Blockchain and Machine Learning For Predictive Analytics in Customer Relationship Management

CRM strengthens customer relationships in today's fast-paced corporate land-scape. This paper examines a novel strategy that integrates RNN, Deep Learning, and NLP with Blockchain-Enhanced Customer Relationship Management. This relationship might help firms foresee consumer needs, engage with them, and protect their data, improving CRM. Blockchain CRM (BCRM) secures and simplifies data. Trust and transparency are encouraged while customer data is protected. Deep learning algorithms make it simpler to segment clients and customize offerings. Time-series analysis using machine learning algorithms like RNN predicts client behavior accurately. NLP helps firms understand client feedback by analyzing reviews and comments. Our testing revealed RNN, NLP, and Deep Learning performed better. NLP was flawless, RNN right, and Deep Learning superior. These findings illustrate that the offered solutions may accommodate many corporate objectives and duties. Our graphics helped firms identify the optimal algorithm for CRM enhancement initiatives by comparing them. In predictive analytics accuracy, data security, speed, customization, and rule compliance, the BCRM approach using blockchain and machine learning outperforms CRM alternatives. It provides firms a competitive advantage in maintaining and strengthening customer connections, creating trust, and driving growth and success in a data-driven world.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1109/ictbig64922.2024.10911087
Citations
2
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
1.56
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article

Blockchain and Machine Learning For Predictive Analytics in Customer Relationship Management

Santhosh Kumar. C, Monali Ravindra Borade, N. Kalidas, Jatin Khurana et al.
2 citations
Blockchain Technology Applications and Security
1.56
article

Blockchain and Machine Learning For Predictive Analytics in Customer Relationship Management

Santhosh Kumar. C, Monali Ravindra Borade, N. Kalidas, Jatin Khurana, Ashmeet Kaur, Anila Bajpai
article en
2 citations

Abstract

CRM strengthens customer relationships in today's fast-paced corporate land-scape. This paper examines a novel strategy that integrates RNN, Deep Learning, and NLP with Blockchain-Enhanced Customer Relationship Management. This relationship might help firms foresee consumer needs, engage with them, and protect their data, improving CRM. Blockchain CRM (BCRM) secures and simplifies data. Trust and transparency are encouraged while customer data is protected. Deep learning algorithms make it simpler to segment clients and customize offerings. Time-series analysis using machine learning algorithms like RNN predicts client behavior accurately. NLP helps firms understand client feedback by analyzing reviews and comments. Our testing revealed RNN, NLP, and Deep Learning performed better. NLP was flawless, RNN right, and Deep Learning superior. These findings illustrate that the offered solutions may accommodate many corporate objectives and duties. Our graphics helped firms identify the optimal algorithm for CRM enhancement initiatives by comparing them. In predictive analytics accuracy, data security, speed, customization, and rule compliance, the BCRM approach using blockchain and machine learning outperforms CRM alternatives. It provides firms a competitive advantage in maintaining and strengthening customer connections, creating trust, and driving growth and success in a data-driven world.

Jain University (IN), Shri Venkateshwara University (IN), Karpagam Academy of Higher Education (IN), Chitkara University (IN)
Decent work and economic growth
Openalex Percentile: Top 11%
Blockchain Technology Applications and Security
1.56
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Blockchain and Machine Learning For Predictive Analytics in Customer Relationship Management — Santhosh Kumar. C, Monali Ravindra Borade, et al. · (2024) | TGRS Research Map | TGRS