Loyalty Programs Research Articles

Penerapan Algoritma Clustering untuk Segmentasi Pelanggan E-commerce berdasarkan Data Pembelian dan Aktivitas

In the current digital era, e-commerce has become one of the main pillars of global trade. With the ever-increasing amount of transaction and user activity data, e-commerce companies are faced with the challenge of understanding and managing diverse customer segments more effectively. This paper discusses the application of clustering algorithms for e-commerce customer segmentation based on purchasing data and user activity. The aim of this research is to identify homogeneous customer groups to support more targeted marketing strategies and increase customer retention. The problem faced is how to process big data originating from user transactions and activities on e-commerce platforms, as well as how to identify patterns that are useful for customer segmentation. The data used in this research includes purchase history, frequency of visits, length of time spent on the site, and interactions with certain products. The solution method applied in this research is the clustering algorithm, especially K-Means and DBSCAN. K-Means is used to group data into a predetermined number of clusters based on the Euclidean distance between data points. Meanwhile, DBSCAN is used to identify clusters with high density and separate data that is considered noise or outliers. Data preprocessing is carried out to clean and normalize the data before being applied to the clustering algorithm. Validation of clustering results is carried out using metrics such as Silhouette Score and Davies-Bouldin Index. The research results show that by applying the clustering algorithm, customers can be grouped into several segments that have similar characteristics. For example, we found groups of customers with high purchase frequency but low transaction value, as well as other groups with high transaction value but low purchase frequency. This information is very useful for companies to design more effective marketing strategies, such as special offers for customers with high transaction values ​​or loyalty programs for customers with high purchasing frequency. The conclusion of this research is that clustering algorithms can be a very effective tool in e-commerce customer segmentation, allowing companies to understand customer behavior patterns and develop more targeted and effective marketing strategies. Thus, implementing this method is expected to improve business performance and overall customer satisfaction.

The Influence of Service Quality and Brand Image on Customer Satisfaction and Customer Loyalty at the Pratama Marga Ayu Clinic in Badung, Bali

This research investigates the impact of service quality and brand image on customer satisfaction and customer loyalty at the Pratama Marga Ayu Clinic in Badung, Bali. Using SPSS and Smart-PLS for analysis, the study reveals that both service quality and brand image significantly and positively affect customer satisfaction, which in turn influences customer loyalty. Additionally, customer satisfaction mediates the relationship between service quality and customer loyalty. The findings highlight the importance of enhancing service quality and brand image to foster higher customer satisfaction and loyalty. The research concludes with practical suggestions for improving service and brand image, including increasing healthcare personnel, enhancing branding efforts, and implementing customer loyalty programs. Future studies are recommended to explore other influencing factors such as product reviews, location, and social media marketing to further enrich the understanding of customer decision-making.

Pengaruh Promosi terhadap Keputusan Pembelian Air Minum dalam Kemasan

This research aims to determine the effect of promotions on CV drinking water purchasing decisions. Zam Zami Alget. Promotions have a significant impact on CV drinking water purchasing decisions. Zam-Zami- Alget, through effective promotional strategies, such as advertising, discounts, or loyalty programs, consumers become more aware of products and tend to choose them because of the perceived added value offered. This research was carried out at CV. Zam Zami Alget, East Panyabungan District, Mandailing Natal Regency. This research method used is quantitative by describing the data using numbers. The sample of this research was 30 people using a quantitative approach. The results of simple linear regression analysis using SPSS version 25 produced the equation Y=17.394+ 0.524. Data analysis using the t test obtained a calculated t result of 3,790 and a t table at the 5% significance level of 1.701, so t calculated > t table and the significance value was 0.001 < 0.05. This shows that there is a promotional influence on the decision to purchase CV drinking water. Zam Zami Alget Alget, East Panyabungan District, Mandailing Natal Regency.

Evaluation of Blockchain Technology in the Context of Tourism Sector within the Framework of Diffusion of Innovation Theory: Challenges and Opportunities

Blockchain technology is one of the technologies emphasized both academically and practically due to the possibility of application integration in different fields. The tourism sector has an interest in blockchain technology due to its early and rapid adoption of technology. Today, blockchain technology is mainly used in finance. However, it is also preferred in tourism due to the opportunities it provides in data management, payment systems, identity management and loyalty programs. In this study, a literature review was first conducted to examine the use of blockchain technology in the tourism sector. Then, the first pioneer companies that emerged in the field of tourism were classified. The relationship between blockchain and tourism is evaluated within the scope of institutional analysis. Then, an analysis was carried out within the framework of the diffusion of innovation theory. As a result, it has been determined that blockchain technology is still developing. However, the promising and growing number of the first sectoral solutions increases the likelihood of acceptance. There is a lack of knowledge about blockchain among industry players and consumers. Integration of blockchain technology with tourism applications is ongoing, but no generally accepted standard has emerged. It has been determined that there are deficiencies regarding local and global legal regulations.

The Impact of Economic Incentives on the Purchase Behavior of Recycled Fashion and Footwear

This study investigates the impact of economic incentives on the purchase behavior of recycled fashion and footwear in Vietnam, addressing a critical gap in sustainable consumption research within emerging markets. Employing a mixed-methods approach, including a large-scale survey (n=1,023) and field experiments across 120 stores, we examine the effectiveness of various incentive types: discounts, loyalty programs, and government subsidies. Our findings reveal that while price discounts drive immediate sales increases (28.3% volume increase), loyalty programs foster superior long-term engagement (23.5% increase in repeat purchases) and higher average order values (31.7% increase). Government subsidies, particularly when combined with educational initiatives, also prove effective (27.3% sales volume increase). The study identifies key moderating factors, including environmental consciousness, age, and urban-rural location, which significantly influence the impact of these incentives. By providing empirical evidence on the nuanced effectiveness of economic incentives in promoting sustainable fashion choices, this research offers valuable insights for retailers, policymakers, and sustainability advocates. The findings contribute to bridging the intention-action gap in sustainable consumption and provide a foundation for developing targeted strategies to promote recycled fashion in emerging markets.

An Impact of CRM at Max Fashion Retail Limited

Effective customer relationship management (CRM) is essential for maintaining competitive advantage in the retail fashion industry. At Max Fashion, CRM strategies have been designed to enhance customer loyalty, streamline communication, and improve overall customer satisfaction. This study examines the various CRM practices employed by Max Fashion, including the use of customer data analytics, personalized marketing campaigns, and loyalty programs. By integrating technology such as CRM software and social media platforms, the company aims to better understand customer preferences and purchasing behaviour. The research highlights how these strategies contribute to increased customer retention and long-term business success. Through a combination of qualitative interviews with Max Fashion's management team and quantitative data analysis from customer feedback, the study identifies the key factors driving CRM effectiveness. This research provides valuable insights for fashion retailers seeking to implement or refine their own CRM strategies in an increasingly digital marketplace

The Impact of Sales Promotion Programs on the Loyalty of Saudi Telecom Company Customers STC

This study investigates the impact of sales promotion programs on customer loyalty in the context of the Saudi Telecom Company STC. Utilizing data from 457 respondents, the research examines the role of different types of sales promotions, the frequency of promotions, promotional communication channels, and seasonal promotions on customer retention and satisfaction. The findings reveal a significant positive relationship between frequent and well-structured sales promotions and customer loyalty, with a β value of 0.914 for the frequency of promotions. While promotional communication channels showed a moderate influence (β = 0.592), seasonal promotions played a strong role in driving repeat purchasing behavior (β = 0.768). Customer retention and interaction with loyalty programs were also shown to be critical intermediary factors that mediate the effect of sales promotions on loyalty. The study confirms that well-designed promotional programs and consistent communication efforts can significantly enhance customer retention and satisfaction. Limitations and recommendations for future research are discussed, including the need for cross-industry studies and the exploration of digital and personalized promotional strategies.

The Possibilities of Artificial Intelligence Usage in Loyalty Programs

From the year 2022, when the GPT 3 model became publicly available, Artificial intelligence (AI) has been a buzzword in marketing. To say it still is influencing the field would be an understatement with new models and technologies continuously emerging and existing ones getting better and better. Loyalty programs as a sales promotion tool have also undergone big changes in recent years and AI is bringing new opportunities and challenges to the field. In this paper, we investigate the possibilities of artificial intelligence usage in loyalty programs. We aim to showcase the diverse opportunities through which AI can enhance loyalty program experiences. Among those usage opportunities we put specific attention on AI personalization and predictive modelling. By harnessing AI capabilities, organizations can possibly find new ways to enhance customer engagement, satisfaction, and build stronger loyalty. In this paper we are also looking at the current state of loyalty programs in the selected market and the way AI is being used in them. It is important to note that we approach the topic from two points of view – customers` and brands`. That means that we are trying to highlight how certain AI technologies can possibly improve customers` experience as well as how AI may be a helpful tool for businesses who want to manage loyalty programs. The final part of our article includes information on the suggested ways AI technologies may be implemented into loyalty programs based on the information provided in previous parts of the paper. Suggested implementation strategies are also appropriate as a starting point for further research, where every single technology would be researched more in detail. The main goal of this article is to provide readers with a comprehensive overview of the possibilities of how Artificial Intelligence can be used in the context of loyalty programs today. The article is theoretical-empirical and is based on external information from trustworthy sources as well as our own research of certain AI technologies in the context of loyalty programs.

Fostering customer engagement behaviour with gamified loyalty programmes: a study from the “value get, value give” perspective

Fostering customer engagement behaviour with gamified loyalty programmes: a study from the “value get, value give” perspective

Cognitive Bias Sunk Cost in Marketing

The sunk cost cognitive bias, or sunk cost fallacy, is a human tendency to continue with: an investment, make a decision, business, couple or project based on the resources that have been invested, instead of making a current evaluation of the results. future benefits and costs. The objective of the research was to analyze the impact of sunk cost cognitive bias on customer decisions and its application in neuromarketing strategies. The specific objectives were: (i) Evaluate how sunk cost influences the perception of the value of products or services. (ii) Identify marketing strategies that exploit the sunk cost bias. (iii) Propose strategies to apply the sunk cost bias in marketing. The results show that the sunk cost bias significantly influences the perception of the value of products and services, affecting purchasing decisions, depending on the educational level, gender, and income level that influence the continuity in the use of products and services. due to previous investment of time or money; When purchasing expensive items customers feel obligated to continue using paid more even if it is not useful and used in full. The continuity in prepaid subscriptions, the perception of discounts for large quantities as a way to make better use of money, the probability of participating in loyalty programs for the accumulated rewards, the preference for payments and flexible cancellation, create a valuable perception of products they have previously invested in, the preference for repairing expensive items, and the perception of loss from a previous investment. It is concluded that the sunk cost cognitive bias significantly influences the decisions and behavior of a vast majority of customers, and how companies can use this information to design effective marketing campaigns.

Analysis of sales techniques from the perspective of psychology in MIPYMES (MSMEs)

The study analyzes how MSMEs can improve their business strategies using psychological principles such as scarcity, urgency, personalization, and the anchoring effect. These principles help understand and predict consumer behaviors, allowing sales strategies to be adapted more effectively. Additionally, the document highlights the importance of segmenting the market and building long-term relationships with customers to increase loyalty and satisfaction. In terms of customer satisfaction, the importance of exceeding customer expectations and ensuring fair and equitable treatment is highlighted. Strategies such as creating memorable experiences, implementing loyalty programs, and using customer feedback are key to improving satisfaction. Professional development and training are essential for the growth of MSMEs. Continuous training in soft skills such as emotional intelligence and effective communication improves employee performance and job satisfaction. Social learning theory and the 70-20- 10 model are proposed as effective approaches to competency development. Finally, the integration of psychology in business management contributes to organizational knowledge, promoting innovation and transformational leadership. MSMEs that apply these psychological principles can improve their performance and achieve sustainable success. The study concludes with recommendations to develop internal training programs, build trust with customers, and conduct regular market research to adapt sales strategies.

IMPULSE BUYING AND RETAILER LOYALTY PROGRAMS: ASSESS THE INFLUENCE OF LOYALTY PROGRAMS, REWARDS, AND CUSTOMER INCENTIVES ON IMPULSE BUYING

Comprehending the link between impulse buying and retailer loyalty programs is crucial in retail marketing. These programs, designed to encourage repeat purchases and foster customer loyalty with personalized rewards, profoundly impact impulsive behaviors. This study uses a mixed methods approach to assess the effectiveness of loyalty strategies across diverse consumer demographics. Rewards such as discounts, points, or exclusive access cultivate a sense of belonging and exclusivity, influencing purchasing decisions by triggering immediate incentives and urgency through limited time offers. Emotional and psychological factors drive impulse buying. The expectation of rewards, the excitement of earning points, and the sense of exclusivity all play roles in impulsive purchases. Retailers can capitalize on these motivators by tailoring programs accordingly. Demographic variables such as age, income, and shopping habits influence program effectiveness, with younger consumers typically favoring digital rewards and older consumers showing a preference for traditional discounts. Qualitative research delves into motivations and perceptions, providing rich insights into how loyalty programs influence impulse buying behaviors. This holistic approach offers valuable insights for refining marketing strategies, increasing customer loyalty, and promoting impulse buying through personalized rewards, real-time offers, and gamification.

PaaS Solutions for Scalable Social Media Engagement and Brand Loyalty Programs

Abstract: This research paper is a systematic analysis of how PaaS solutions can revolutionize the approach to increasing social network presence and improving brand reward programs. Based on the literature survey, comparison with current practices, and case study investigations, we study how, benefiting from PaaS, organizations deliver enhanced, efficient, and customer-centric experiences. This paper explores the attributes of PaaS that Microsoft especially targets for such applications the ability to perform real time analysis, omnichannel support and superior personalization. Based on the analysis of successful stories in different industries, we illustrate how, with the help of PaaS, Starbucks, Nike and Sephora were able to significantly enhance the specifics of customer interactions. It also focuses on the implementation issues that can be tackled. Some of the problems that may conflict with the research are data privacy, the complexity of integration, and sometimes, the use of the system by the targeted users. In addition, we analyze such innovative tendencies and tools as artificial intelligence, blockchain, augmented reality, and other future aspects concerning the development of PaaS-based loyalty and engagement solutions. The results reveal that PaaS provides definite top-line and bottom-line benefits for scalability, cost, and flexibility; it provides enterprises of all sizes with complex engagement solutions that were earlier only available to large enterprises. The study benefits both the academic and business worlds by offering theoretical and practical insights into the adoption of PaaS within businesses that desire to improve their app-based presence and connections with clients. The article ends with implementation suggestions and propositions for further research, focusing on the developments and trends related to cloud solutions concerning the future of customer engagement and their loyalty schemes..

Innovative strategic marketing practices to propel small business development and competitiveness

In today's dynamic and competitive business environment, small businesses face unique challenges in establishing their presence and achieving sustainable growth. This paper explores innovative strategic marketing practices that can propel small business development and enhance competitiveness. The primary focus is on leveraging digital marketing, personalization, customer engagement, data analytics, and strategic partnerships. Digital marketing has revolutionized how small businesses reach and engage with their target audiences. By utilizing social media platforms, search engine optimization (SEO), content marketing, and email marketing, small businesses can create cost-effective and highly targeted campaigns. These strategies not only increase brand visibility but also foster customer loyalty through consistent and relevant communication. Personalization is another key strategy that drives small business competitiveness. By tailoring marketing messages and offers to individual customer preferences and behaviors, businesses can create more meaningful and impactful interactions. This approach enhances customer satisfaction and encourages repeat business, contributing to long-term growth. Effective customer engagement is critical for small businesses to build strong relationships and foster community. Utilizing interactive content such as polls, quizzes, and live chats on social media and websites can create a more engaging and immersive customer experience. Additionally, loyalty programs and personalized incentives can strengthen customer retention and advocacy. Data analytics plays a crucial role in informing and optimizing marketing strategies. By analyzing customer data, market trends, and campaign performance, small businesses can gain valuable insights that drive strategic decision-making. This data-driven approach allows for more precise targeting, efficient resource allocation, and continuous improvement of marketing efforts. Strategic partnerships and collaborations with other businesses, influencers, and community organizations can also enhance marketing effectiveness. These partnerships can expand reach, provide access to new customer segments, and enhance credibility. Co-marketing initiatives, joint events, and cross-promotions are examples of how small businesses can leverage strategic alliances for mutual benefit. In conclusion, innovative strategic marketing practices, including digital marketing, personalization, customer engagement, data analytics, and strategic partnerships, are essential for propelling small business development and competitiveness. By adopting these practices, small businesses can effectively navigate the competitive landscape, achieve sustainable growth, and secure a strong market position in today's ever-evolving business environment.

Gasoline Discount Programs in Lakewood, Colorado: A Cost-Saving Analysis

Using gas price data and discount or cashback offers collected in Q4 of 2022, we examined which among four programs: wholesale club membership; grocery store fuel points; gas station loyalty programs; and third-party mobile applications, would likely provide the most savings to alternative demographics proxied by faculty, staff and students on campus, as well as the average American consumer. Though what’s best ultimately depends on personal circumstances, the key result from this research was that for the average American consumer who buys about 45 gallons of regular gas per month, Costco gas is best only if we disregard and exclude the membership fee in the cost of gas. Otherwise, Costco gas is best for premium gas only, and cedes supremacy to the third-party app Upside for regular gas. Upside is best for midgrade gas too. However, grocery fuel points supersede both Costco and Upside if the consumer spends about $300 or more and redeems the points for discounts at the pump. Ultimately, the study shows that consumers in both the high-spending and low-spending demographic may need to reassess their circumstances and reconsider their options to avoid potentially losing about $124 and saving $126 on gas a year.

Does customer orientation mediate the relationship between knowledge-based dynamic capability and the competitive performance of SMEs in India?

Purpose This paper aims to examine the mediating effect of customer functional and relationship customer orientation on the relationship between the knowledge-based dynamic capabilities and the competitive performance (CP) of small and medium enterprises (SMEs) operating in India. Design/methodology/approach The hypotheses proposed for this study were tested using data from the proprietors and competent authorities of 441 sample SMEs using structural equation modelling with partial least squares. Findings The results of this study indicate that knowledge-based dynamic capability (KBDC) has a significant connection with the CP of SMEs in a growing economy such as India. In addition, this study confirmed that the connection and functional customer orientation partially mediate the association between knowledge-based dynamic capabilities and the CP of SMEs. Practical implications This study’s practical contribution lies in its investigation of whether customer orientation serves as a mediator between KBDC and CP in SMEs in India. For instance, SMEs can implement strategies like customer feedback loops, loyalty programmes and customized solutions based on market insights to enhance customer orientation and ultimately improve CP. Originality/value This study analyses how SMEs can use knowledge-based dynamic capabilities and customer orientation to obtain a competitive advantage. This research contributes to the existing literature on knowledge management by expanding the notion of KBDC by integrating functional and relational customer orientation.

Strategy Development to Improve Brand Awareness and Sales Performance

The rapid growth of the beauty and skincare industry in Indonesia is driven by the extensive use of digital platforms for product promotion and marketing. Noera Beauty Care, a local beauty brand, faces challenges in enhancing its brand awareness and sales performance. This study aims to analyze the influence of digital marketing, content marketing, endorsement influence, and brand engagement on brand awareness and its impact on purchase intention. A mixed-method approach was employed, combining qualitative interviews with the CEO and head of marketing and quantitative surveys of 200 active social media users. The data were analyzed using PLS-SEM. The findings indicate that digital marketing, content marketing, and endorsement influence significantly impact brand awareness, while brand engagement does not. Brand awareness positively affects purchase intention. Based on these findings, several marketing strategies are proposed, such as product innovation through collaboration with influencers, creating live shopping or virtual try-on sessions, website updates and development, evaluation, and adjustment of marketing strategies, investing in IT infrastructure, strengthening relationships with consumers through loyalty programs, and creating educational content and quizzes to increase public knowledge about the benefits of Noera products.

Gift Cards, Promotions, Loyalty Programs: Prospects for Applying the Рrovisions on the Framework Contract to Consumer Protection Disputes

Gift Cards, Promotions, Loyalty Programs: Prospects for Applying the Рrovisions on the Framework Contract to Consumer Protection Disputes

Influence of Fashion Brand Loyalty Programs on Repeat Purchases in Uganda

Purpose: The aim of the study was to analyze the influence of fashion brand loyalty programs on repeat purchases in Uganda. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Design and implement loyalty programs that are customized to meet the specific needs and preferences of different customer segments. Establish and enforce policies that protect consumer data collected through loyalty programs. Ensuring robust data privacy measures will build consumer trust and encourage participation in loyalty programs, while also complying with legal standards and regulations. Unique Contribution to Theory, Practice and Policy: Expectancy-value theory, social exchange theory & theory of planned behavior may be used to anchor future studies on influence of fashion brand loyalty programs on repeat purchases in Uganda. Brands should use data analytics to identify key consumer segments and develop targeted rewards and incentives that resonate with each group, thereby enhancing program effectiveness and encouraging repeat purchases. Establish and enforce policies that protect consumer data collected through loyalty programs. Ensuring robust data privacy measures will build consumer trust and encourage participation in loyalty programs, while also complying with legal standards and regulations.

Examining the Nexus Between Customer Engagement and Satisfaction: Evidence from A Selected Retail Bank in South Africa

In the current retail banking environment, effective customer engagement is crucial for the success of organizations, impacting customer satisfaction, loyalty, and overall business performance. Given the competitive landscape and evolving customer expectations, it is essential for banks, especially Absa bank in South Africa, to understand the dynamics of customer engagement. This study aims to investigate how customer engagement initiatives influence customer satisfaction at Absa bank in the Durban area to provide strategic insights for enhancing competitiveness. Using theoretical frameworks such as Sashi's customer engagement cycle and Gronroos' model of service quality, this research explores the relationship between communication strategies related to organizational change and customer satisfaction levels at Absa bank in Durban. A quantitative research approach was employed, utilizing a structured questionnaire survey and convenience sampling to gather data from walk-in clients at various Absa bank branches. Statistical analyses, including descriptive and inferential methods, were used to analyze the data and test hypotheses. The results of the study offer valuable insights into customer preferences and expectations in the retail banking sector. Customers appreciate consistent messaging across different engagement channels and value personalized communication from the bank. Personalized calls, follow-up phone calls, and nonverbal cues such as a firm handshake were found to significantly impact customer perceptions and satisfaction with Absa bank's services. Customers display a high level of trust, satisfaction, and engagement with Absa bank, indicating the success of its customer engagement initiatives. The study also emphasizes the importance of social media in enhancing positive word-of-mouth and shaping consumer perceptions. Based on these findings, it is recommended that Absa bank implements a proactive customer engagement strategy focused on providing positive and personalized experiences to its existing customers. Key strategies include tailoring customer interactions, soliciting feedback, introducing loyalty programs, and utilizing various engagement platforms.