Top

Published in:

2024 | OriginalPaper | Chapter

Unveiling Consumer Segmentation: Harnessing K-means Clustering Using Elbow and Silhouette for Precise Targeting

Authors : Shweta Saraswat, Vaibhav Agrohi, Mahesh Kumar, Monica Lamba, Raminder Kaur

Published in: Proceedings of Third International Conference on Computing and Communication Networks

Publisher: Springer Nature Singapore

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Consumer segmentation is essential for accurate targeting and successful marketing efforts in today’s competitive business environment. Modern marketing groups individuals by interests and attributes. Segmentation drives targeting, personalization, and ROI. This article segments customers using K-means clustering. The Elbow approach and Silhouette score determine the appropriate number of clusters and increase segmentation accuracy. They also examine the possibility of precision targeting and customized marketing techniques across sectors. Businesses may optimize marketing, improve customer happiness, and increase profits by using K-means clustering. To compete in today’s market, this research helps marketers enhance targeting. Elbow and Silhouette K-means clustering may enhance client segmentation, engagement, loyalty, and economic success.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

previous chapter Convolution Neural Network Versus Transfer Learning in Image Classification

next chapter Multimodal Sentiment Analysis and Multimodal Emotion Analysis: A Review

Tabianan, K., Velu, S., Ravi, V.: K-means clustering approach for intelligent customer segmentation using customer purchase behavior data. Sustainability 14(12), 7243 (2022)CrossRef

Zhou, J., Jinliang, W., Xu, B.: Customer segmentation by web content mining. J. Retail. Consum. Serv. 61, 102588 (2021). https://doi.org/10.1016/j.jretconser.2021.102588

Mahfuza, R., Islam, N., Toyeb, M., Emon, M.A.F., Chowdhury, S.A., Alam, M.G.R.: LRFMV: an efficient customer segmentation model for superstores. PLoS One 17(12), e0279262 (2022). https://doi.org/10.1371/journal.pone.0279262.PMID:36538513;PMCID:PMC9767363CrossRef

Loftus, T.J., Shickel, B., Balch, J.A., Tighe, P.J., Abbott, K.L., Fazzone, B., Anderson, E.M., Rozowsky, J., Ozrazgat-Baslanti, T., Ren, Y., Berceli, S.A., Hogan, W.R., Efron, P.A., Moorman, J.R., Rashidi, P., Upchurch, G.R. Jr., Bihorac, A.: Phenotype clustering in health care: a narrative review for clinicians. Front. Artif. Intell. 5, 842306 (2022). https://doi.org/10.3389/frai.2022.842306. PMID: 36034597; PMCID: PMC9411746

Ikotun, A. E., Abualigah, A., Abuhaija, L., Belal Heming, J.: K-means clustering algorithms: a comprehensive review, variants analysis, and advances in the era of big data. Inform. Sci. 622 (2022). https://doi.org/10.1016/j.ins.2022.11.139

Belyadi, H., Haghighat, A.: Machine Learning Guide for Oil and Gas Using Python (2021)

Smith, A., Johnson, B.: Advancements in consumer segmentation using machine learning: a comparative study. J. Mark. Anal. 8(3), 189–205 (2022)

Saraswat, S., Sharma, S., Kulshrestha, R., Verma, N., Lamba, M.: Perceptions unveiled: analyzing public sentiment on IoT and AI integration in revolutionizing social interactions. In: 7th I-SMAC, pp. 65–70 (2023). https://doi.org/10.1109/I-SMAC58438.2023.10290487

Patel, R., Gupta, S., Sharma, M.: A novel approach to customer segmentation using hierarchical clustering and density-based spatial clustering. J. Bus. Anal. 15(1), 45–62 (2023)

10.

Kim, J., Park, S., Lee, H.: Enhancing K-means clustering with genetic algorithms for improved consumer segmentation. J. Interact. Mark. 37, 78–92 (2023)

11.

Brown, L., Adams, C., Carter, E.: Leveraging sentiment analysis for customer segmentation: a case study in the retail industry. J. Mark. Sci. 30(4), 576–589 (2023)

12.

Yang, Y., Li, Q., Zhang, Y.: Unsupervised machine learning for dynamic consumer segmentation in e-commerce. Decis. Support Syst. 120, 123–135 (2023)

13.

Wang, X., Zhang, Z., Li, S.: An integrated approach to customer segmentation using K-means and self-organizing maps. Int. J. Inf. Manag. 54, 102247 (2023)

14.

Saraswat, S., Keswani, B., Kulshrestha, R., Sharma, S., Verma, N., Alam, S.: Accuracy assessment of several machine learning algorithms for breast cancer diagnosis. Math. Stat. Eng. Appl. 71(4), 12578–12587 (2022)

15.

Gupta, R., Kumar, S., Sharma, A.: Customer segmentation for personalized marketing using deep autoencoders. Expert Syst. Appl. 124, 230–242 (2023)

16.

Verma, B., Saraswat, S., Saraswat, V., Misra, R.: Interstitial lung disease patterns classification using hybrid features set and multi level segmentation implemented by machine learning algorithm. In: 8th ICCES, pp. 1811–1815 (2023). https://doi.org/10.1109/ICCES57224.2023.10192662

17.

Saraswat, S., Keswani, B., Sharma, V., Saraswat, V.: Mammograms-based breast cancer detection using AI image processing techniques. J. Coast. Life Med. (2023)

18.

Saraswat, S., Lamba, M., Gupta, M., Sharma, A.: Automatic attendance system using facial recognition using the ADA boost algorithm (2023). SSRN: https://doi.org/10.2139/ssrn.4638529

19.

Nainwal, A., Pant, B., Sharma, G.: A comprehending deep learning approach for disease classification. In: IoT Based Control Networks and Intelligent Systems: Proceedings of 3rd ICICNIS 2022, pp. 113–122. Springer Nature Singapore, Singapore (2022)

Title: Unveiling Consumer Segmentation: Harnessing K-means Clustering Using Elbow and Silhouette for Precise Targeting
Authors: Shweta Saraswat
Vaibhav Agrohi
Mahesh Kumar
Monica Lamba
Raminder Kaur
Publisher: Springer Nature Singapore
Book: Proceedings of Third International Conference on Computing and Communication Networks
Print ISBN: 978-981-9708-91-8

Electronic ISBN: 978-981-9708-92-5

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-981-97-0892-5_28

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"