Call for Papers:Vol.10 Issue.6

Submission
Last date		 30-Dec-2024
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-10,Issue-6. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Integrated Churn Prediction and Segmentation
PaperId: :  20376
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 3 2023
DUI:    16.0415/IJARIIE-20376
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Rohit RanjanBangalore Institute of Technology
Ram Kumar PandeyBangalore Institute of Technology
Rahul Kumar SainiBangalore Institute of Technology
Mrityunjay PrakashBangalore Institute of Technology
Nikitha K. S.Bangalore Institute of Technology

Abstract

AI/ML
SMOTE, EDA, K-Means, K-Fold Cross Validation, Normalization, Bagging Tree, Extra Tree, Random Forest, Segmentation
Customer churn prediction and segmentation are crucial aspects of data-driven marketing. This paper presents a comprehensive approach that encompasses various modules to tackle these challenges effectively. The methodology proposed in this study includes data processing, churn prediction using machine learning algorithms, customer segmentation through K-means clustering, and result analysis. To ensure the quality and consistency of the dataset, the data processing stage performs essential tasks such as data transformation, cleaning, and normalization. Additionally, the Synthetic Minority Over-sampling Technique (SMOTE) is employed to address any issues of data imbalance, enhancing the reliability of the results. The churn prediction module plays a pivotal role in identifying potential churners accurately. By employing bagging tree, extra trees, and random forest algorithms, this module achieves high prediction accuracy. Furthermore, k-fold cross-validation and feature selection techniques are utilized for robust model evaluation and determination of variable importance. The customer segmentation module utilizes Exploratory Data Analysis (EDA) techniques to extract meaningful insights from the data. By employing K-means clustering, customers are grouped based on their similarities and behaviors, enabling businesses to tailor their marketing strategies to different customer segments effectively. Finally, the results obtained from the churn prediction and segmentation models are thoroughly analyzed to assess their effectiveness. This analysis provides valuable insights for businesses seeking to proactively manage customer churn and implement targeted marketing strategies, ultimately leading to improved business performance and enhanced customer satisfaction. This paper offers a comprehensive and practical approach for customer churn prediction and segmentation in data-driven marketing. The proposed methodology and its associated modules provide a structured framework for businesses to effectively manage customer churn and implement targeted marketing strategies, resulting in improved business performance and customer satisfaction.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Rohit Ranjan, Ram Kumar Pandey, Rahul Kumar Saini, Mrityunjay Prakash, and Nikitha K. S.. "Integrated Churn Prediction and Segmentation" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 3 2023 Page 1948-1958
MLA Rohit Ranjan, Ram Kumar Pandey, Rahul Kumar Saini, Mrityunjay Prakash, and Nikitha K. S.. "Integrated Churn Prediction and Segmentation." International Journal Of Advance Research And Innovative Ideas In Education 9.3(2023) : 1948-1958.
APA Rohit Ranjan, Ram Kumar Pandey, Rahul Kumar Saini, Mrityunjay Prakash, & Nikitha K. S.. (2023). Integrated Churn Prediction and Segmentation. International Journal Of Advance Research And Innovative Ideas In Education, 9(3), 1948-1958.
Chicago Rohit Ranjan, Ram Kumar Pandey, Rahul Kumar Saini, Mrityunjay Prakash, and Nikitha K. S.. "Integrated Churn Prediction and Segmentation." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 3 (2023) : 1948-1958.
Oxford Rohit Ranjan, Ram Kumar Pandey, Rahul Kumar Saini, Mrityunjay Prakash, and Nikitha K. S.. 'Integrated Churn Prediction and Segmentation', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 3, 2023, p. 1948-1958. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Integrated_Churn_Prediction_and_Segmentation_ijariie20376.pdf (Accessed : ).
Harvard Rohit Ranjan, Ram Kumar Pandey, Rahul Kumar Saini, Mrityunjay Prakash, and Nikitha K. S.. (2023) 'Integrated Churn Prediction and Segmentation', International Journal Of Advance Research And Innovative Ideas In Education, 9(3), pp. 1948-1958IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Integrated_Churn_Prediction_and_Segmentation_ijariie20376.pdf (Accessed : )
IEEE Rohit Ranjan, Ram Kumar Pandey, Rahul Kumar Saini, Mrityunjay Prakash, and Nikitha K. S., "Integrated Churn Prediction and Segmentation," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 3, pp. 1948-1958, May-Jun 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/Integrated_Churn_Prediction_and_Segmentation_ijariie20376.pdf [Accessed : ].
Turabian Rohit Ranjan, Ram Kumar Pandey, Rahul Kumar Saini, Mrityunjay Prakash, and Nikitha K. S.. "Integrated Churn Prediction and Segmentation." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 3 ().
Vancouver Rohit Ranjan, Ram Kumar Pandey, Rahul Kumar Saini, Mrityunjay Prakash, and Nikitha K. S.. Integrated Churn Prediction and Segmentation. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(3) : 1948-1958. Available from: https://ijariie.com/AdminUploadPdf/Integrated_Churn_Prediction_and_Segmentation_ijariie20376.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Enhancing Diabetic Retinopathy Management Through Personalized Recommendations with Reinforcement LearningComputer EngineeringH.M.A.I.B Herath Download
Development Of Novel Speech To Text Medical App On Patient’s Data using Artificial Intelligence and Edge Computingcomputer engineeringKriti prasad Download
The Role of Artificial Intelligence in HealthcareComputer engineeringMandla Tirumala Sai Download
Speech Sentiment Classification with MLMachine LearningSagar M Prajapathi Download
BIPOLAR AND SLEEP APNEA DETECTIONSComputer ScienceKarthik V Download
Quantum Computing in Cryptography: Revolutionizing Security in the Digital EraComputer EngineeringAnanya T Download
Exploring Audio Features for Enhanced Bird Identification Using Neural NetworksMachine LearningAshwin Bhatt Download
The Impact of Emerging Technologies on Modern E-Commercecomputer scienceAnisha shermi A Download
Transforming Emergency Response and Personalized Health Management with AI and Quantum InnovationsComputer ScienceTapaswini Kar Download
Harnessing Artificial Intelligence for the Future of Personalized HealthcareComputer EngineeringShravani A Download
Optimisation de l’apprentissage des données météorologique déséquilibrées basé sur la modélisation du formule d’Itô et le k-NNIntelligence artificiel, InformatiqueRAMAHEFY Tiana Razefania Download
Comparative Analysis of Machine Learning Techniques for Human Stress Level Prediction: Performance Metrics and InsightsBiomedical EngineeringA. Rasheedha Download
Natural Language Processing Techniques for Ranking Subjective ResponsesComputer ScienceMohammed Ayub G Download
Decision Support System for predicting Diseases using A.I.AI in HealthcareRitika Chatterjee Download
REVIEW ON MACHINE LEARNINGartificial intelligenceBHUMIKA S K Download
12