speed, reliability, and competitive pricing strategies play a crucial role in customer decision-making. Recommendations include prioritizing service quality, implementing competitive pricing strategies, and focusing on service speed and reliability to enhance customer satisfaction and retention.
 

Adoption of Online Home Services an Empirical Study of Consumer Behaviour in Ludhiana City

The advent of technology has revolutionized the service industry, particularly in the realm of home services. This study aims to investigate the nuanced relationship between demographic factors and the adoption of online home services by customers. Recognizing the increasing prevalence of digital platforms offering services ranging from home maintenance to professional consultations, understanding the demographic influences on consumer adoption becomes imperative for service providers and marketers. This research employs a mixed-methods approach, combining quantitative surveys and qualitative interviews, to gather comprehensive insights into the preferences and behaviors of consumers in the online home services sector. The study focuses on key demographic variables such as age, income, education, and geographic location to discern patterns and correlations that may influence the likelihood of customer adoption. The findings are expected to contribute to both academic literature and industry practices by shedding light on the factors that drive or inhibit the adoption of online home services among different demographic groups. Moreover, implications for marketing strategies and platform design may emerge from understanding how customer demographics intersect with their preferences, trust levels, and technological literacy. As the digital landscape evolves, this research aims to provide actionable insights for businesses aiming to tailor their services to diverse customer segments. The outcomes of this study will contribute to a deeper understanding of the socio-economic and cultural factors influencing the adoption of online home services, fostering a more informed and effective approach for businesses operating in this dynamic and rapidly growing sector.

War on Aisle 5: Casualties, National Identity, and Consumer Behavior

A growing body of research argues that external threats from the international system strengthen ethnocentrism and authoritarianism, personal values anchored in national identity. We evaluate a necessary implication of this argument, that these shifting values drive change in broader social behaviors. Our focus is revealed value change in a non-political setting: American consumers’ choice of supermarket brands that symbolize national identity. Our empirical analyses leverage US counties’ quasi-random exposure to US Iraq War casualties to identify the effects of local casualties on the weekly market share growth of “American” supermarket brands. We analyze weekly supermarket scanner data for a representative sample of over 1,100 US supermarkets and 8,000 brands. During 2003-2006, the weekly market share of American brands grew relative to non-American brands in casualty-exposed supermarkets. Variation in share growth across customer demographics is consistent with reactions to external threat. We rule out alternative mechanisms including partisan cues, other product characteristics, and animosity towards other countries. These findings strengthen IR’s theoretical microfoundations by showing that international politics can reshape values enough to change broader social behaviors.

A look at Singapore hostess bars through the lens of Negri and Chakrabarty

This article, written in a confessional, autoethnographic style, explores the author’s experiences over a number of years with Singapore hostess bars/pubs. The research method is participant-observation of practices, discourses, pricing models and customer demographics, and knowledge gained from hostesses, bar managers and musicians. The law aspect of the article is critiquing the lack of citizenship rights and marriage rights for foreign workers in Singapore such as pub hostesses and construction workers. It also looks at the working conditions and cultures of the pubs, and describes the alienation and emotional labour involved in delivering heavily racialized and gendered services. Neither Filipina/Vietnamese hostesses nor Europeans have established places within the Singapore citizenship narrative or in government policy, which relies upon the hegemonic CMIO (Chinese, Malay, Indian, Others) Model. Filipina and Vietnamese pub hostesses do not fit neatly within this model and are hindered by the power of the narrative.