Come with me now: New potential consumers identification from competitors

Hugo Alatrista-Salas; Miguel Nunez-del-Prado; Victoria Zevallos

doi:10.1007/978-3-030-46140-9_24

Come with me now: New potential consumers identification from competitors

Hugo Alatrista-Salas, Miguel Nunez-del-Prado, Victoria Zevallos

Universidad del Pacífico

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The telecommunications industry is confronted more and more to aggressive marketing campaigns from competitor carriers. Therefore, they need to improve the subscriber targeting to propose more attractive offers for gaining new subscribers. In the present effort, a five steps methodology to find new potential subscribers using supervised learning techniques over imbalanced datasets is proposed. The proposed technique applies community detection to infers consumption information of competitors carriers subscribers within the communities. Besides, it uses a sampling technique to reduce the effect of a dominant class for an imbalanced classification task. The proposal is evaluated with a real dataset from a Peruvian carrier. The dataset contains one-month data, which is about 200 millions of transaction. The results show that the proposed technique is able to identify between two to ten times more new potential clients, depending on the sampling technique, as shows using the top decile lift value.

Original language	English
Title of host publication	Information management and dig data
Subtitle of host publication	6th International Conference, SIMBig 2019, Proceedings
Editors	Juan Antonio Lossio-Ventura, Nelly Condori-Fernandez, Jorge Carlos Valverde-Rebaza
Place of Publication	Cham
Pages	252-266
Number of pages	15
ISBN (Electronic)	978-3-030-46140-9
DOIs	https://doi.org/10.1007/978-3-030-46140-9_24
State	Published - 23 Apr 2020
Event	International Conference on Information Management and Big Data - Lima, Peru Duration: 21 Aug 2019 → 23 Aug 2019 Conference number: 6th https://simbig.org/SIMBig2019/

Publication series

Name	Communications in Computer and Information Science
Volume	1070 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	International Conference on Information Management and Big Data
Abbreviated title	SIMBig 2019
Country/Territory	Peru
City	Lima
Period	21/08/19 → 23/08/19
Internet address	https://simbig.org/SIMBig2019/

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

Keywords

Community detection
Imbalanced classification
Subscribers attraction

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-46140-9_24

Cite this

Alatrista-Salas, H., Nunez-del-Prado, M., & Zevallos, V. (2020). Come with me now: New potential consumers identification from competitors. In J. A. Lossio-Ventura, N. Condori-Fernandez, & J. C. Valverde-Rebaza (Eds.), Information management and dig data: 6th International Conference, SIMBig 2019, Proceedings (pp. 252-266). (Communications in Computer and Information Science; Vol. 1070 CCIS).. https://doi.org/10.1007/978-3-030-46140-9_24

Alatrista-Salas, Hugo ; Nunez-del-Prado, Miguel ; Zevallos, Victoria. / Come with me now : New potential consumers identification from competitors. Information management and dig data: 6th International Conference, SIMBig 2019, Proceedings. editor / Juan Antonio Lossio-Ventura ; Nelly Condori-Fernandez ; Jorge Carlos Valverde-Rebaza. Cham, 2020. pp. 252-266 (Communications in Computer and Information Science).

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abstract = "The telecommunications industry is confronted more and more to aggressive marketing campaigns from competitor carriers. Therefore, they need to improve the subscriber targeting to propose more attractive offers for gaining new subscribers. In the present effort, a five steps methodology to find new potential subscribers using supervised learning techniques over imbalanced datasets is proposed. The proposed technique applies community detection to infers consumption information of competitors carriers subscribers within the communities. Besides, it uses a sampling technique to reduce the effect of a dominant class for an imbalanced classification task. The proposal is evaluated with a real dataset from a Peruvian carrier. The dataset contains one-month data, which is about 200 millions of transaction. The results show that the proposed technique is able to identify between two to ten times more new potential clients, depending on the sampling technique, as shows using the top decile lift value.",

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Alatrista-Salas, H, Nunez-del-Prado, M & Zevallos, V 2020, Come with me now: New potential consumers identification from competitors. in JA Lossio-Ventura, N Condori-Fernandez & JC Valverde-Rebaza (eds), Information management and dig data: 6th International Conference, SIMBig 2019, Proceedings. Communications in Computer and Information Science, vol. 1070 CCIS, Cham, pp. 252-266, International Conference on Information Management and Big Data, Lima, Peru, 21/08/19. https://doi.org/10.1007/978-3-030-46140-9_24

Come with me now: New potential consumers identification from competitors. / Alatrista-Salas, Hugo; Nunez-del-Prado, Miguel; Zevallos, Victoria.
Information management and dig data: 6th International Conference, SIMBig 2019, Proceedings. ed. / Juan Antonio Lossio-Ventura; Nelly Condori-Fernandez; Jorge Carlos Valverde-Rebaza. Cham, 2020. p. 252-266 (Communications in Computer and Information Science; Vol. 1070 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - The telecommunications industry is confronted more and more to aggressive marketing campaigns from competitor carriers. Therefore, they need to improve the subscriber targeting to propose more attractive offers for gaining new subscribers. In the present effort, a five steps methodology to find new potential subscribers using supervised learning techniques over imbalanced datasets is proposed. The proposed technique applies community detection to infers consumption information of competitors carriers subscribers within the communities. Besides, it uses a sampling technique to reduce the effect of a dominant class for an imbalanced classification task. The proposal is evaluated with a real dataset from a Peruvian carrier. The dataset contains one-month data, which is about 200 millions of transaction. The results show that the proposed technique is able to identify between two to ten times more new potential clients, depending on the sampling technique, as shows using the top decile lift value.

AB - The telecommunications industry is confronted more and more to aggressive marketing campaigns from competitor carriers. Therefore, they need to improve the subscriber targeting to propose more attractive offers for gaining new subscribers. In the present effort, a five steps methodology to find new potential subscribers using supervised learning techniques over imbalanced datasets is proposed. The proposed technique applies community detection to infers consumption information of competitors carriers subscribers within the communities. Besides, it uses a sampling technique to reduce the effect of a dominant class for an imbalanced classification task. The proposal is evaluated with a real dataset from a Peruvian carrier. The dataset contains one-month data, which is about 200 millions of transaction. The results show that the proposed technique is able to identify between two to ten times more new potential clients, depending on the sampling technique, as shows using the top decile lift value.

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KW - Subscribers attraction

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KW - Imbalanced classification

KW - Subscribers attraction

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ER -

Alatrista-Salas H, Nunez-del-Prado M, Zevallos V. Come with me now: New potential consumers identification from competitors. In Lossio-Ventura JA, Condori-Fernandez N, Valverde-Rebaza JC, editors, Information management and dig data: 6th International Conference, SIMBig 2019, Proceedings. Cham. 2020. p. 252-266. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-46140-9_24

Come with me now: New potential consumers identification from competitors

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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Cite this