Customer Loyalty Management - Crossref Bibliographic Metadata

This dataset provides detailed bibliographic metadata records for scholarly publications related to 'Customer Loyalty Management', as retrieved from Crossref.org. This metadata corpus facilitates in-depth exploration of the academic discourse surrounding strategies to foster enduring customer relationships. Contextual Overview of Customer Loyalty Management: 1. Definition and Context: Customer Loyalty Management involves strategic efforts and programs designed to build and maintain long-term relationships with customers, encouraging repeat purchases and reducing churn. It focuses on understanding customer needs, delivering superior value, and creating positive experiences. While customer relationships have always been important, formalized loyalty management gained prominence with the rise of database marketing, CRM systems, and the recognition of the high cost of customer acquisition versus retention. 2. Strengths and Weaknesses: Strengths include increased customer lifetime value, reduced marketing costs, generation of positive word-of-mouth, and greater resilience to competitive pressures. Loyalty programs can provide valuable customer data. Weaknesses may involve the cost of loyalty programs, potential for programs to reward existing behavior rather than drive new loyalty, difficulty in differentiating loyalty initiatives, and the risk of "loyalty fatigue" among consumers if programs are not genuinely valuable or well-managed. 3. Relevance and Research Potential: Customer Loyalty Management is critical in today's competitive markets, where customer choice is abundant and switching costs can be low. It is a core component of relationship marketing and customer strategy. Research opportunities include the impact of digital and mobile technologies on loyalty program design and effectiveness, the role of emotional connection versus transactional benefits in building true loyalty, measuring the ROI of loyalty initiatives, and strategies for fostering loyalty in subscription-based and platform-based business models. Dataset Structure and Content: The dataset consists of one or more archives. Each archive contains a series of approximately 850 monthly folders (e.g., spanning from January 1950 to January 2025), reflecting a granular month-by-month process of metadata retrieval and curation for Customer Loyalty Management. Within each monthly folder, users will find several JSON files documenting the search and filtering process for that specific month: term_results/: A subfolder containing JSON files for results of initial broad keyword searches related to Customer Loyalty. merged_results.json: Aggregated results from these individual term searches before advanced filtering. filtered_results.json: Results after applying a more specific, complex Boolean query (e.g., ("customer loyalty" OR "loyalty management" ...) AND ("marketing" OR ...)) and exact phrase matching to refine relevance. The exact query used is detailed within this file. final_results.json: This is the primary file of interest for most users. It contains the curated, deduplicated (by DOI) list of unique publication metadata records deemed most relevant to 'Customer Loyalty Management' for that specific month. Includes fields like Title, Authors, DOI, Publication Date, Source Title, Abstract (if available from Crossref). statistics_results.json: Summary statistics of the search and filtering process for the month. This granular monthly structure allows researchers to trace the evolution of academic discourse on Customer Loyalty Management and identify relevant publications with high temporal precision. For an overview of the general retrieval methodology, refer to the parent Dataverse description (Management Tool Bibliographic Metadata (Crossref)). Users interested in aggregated publication counts or trend analysis for Customer Loyalty should consult the corresponding datasets in the Raw Extracts Dataverse and the Comparative Indices Dataverse.