The Journal of Marketing Analytics was created in 2013 by Palgrave Macmillan from the merger of the Journal of Targeting, Measurement, and Analysis for Marketing (2001–2012) and the Journal of Database Marketing and Customer Strategy Management (2001–2012) (ABDC), with Dr. Tom Breuer as its first editor-in-chief. The JMA team would like to thank Dr. Tom Breuer for his work and innovative thinking in starting this project. The JMA is a peer-reviewed journal that publishes four print and online issues per year, provides a single accessible resource for the rapidly changing field of marketing analytics, combines the best of applied scientific research and commercial best practices, and covers targeting, segmentation, big data, customer loyalty, CRM, data quality management, marketing strategy, and more. The journal also includes sophisticated analytic approaches, such as fuzzy-set qualitative comparative analysis, product reviews, and multilevel modeling to improve neighborhood targeting. It provides a means to stay informed about this rapidly changing field and leverage the power of data to achieve sustainable competitive advantage.

The Journal of Marketing Analytics is a publication addressing this blossoming field by combining applied research and practice papers. Its unique combination of academic research and insights from commercial best practices makes it a valuable resource for both scholars and practitioners. The journal aims to blend rigorous scientific research methods with the applicability of real-world case studies. Papers are selected through a double-blind review process based on their content and merit, ensuring the publication of the best papers in the field. JMA is designed to help scholars and academics stay informed about the latest developments in the science of marketing analytics and help professionals in marketing analytics stay abreast of the latest trends and implications of cutting-edge analytics research.

In today’s competitive markets, merely storing and reporting information is insufficient. Companies must possess the ability to comprehend vast amounts of data, apply insights to their market approach, respond to new competitors, and adapt to shifting market conditions. To achieve this, marketing analytics has become a central component of data-driven decision-making. Companies can no longer rely solely on intuition to make decisions, as data are now a crucial source of sustainable competitive advantage. While new products can be quickly replicated, leveraging data strategically remains one of the few effective ways companies can stand out in a globalized world, where employees are less loyal and businesses are frequently on the move.

The JMA is included on the ABS and ABDC journal ranking lists and is a Q1 journal by Scimago Journal&Country Rank. Figure 1 shows the citations per document as reflected by SJR. In this context, we would also like to thank our reviewers, special issue editors, publishing team, and authors who put much effort into our journal's creation and constant improvement and growth. Table 1 includes our most cited papers since 2013, according to Scopus.

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Citations per document (SJR)

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Table 1 Most cited articles
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We explored the essential research topics in JMA by performing a bibliometric analysis of the articles published in printed issues and currently online since 2013, as included in the references section. We first downloaded all the bibliometric data for each article through Scopus. Figure 2 includes a co-citation network map obtained through a network analysis in VOSViewer of the keywords provided by the authors.

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Co-citation network mapping

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The first cluster is focused on data-driven customer insights, reflecting big data and data mining use for customer segmentation, forecasting, and retail. Researchers in this group are interested in understanding how to use customer data to enhance engagement and increase customer lifetime value. The second area analyzes brand loyalty, machine learning, and sentiment analysis for social media marketing. Research in this cluster studies methods for using data to identify and target loyal customers and increase brand loyalty.

The marketing budget optimization group researched brand management, budget allocation, and digital marketing topics. Articles in this group discussed how to effectively manage and allocate marketing budgets to maximize brand satisfaction and loyalty. The fourth area of research reflects customer loyalty and satisfaction, as well as the use of PLS-SEM. These studies review how to measure and enhance customer satisfaction and loyalty and how to use social media to promote sustainability initiatives.

Another research stream is focused on customer relationship management, customer segmentation, and decision calculus for retention. Researchers in this cluster are interested in understanding how to use customer data to optimize retention and improve customer relationships. Finally, the last group is focused on analytics, sales, and text mining. These studies analyzed how to use analytics and text mining to improve sales performance and enhance customer engagement.

We then performed a machine-learning-based lexical, thematic analysis of the abstracts of all JMA papers using Leximancer to extract the essential themes approached during the ten years of publication. Similar insights were reflected in the themes extracted in this analysis, as shown in Fig. 3. The themes emphasize the central role of customers in the marketing analytics framework and their role in the modeling and application of analytics. Methodologies, modeling, forecasting, and prediction have become essential in modern analytics, especially considering the focus on the bottom line, performance, and sales.

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Thematic analysis results

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Overall, the analysis highlights the diversity of research themes and approaches within marketing analytics, ranging from data mining and machine learning to customer relationship management and sustainability. The research areas identified in this analysis can be used to guide researchers to develop a better understanding of the key topics and themes in the field of marketing analytics. Considering the evolution of marketing analytics and the emerging themes from the ten years of JMA, we propose these topics for future research on marketing analytics:

  • Integration of multiple data sources to gain more accurate and comprehensive insights into customer behavior and preferences.

  • Personalization and customization, using machine learning and sentiment analysis to personalize marketing messages and products for individual customers.

  • Optimization of marketing budgets and allocating resources more effectively.

  • Omnichannel customer experience and optimizing touchpoints across channels.

  • Artificial intelligence and automation to enhance the effectiveness of marketing campaigns and improve customer experiences.