# Customer Relationship Intelligence: Integrating CRM and MDM for Enhanced Customer Engagement

arXiv: https://arxiv.org/abs/2609.06189 · HTML: https://mlsanity.com/paper/2609.06189/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 45 references that are in the map.
- First posted on arXiv 5 Sep 2026.

## Builds on (most cited first, 3 of 3)

- [Case Studies on using Natural Language Processing Techniques in Customer Relationship Management Software](https://mlsanity.com/paper/2106.05160/) (2021)
- [Enterprise Analytics using Graph Database and Graph-based Deep Learning](https://mlsanity.com/paper/2108.02867/) (2021)
- [A Framework in CRM Customer Lifecycle: Identify Downward Trend and Potential Issues Detection](https://mlsanity.com/paper/1802.08974/) (2018)

## Abstract (arXiv)

This study examines how Customer Relationship Management (CRM), Master Data Management (MDM), and Customer Knowledge Management (CKM) jointly constitute a Customer Relationship Intelligence (CRI) framework for enhanced Customer Engagement (CE). A cross-sectional survey of 100 participants across retail, healthcare, IT, and telecommunications sectors was analysed using Spearman rho correlation and ordinal logistic regression (IBM SPSS). Bivariate correlations were weak and non-significant (r<0.19, p>0.06). Regression identified CRM (beta=0.717, p=0.002) and CKM (beta=0.581, p=0.009) as significant positive predictors of CE; MDM showed a positive but non-significant direct effect (beta=0.346, p=0.071). The model explained 20.5% of CE variance (Nagelkerke R^2=0.205). Parallel mediation analysis (Hayes PROCESS Model 4, 5,000 bootstrap samples) found no significant indirect effects of MDM on CE via CRM (IE=0.021, 95% BC CI [-0.072, 0.121]) or CKM (IE=0.032, 95% BC CI [-0.061, 0.126]); Hypothesis H4 was not supported. CRM and CKM emerge as the principal drivers of CE within the CRI framework, while MDM functions as a foundational data quality enabler whose strategic value is realised through its enabling effect on CRM execution and knowledge management. Findings should be treated as exploratory given the sample size and cross-sectional design. Future research should replicate with larger sector-specific samples and longitudinal designs, particularly in regulated BFSI contexts where MDM architecture is shaped by data governance mandates.