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This study aims to investigate the influence of the service concept on customer acquisition and when the relationship is moderated with manager’s experience in Savings and Credit Cooperative Societies (SACCOS) within Dar es Salaam City, Tanzania.

The study adopts a cross-sectional research design and utilizes simple random sampling to select 226 respondents, all of whom are managers of SACCOS in Tanzania. Data were collected through a questionnaire and analyzed using a partial least square structural equation modeling (PLS-SEM).

The findings indicate that service concept have a highly statistically significant impact on customer acquisition, with a p-value of less than 0.05. Conversely, managers’ experience also influences customer acquisition by the p-value of less than 0.05. The result also confirms the significance influence of positive moderating effect of manager’s experience on the relationship between service concept and customer acquisition, with a p-value of less than 0.05, therefore it shows that manager’s experience facilitate the influence of service concept to customer acquisition.

The findings of this study provide valuable insights for SACCOS aiming to thrive and attract more customers. By understanding the nuances of service concepts, these institutions can refine their strategies for customer acquisition effectively.

The study’s insights into the composite effect of service concepts hold significance for SACCOS seeking to enhance their customer acquisition strategies enhanced by manager’s experience. These findings contribute new perspectives to the SACCOS and other related financial services sector, offering fresh insights into innovation and customer-centric approaches.

Artificial intelligence (AI) is increasingly applied by businesses to optimize their processes and decision-making, develop effective and efficient strategies, and positively influence customer behaviors. Businesses use AI to generate behaviors such as customer retention (CR). The existing literature on “AI and CR” is vastly scattered. The paper aims to review the present research on AI in CR systematically and suggest future research directions to further develop the field.

The Scopus database is used to collect the data for systematic review and bibliometric analysis using the VOSviewer tool. The paper performs the following analysis: (1) year-wise publications and citations, (2) co-authorship analysis of authors, countries, and affiliations, (3) citation analysis of articles and journals, (4) co-occurrence visualization of binding terms, and (5) bibliographic coupling of articles.

Five research themes are identified, namely, (1) AI and customer churn prediction in CR, (2) AI and customer service experience in CR, (3) AI and customer sentiment analysis in CR, (4) AI and customer (big data) analytics in CR, and (5) AI privacy and ethical concerns in CR. Based on the research themes, fifteen future research objectives and a future research framework are suggested.

The paper has important implications for researchers and managers as it reveals vital insights into the latest trends and paths in AI-CR research and practices. It focuses on privacy and ethical issues of AI; hence, it will help the government develop policies for sustainable AI adoption for CR.

To the author's best knowledge, this paper is the first attempt to comprehensively review the existing research on “AI and CR” using bibliometric analysis.