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International Journal of Advances in Business and Management Research (IJABMR)
Articles
DOI: 10.62674/ijabmr.2025.v2i04.005
Published: 2025-06-12

Customization and Personalization: Driving Engagement and Loyalty in the Digital Marketplace

Prestige Institute of Management & Research, 462021 Bhopal (M.P.)
Prestige Institute of Management & Research, 462021 Bhopal (M.P.)
Prestige Institute of Management & Research, 462021 Bhopal (M.P.)
Artificial Intelligence in Branding Customization Customer Engagement Personalization

Abstract

Purpose:The Purpose of this paper is to systematically review the literature available on the concepts of customization and personalization within the framework of digitized market structure. Being a customer centric era, the research aims at analyzing and evaluating the impact of these strategies on the customer engagement and customer loyalty taking into consideration the current trends, implications and challenges. The paper also delves into the role of Artificial intelligence and technological advancements in shaping branding strategies. Design/methodology/approach: The Systematic Literature Review(SLR) method is used to critically evaluate the existing literature on personalization and customization in branding. The in depth study of various relevant academic work provides a clear and holistic understanding of the topic. Findings: The digital era has revolutionized the approach and the experience that the companies are providing to the customers. Personalization and customization backed up with Artificial intelligence are playing a major role in increasing the customer satisfaction by providing tailored products and services.This ultimately impacts the customer connections and  loyalty towards the brands in a positive way. Although a major challenge is the existence of privacy concerns due to personalization. The marketers can overcome this by balancing this concern with the privatization and standardization. Practical implications: The marketers should utilize the consumers demand with the help of customer interactions to effectively craft their branding strategies and increase customer engagement and loyalty.

Introduction

The shopping experience today is the dominant reason for many companies to excel in the field of fast sales. From personalisation to customisation and giving a great experience from AR to omnichannel, companies have been coming up with many innovative techniques with which they can attract as many customers as they can. The customer today will try in-store service as well as online services of the same brand [1, 2]. The companies and the brands that have understood this mechanism can expect loyal customers, increased sales and an increase in the number of customers. AR and VR technologies have greatly revolutionised the marketing experience for consumers interacting with companies. In fact, there have been many studies that have shown that AI usage is a gift for some of the companies providing personalised experiences to their customers. The companies should focus on it to attain higher profits. There has been a paradigm shift in the market because of the AI powered marketing techniques offering personalised experiences to the customers [3, 4]. By giving a deeper, studied understanding of these technologies, the companies can offer a great amount of shift in the customer experience techniques, resulting in an increase of the loyal customers. With new technologies like VR and AR, apparel and accessories companies have been able to provide the customers with an out-of-this-world experience that was only limited to the gaming world before. It helps people to try on various things that they would have become hesitant in trying on in the stores [5]. These trends and innovations have made people get out of their comfort zone and explore new trends.

Companies have now started the D2C (Direct to Consumer) approach to cut short the cost of sales, and it has been a great deal for various companies over the past decade. The e-commerce sector has made great advancements that led to an increase in the customer experience with minimum costs, and the new technologies have made it easier for them to follow this road [6, 7]. The AI technologies offering various helps, like chatbots that can talk to the customer, giving them feedback; automated customer support giving the answers they need; and personalised advertising algorithms will lead to a higher number of sales. Automation streamlines repetitive tasks, allowing marketers to focus on strategic planning [8].

Lifestyle brands have befitted from these advancements the most.

a) The clothing brand H&M has entered into VR technology since 2022 that has given a tough competition to its competitors.

b) Adidas has also introduced the VR technology in their footwear brand from 2019 that led their customers virtually wear their iconic shoes and collections.

The country India with such a diverse division and a great number of target youth has been a potential target for the companies that are offering the lifestyle fashion. The diverse division of this country however has made it difficult for companies to apply similar approach towards consumers. Therefore, the companies should focus on region-based policies. The companies that are into customization and customized products should focus on the returning policies. The companies and brands that are into customization and standardization should focus on balancing the cost and demand between their product lines [9]. AI Technology has been a great motivation for advanced learning and putting things into automation, helping in data collection and analysis in decision making for the businesses. The new technology has been helping the companies and data analysts in collecting, storing, managing and analysis of information that has been a helpful aid in decision making for the future reference. AI can also benefit companies in making the data easier to understand and process [10, 11].

The mobile companies have become so important that the world revolve around it. This is the reason that the e- commerce business has made a boom in the economy. The smartphone uses and the technology has been making the companies to enter into giving the personalized experience [12, 13]. The retailers and the companies have started making the AR VR version to make the experience very personalized and maintain the interest of the consumers. These can build loyal consumers, and it can grow day by day [14, 15, 16]. This paper has analysed the research papers of the domains like personalization and customization and the use of AI in making the global reach.

Methodology

This study adopts a Systematic Literature Review (SLR) approach to examine the implementation of customisation and personalisation, considering AI as well as branding, which is set up to offer a methodical and clear means of assessing and including relevant literature on the given topic. The search of Research papers was done from the most reliable sources – Google scholar, ERIC and Emerald Insight – focusing on the research done from the year 2010 to 2024, to get a more comprehensive and systematic analysis of the subject and get a better idea of the impact on consumer behaviour after the implementation of these strategies.

An initial search was conducted using the specified keywords, which yielded numerous studies, which were then screened based on titles and abstracts to exclude irrelevant articles. Full texts of the remaining studies were reviewed to ensure they met the inclusion criteria. Any duplicates or irrelevant materials were removed. Out of an initial pool of 106 papers, 90 were included, and 16 were excluded based on the criteria already mentioned in the paper. The inclusion criteria ensured that the selected studies were pertinent to the research focus on customisation and personalisation. For the purpose of identifying common trends, impact on brand loyalty, customer satisfaction, opportunities and prospects in the same context, extracted data was categorised thematically. 4 major themes were identified which helped to categorise the paper and give a clear image of all the aspects of the research area. Apart from this, the review aimed to identify the research gaps and also to give the future research directions in one of the most trending agendas.

Literature Review

Key Words Analysis

The figure below (Figure 1) analyses the key themes of 105 research papers on personalisation and customisation in branding and the leading role of artificial intelligence in today’s digital era [17]. Significant areas of interest include the impact of these two strategies on consumers' satisfaction levels. This satisfaction is directly connected to the customer's loyalty to the brand.

Figure 1. Work Cloud of Key Words Used in the Research Papers Source - Developed for the purpose of research from review of research papers

Personalization and Customization in branding-

The customer expectations have revolutionised in the digital era, and the customers want to stand out while being a part of a crowd, as they want to get the product their way. Therefore, the marketers felt the need for personalisation so that they could serve and satisfy the consumers in a better way. The definition of the word “personalisation”, according to the Oxford dictionary, is “the action of designing or producing something that meets someone's individual requirement.” In this regard, personalisation is a way to acknowledge the uniqueness of each customer by satisfying them with products that are tailored according to their preference [18]. Given customers’ expectations, retailers must respond to the demand for personalised experiences not only to differentiate themselves but also to survive in the competitive environment. Specifically, personalisation uses insight based on each customer's personal and behavioural data to deliver a superior experience. More often than not, personalisation requires customer engagement to co-create a personalised experience, which can occur through customer reviews, purchase data, and social media interactions, among others [19].

Personalisation is not only about addressing the customer by name but also anticipating their needs and preferences, fostering a deeper connection and increasing brand loyalty. Therefore, personalisation has become an important element of the marketing mix. The process of personalisation consists of majorly 3 steps – the initial one being the understanding of the customers and the need; after this comes the delivering of the personalised offerings and thereafter measuring the impact of these initiatives on the consumers [20, 21]. Personalisation is often confused with customisation, and many times these two are used interchangeably. Although both Personalisation and customisation are used to enhance the user experience and engagement, leading to increased customer satisfaction, there is a slight line of difference between the two approaches. Personalisation includes tailoring a product or service on the basis of the individual preferences; this is usually done with the help of past purchases or behaviour of the customers [22, 23]. For example, marketers show the individuals the advertisement of their product or service based on their search history and also the personalised recommendations while shopping on a particular website. Customisation enables consumers to modify or choose the product based on their desires, offering a sense of control and empowerment, making them a part of the process indirectly [24, 25]. For instance, companies like Nike and Dell have embraced customisation by offering consumers the ability to design personalised shoes or laptops. This not only appeals to the customer’s need for individuality but also increases their emotional attachment to the product and brand.

Both personalisation and customisation play a vital role in the marketing process, but they differ in the way they engage with the consumer [26, 27, 28]. While personalisation relies on data to predict and cater to customer needs, customisation gives the consumer the power to make choices and influence the final outcome [29].  These strategies also require brands to use advanced technologies like AI and machine learning to gather and analyse customer data, which in turn helps deliver more relevant and personalised experiences to customers [30]. The below chart is from the report of the database of statistics which shows the types of data personalisation that are used by the companies.

Figure 2. Leading Types of Data Personalization Companies Used for Customer Profiling as of 2023 Source: Data from Statista report

Discussion

Role of AI

The imperatives of economic globalisation and heightened competitive dynamics demand heightened investments in innovation and customer engagement from companies. Over time, the world has steadily gravitated towards the digital approach [31]. In an interconnected age, customers wield unprecedented empowerment, capable of substituting functions, services, content, and products at will. This transformation is propelled by the rise of interactive Web 2.0 alongside technological advancements such as Big Data, Artificial Intelligence (AI), Augmented Reality (AR), and the Internet of Things (IoT). The incorporation of Augmented Reality (AR) technology into Customer Relationship Management (CRM) systems offers a myriad of advantages for enriching customer engagement. AR enables businesses to tailor experiences to each customer’s preferences and requirements. Augmented reality-driven experiences establish emotional relationships with consumers [32]. These emotional ties create a lasting impression and create strong brand devotion. AI algorithms help the companies to analyse the past purchase behaviour of the consumers, which is known as trend analysis, which ultimately is a contributor for personalisation [33, 34]. Apart from this, the AI driven tools like chatbots help to create a better customer experience by assisting and solving the queries of the customers [35, 36]. Also, a major part of AI in personalisation is played in the form of improved target marketing, as it sends personalised messages to the consumers on the basis of their liking and past behaviour of purchase [37, 38].

Inspiring Stories of Brands using personalization and customization with AI-

  • he clothing brand H&M has entered into VR technology since 2022 that has given a tough competition to its competitors.
  • Nykaa and Sephora again use personalized recommendations and AR to give a more personalized experience to its customers.
  • Netflix uses the algorithms by analysing the history and ratings to understand the liking and preferences of the viewers so that it can recommend relative content in future accordingly.
  • Same personalization strategy is used by Amazon and Myntra for personalized recommendations to its customers.
  • Brands like Adidas and Nike use customization strategy, giving the customers freedom to design their products with specific slogans, materials, styles and colours.

Figure 3. Figure 3: Figure Showing the Year and Frequency of Occurrence for the Given Research Papers Source: Developed for the purpose of research from review of research papers

The above figure (Figure 3) represents the distribution of publications across various years. It indicates the number of research papers published each year, ranging from 2010 to 2024. There are 106 articles overall, with a significant peak in 2019 that indicates the fluctuations in the amount of research produced over the years.

A – KEYWORDS (KW) KW-1- Personalization + Branding + Retail
KW -2- Customization + Retail
KW-3- AI + Personalization+ branding
KW-4- Personalization + Customization+ customer engagement
KW-5-                 AI + Branding +                  Impact               on Consumers
B- SEARCH ENGINES/DATABASES (DB) DB-1- Google Scholar DB-2- ERIC DB-3- Emerald Insight
C1–EXCLUSION CRITERIA (EC) EC1 – any of the selected keywords not appeared in the title, abstract, keywords, full text EC2 – Not in English EC3 – conference preceding, editorials
C2–INCLUSION IC1 – any of the selected keywords appeared in the title, abstract, keywords, full text. IC2-Studies from 2010 to 2024
Table 1. Search Strategy (Keywords, Databases, and Inclusion/Exclusion Criteria) Source: Developed for the purpose of research from review of research papers

Distribution of Research Studies by Region

Figure 4. Frequency Distribution by Region Source: Developed for the purpose of research from review of research papers

The figure 4 above highlights that the majority of research studies focus on customisation and personalisation at a global level. In terms of regional studies, the highest number have been conducted in the USA, followed by the UK, and then studies that span multiple continents [39, 40]. The global focus on these marketing strategies reflects a growing recognition of the importance of highlighting the innovations that are adopted by the companies across the globe while maintaining the privacy of the consumer data. The role of Artificial intelligence in the implementation of these aspects is inseparable, especially in the digital era [41, 42].

Types of Studies

The different study types that were part of the analysis are broken down in Figure 5. There are 22% of conceptual research, which suggests that the literature places a considerable priority on theoretical aspects and concepts. Also 21% of the research was qualitative, which involved in-depth investigation and comprehension of phenomena, and 19% was quantitative, focusing on the numerical data and statistical analysis. While less popular, other study types, including systematic literature reviews (SLR) with 9%, surveys with 8%, Empirical 7%, experimental studies with 6%, and others, made a significant contribution to the body of knowledge on customisation and personalisation in Branding.

Figure 5. Different Study Types Source: Developed for the purpose of research from review of research papers

Major Journals supporting the Research

The graph (Figure 6) displays how often papers about customisation and personalisation have been published in various journals. It is the journal of retailing that puts out the most, with 04 publications. The European journal of marketing and Journal of Business Research, Journal of Marketing Research, Journal of Interactive Advertising, and Journal of Retailing and Consumer Services all with 03 and there are other journals with two or one paper each. This list demonstrates that there is a significant quantity of research being carried out and published in a variety of journals on the subject of the adoption of these strategies of customer engagement. Such publication is a reflection of the significance and interest that is being shown in this area of educational research.

Figure 6. Frequency of Publication in various Journals Source: Developed for the purpose of research from review of research papers

Theme Source Frequency Paper No.
Personalization in Branding Aksoy et al. (2021), He et al. (2020), Herbas Torrico & Frank (2021), Fan et al. (2020), Tang Kmet & Copulsky (2022), Poon (2021), Nobile & Cantoni (2021), Altarteer et al. (2022), Kang et al. (2021), Scholdra et al. (2022), Völkel et al. (2021), Pallant et al. (2021), Mogaji et al. (2021), Tien (2020), Longo et al. (2021), Tien et al. (2020), Torres et al. (2022), Lee et al. (2021), Kim (2021), Kaiser et al. (2020), Liu et al. (2021), Kent et al. (2021), Yan et al. (2022), Perumal (2021), De Bellis et al. (2020), Wottrich et al. (2021), Kaptein & Parvinen (2022), Fettermann et al. (2022), Kwon et al. (2020), Putha (2022), Zanker et al. (2020), Varsha et al. (2021), Tran (2021), Kumar et al. (2022), Pallant et al. (2021), Hildebrand et al. (2021), Esenduran et al. (2022), Bleier et al. (2021), Shukla & Nigam (2022), Jost & Süsser (2021), Pollard et al. (2021), Rafieian & Yoganarasimhan (2021), Kang & Namkung (2022), Raz & Verma (2022), Jain & Sundström (2022), Gupta & Ramachandran (2021), Fu'Adi et al. (2021), Babatunde et al. (2022), Yang et al. (2021), Nogueira et al. (2022), Rajagopal (2020), Feng et al. (2022), Pereira (2021). 28 1, 3, 4, 5, 8, 11, 12, 15, 16, 17, 19, 31, 34, 38, 40, 41, 59, 60, 61, 71, 73, 78, 88, 89, 91, 92, 96, 99, 105
Customization in Retail Branding Sweeney & Lamberton (2020), Hsu et al. (2021), Banerjee et al. (2022), Lee et al. (2020), Kumar et al. (2021), Ballesteros et al. (2021), Berman et al. (2021), Schwartz et al. (2022), Hogg et al. (2020), Martínez & Bustos (2021), Aguiar et al. (2022), Heller et al. (2020), Villacís et al. (2021), Trivedi & Gandhi (2021), Buckley et al. (2021), Miotto et al. (2021), Lang et al. (2022), Nawaz et al. (2022), Lee & Choi (2021), Morales et al. (2022), Lee et al. (2020), Lee et al. (2021), Galvao et al. (2022), Ma et al. (2021), Kamath et al. (2021), Gao & Yang (2021). 24 2, 6, 7, 9, 14, 18, 20, 22, 24, 25, 27, 33, 39, 42, 47, 51, 54, 57, 62, 63, 66, 70, 101,103,
Impact on Consumers / Customer Engagement & Loyalty Zhang et al. (2020), Smith et al. (2021), Kim & Lee (2020), Singh et al. (2021), Nam & Kumar (2021), Liu et al. (2022), Yadav et al. (2021), Kim et al. (2021), Choi et al. (2022), Evans et al. (2022), Lee et al. (2022), Alcaide et al. (2021), Zhang et al. (2021), Zhou et al. (2021), Ye & Lee (2021), Islam et al. (2021), Binsal et al. (2021), Gómez et al. (2021), Rahman et al. (2021), Kumar et al. (2022), Zenger & Lim (2022), Slade et al. (2020), Bhat et al. (2021), Nair et al. (2021), Dube et al. (2021), Rodrigues et al. (2022), Shen & Jiang (2022) 25 3, 5, 6, 8, 11, 14, 16, 18, 21, 23, 28, 30, 34, 36, 37, 41, 43, 48, 50, 52, 55, 59, 61, 65, 69
AI & Technology in Personalization Le et al. (2021), Pan et al. (2021), Zhang & Yang (2020), Peng et al. (2022), Bhargava et al. (2021), Singh & Shukla (2021), Zhou & Liu (2021), Kim et al. (2021), Pál et al. (2021), Gupta et al. (2021), Choi et al. (2021), Roy et al. (2021), Yang et al. (2022), Dapino et al. (2022), Tarik et al. (2021), Shah et al. (2021), Wu et al. (2022), Wei et al. (2021), Liu & Li (2022), Kumar & Shankar (2021), Gupta et al. (2021), Kumar & Singh (2022), Yadav et al. (2021), Agnihotri et al. (2022), Yang et al. (2022), Tan et al. (2022), Liu et al. (2022). 24 1, 4, 7, 9, 10, 12, 13, 17, 19, 22, 26, 29, 31, 33, 35, 38, 40, 42, 44, 46,74, 83,86,90,98,104,
Table 2. Thematic Analysis

Ethical & Privacy Challenges

Despite being the inseparable part of the marketing mix, the rising adoption of personalisation and customisation with the alignment of Artificial Intelligence has raised a major question about the privacy concerns of the consumers. The base of personalisation is the collection, integration and analysis of the customer data from various platforms. There are times when this data is misused by certain companies or may be by third parties who are hired for data analysis and to manage algorithms. Nowadays the digitisation and globalisation have led to the spread of the markets across borders as well, which again hampers the local policies and laws. On the different side of the coin, the users also agree to the terms and conditions and policies without reading them properly, which can again be a matter of concern. Overall, the misuse of the personal data of the consumers can adversely affect the trust towards the brand, ultimately leading to a dissatisfied customer and negative public image. Additionally, over personalisation can make the consumer feel pressured and can make them feel that they are being manipulated. Therefore, to avoid all these issues, the companies should ensure that they adhere to the ethical guidelines and ensure the rights and privacy of their valuable customers are being respected.

Limitations

There have been certain limitations in this research paper, foremost being that the research is not industry specific and does not explain how different industries adopt the personalisation and customisation strategies. Also, the continuous advancements in the technology may lead the results to be outdated very soon, which requires the data and techniques to be updated on a regular basis. As per the review of 106 papers, a very minimal percentage is empirical, based on the surveys and feedback of the customers. So, it is recommended that more evidence-based research be done in the future and with a greater span of years so as to get a holistic view of the topic.

Conclusion

The ability to give tailored products and services has become a necessity in today’s digital world, and it is not only required to face the competition but also to manage the existence of the organisations. Successful personalisation programmes yield more engaged customers, as it increases convenience and reduces decision fatigue. Apart from this, these strategies provide a sense of being valued to the customers, thereby building a long-term connection to the brand, which ultimately fosters the overall sales and performance of that particular brand. Additionally, to the sales and performance enhancement, personalisation and customisation lead to gaining a competitive advantage for the organisation in the dynamic environment. At the same time the organisations should take into consideration the ethical and privacy policies, thereby maintaining transparency with their consumers.

Conflict of Interest

The authors express their gratitude to the institutions for their support in the accomplishment of this study.

Acknowledgement

The authors declare that they have no conflict of interests.

References

  1. Altarteer S, Vassilis C, Harrison D, Chan W. Product customisation: virtual reality and new opportunities for luxury brands online trading. InProceedings of the 21st International Conference on Web3D technology 2016 Jul 22 (pp. 173-174). https://doi.org/10.1145/2945292.2945317
  2. Alqurashi, D. R., Alkhaffaf, M., Daoud, M. K., Al-Gasawneh, J. A., & Alghizzawi, M. (2023). Exploring the impact of artificial intelligence in personalized content marketing: A contemporary digital marketing. Migration Letters, 20(S8), 548-560. https://doi.org/10.59670/ml.v20iS8.4630
  3. Bleier A, De Keyser A, Verleye K. Customer engagement through personalization and customization. Customer engagement marketing. 2018:75-94. https://doi.org/10.1007/978-3-319-61985-9_4
  4. Cavdar Aksoy N, Tumer Kabadayi E, Yilmaz C, Kocak Alan A. A typology of personalisation practices in marketing in the digital age. Journal of marketing management. 2021 Jul 24;37(11-12):1091-122. https://doi.org/10.1080/0267257X.2020.1866647
  5. De Bellis E, Hildebrand C, Ito K, Herrmann A, Schmitt B. Personalizing the customization experience: A matching theory of mass customization interfaces and cultural information processing. Journal of Marketing Research. 2019 Dec;56(6):1050-65. https://doi.org/10.1177/0022243719867698
  6. Esenduran G, Letizia P, Ovchinnikov A. Customization and returns. Management Science. 2022 Jun;68(6):4517-26. https://doi.org/10.1287/mnsc.2022.4305
  7. Fan H, Han B, Gao W, Li W. How AI chatbots have reshaped the frontline interface in China: Examining the role of sales–service ambidexterity and the personalization–privacy paradox. International Journal of Emerging Markets. 2022 May 16;17(4):967-86. https://doi.org/10.1108/IJOEM-04-2021-0532
  8. Fettermann DC, Echeveste ME, Tortorella GL. The benchmarking of the use of toolkit for mass customization in the automobile industry. Benchmarking: An International Journal. 2017 Aug 7;24(6):1767-83. https://doi.org/10.1108/BIJ-01-2016-0002
  9. He H, Harris LC, Wang W, Haider K. Brand identity and online self-customisation usefulness perception. Journal of Marketing Management. 2016 Sep 1;32(13-14):1308-32. https://doi.org/10.1080/0267257X.2016.1170720
  10. Hildebrand C, Häubl G, Herrmann A. Product customization via starting solutions. Journal of Marketing Research. 2014 Dec;51(6):707-25. https://doi.org/10.1509/jmr.13.0437
  11. Jost PJ, Süsser T. Company-customer interaction in mass customization. International journal of production economics. 2020 Feb 1;220:107454. https://doi.org/10.1016/j.ijpe.2019.07.027
  12. Kang M, Shin DH, Gong T. The role of personalization, engagement, and trust in online communities. Information Technology & People. 2016 Aug 1;29(3):580-96. https://doi.org/10.1108/ITP-01-2015-0023
  13. Kaptein M, Parvinen P. Advancing e-commerce personalization: Process framework and case study. International Journal of Electronic Commerce. 2015 Jul 3;19(3):7-33. https://doi.org/10.1080/10864415.2015.1000216
  14. Kent T, Kuksa I, Fisher T. Individualisation of markets: towards personalisation. Understanding Personalisation: New Aspects of Design and Consumption. 2022 Aug 21;127. https://doi.org/10.1016/B978-0-08-101987-0.00005-9
  15. Kolarevic B, Duarte JP, editors. Mass customization and design democratization. Routledge; 2018 Dec 7. https://doi.org/10.4324/9781351117869
  16. Kumar V, Rajan B, Venkatesan R, Lecinski J. Understanding the role of artificial intelligence in personalized engagement marketing. California management review. 2019 Aug;61(4):135-55. https://doi.org/10.1177/0008125619859317
  17. Kwon S, Ha S, Kowal C. How online self-customization creates identification: Antecedents and consequences of consumer-customized product identification and the role of product involvement. Computers in Human Behavior. 2017 Oct 1;75:1-3. https://doi.org/10.1016/j.chb.2017.04.051
  18. Surprenant CF, Solomon MR. Predictability and personalization in the service encounter. Journal of marketing. 1987 Apr;51(2):86-96. https://doi.org/10.1177/002224298705100207
  19. Lim WM, Rasul T. Customer engagement and social media: Revisiting the past to inform the future. Journal of Business Research. 2022 Sep 1;148:325-42. https://doi.org/10.1016/j.jbusres.2022.04.068
  20. Lee S, Kim KJ, Sundar SS. Customization in location-based advertising: Effects of tailoring source, locational congruity, and product involvement on ad attitudes. Computers in Human Behavior. 2015 Oct 1;51:336-43. https://doi.org/10.1016/j.chb.2015.04.049
  21. Levesque N, Boeck H. Proximity marketing as an enabler of mass customization and personalization in a customer service experience. InManaging Complexity: Proceedings of the 8th World Conference on Mass Customization, Personalization, and Co-Creation (MCPC 2015), Montreal, Canada, October 20th-22th, 2015 2016 Aug 11 (pp. 405-420). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-29058-4_32
  22. Liu N, Chow PS, Zhao H. Challenges and critical successful factors for apparel mass customization operations: recent development and case study. Annals of Operations Research. 2020 Aug;291:531-63. https://doi.org/10.1007/s10479-019-03149-7
  23. Longo F, Padovano A, Cimmino B, Pinto P. Towards a mass customization in the fashion industry: An evolutionary decision aid model for apparel product platform design and optimization. Computers & Industrial Engineering. 2021 Dec 1;162:107742. https://doi.org/10.1016/j.cie.2021.107742
  24. Mogaji E, Olaleye S, Ukpabi D. Using AI to personalise emotionally appealing advertisement. InDigital and social media marketing: Emerging applications and theoretical development 2019 Nov 12 (pp. 137-150). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-24374-6_10
  25. Nobile TH, Cantoni L. Personalization and customization in fashion: searching for a definition. Journal of Fashion Marketing and Management: An International Journal. 2022 Nov 28;27(4):665-82. https://doi.org/10.1108/JFMM-09-2021-0224
  26. Pallant JL, Karpen IO, Sands SJ. What drives consumers to customize products? The mediating role of brand experience. Journal of Retailing and Consumer Services. 2022 Jan 1;64:102773. https://doi.org/10.1016/j.jretconser.2021.102773
  27. Pallant JL, Sands S, Karpen IO. The 4Cs of mass customization in service industries: a customer lens. Journal of Services Marketing. 2020 Aug 28;34(4):499-511. https://doi.org/10.1108/JSM-04-2019-0176
  28. Park M, Yoo J. Benefits of mass customized products: moderating role of product involvement and fashion innovativeness. Heliyon. 2018 Feb 1;4(2). https://doi.org/10.1016/j.heliyon.2018.e00537
  29. Patil D, Rane NL, Rane J. The future of customer loyalty: How ChatGPT and generative artificial intelligence are transforming customer engagement, personalization, and satisfaction. The Future Impact of ChatGPT on Several Business Sectors. 2024:48-106. http://dx.doi.org/10.70593/978-81-981367-8-7_2
  30. Perumal P. Effects of environmental, personalisation and shopping elements in loyalty programmes on customer satisfaction. University of Johannesburg (South Africa); 2021.
  31. Pollard D, Chuo S, Lee B. Strategies for mass customization. Journal of Business & Economics Research. 2016 Jun 30;14(3). http://dx.doi.org/10.19030/jber.v6i7.2447
  32. Poon S. Designing the Brand Archetype: Examining the Role of Jungian Collective Unconscious in the Creative Customisation of Brands. The International Journal of Social Sciences and Humanities Invention. 2016;3(6):2228-39. http://dx.doi.org/10.18535/ijsshi/v3i6.06
  33. Scholdra TP, Wichmann JR, Reinartz WJ. Reimagining personalization in the physical store. Journal of Retailing. 2023 Dec 1;99(4):563-79. https://doi.org/10.1016/j.jretai.2023.11.001
  34. Shukla PS, Nigam PV. E-shopping using mobile apps and the emerging consumer in the digital age of retail hyper personalization: An insight. Pacific Business Review International. 2018 Apr 1;10(10).
  35. Tang Kmet C, Copulsky J. The future of personalisation: What new technologies are learning about customers. Applied Marketing Analytics. 2024 Mar 16;9(4):311-9. https://doi.org/10.69554/FPHT3579
  36. Torres EN, Lugosi P, Orlowski M, Ronzoni G. Consumer-led experience customization: A socio-spatial approach. Journal of Service Management. 2018 Mar 16;29(2):206-29. https://doi.org/10.1108/JOSM-06-2017-0135
  37. Valz D. Personalization: Why the relational modes between generative AI Chatbots and human users are critical factors for product design and safety. SSRN Electronic Journal. 2023 Aug 1. https://dx.doi.org/10.2139/ssrn.4468899
  38. Varsha PS, Akter S, Kumar A, Gochhait S, Patagundi B. The impact of artificial intelligence on branding: a bibliometric analysis (1982-2019). Journal of Global Information Management (JGIM). 2021 Jul 1;29(4):221-46. http://dx.doi.org/10.4018/JGIM.20210701.oa10
  39. Yan Y, Gupta S, Schoefer K, Licsandru T. A review of E-mass customization as a branding strategy. Corporate Reputation Review. 2020 Aug;23:215-23. https://doi.org/10.1057/s41299-019-00087-9
  40. Zhang C, Zheng X. Customization strategies between online and offline retailers. Omega. 2021 Apr 1;100:102230. https://doi.org/10.1016/j.omega.2020.102230
  41. Ashritha P, Reddy PS. Impact of Artificial Intelligence on Management Decision-Making. International Journal of Advances in Business and Management Research [Internet]. 2023 Dec. 12 [cited 2025 Jun. 11];1(2):10-8. https://doi.org/10.62674/ijabmr.2024.v1i02.002
  42. Diyin Z, Bhaumik A. The Impact of Artificial Intelligence on Business Strategy: A Review of Theoretical and Empirical Studies in China. International Journal of Advances in Business and Management Research [Internet]. 2025 Mar. 12 [cited 2025 Jun. 11];2(3):9-17. https://doi.org/10.62674/ijabmr.2025.v2i03.002

How to Cite

Motlani, S., Choudhary, S., & Jain, R. (2025). Customization and Personalization: Driving Engagement and Loyalty in the Digital Marketplace. International Journal of Advances in Business and Management Research (IJABMR), 2(4), 42–53. https://doi.org/10.62674/ijabmr.2025.v2i04.005

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