TY - GEN
T1 - Come with Me Now
T2 - 6th International Conference on Information Management and Big Data, SIMBig 2019
AU - Alatrista-Salas, Hugo
AU - Nunez-del-Prado, Miguel
AU - Zevallos, Victoria
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
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.
KW - Community detection
KW - Imbalanced classification
KW - Subscribers attraction
UR - https://www.scopus.com/pages/publications/85084826947
U2 - 10.1007/978-3-030-46140-9_24
DO - 10.1007/978-3-030-46140-9_24
M3 - Conference contribution
AN - SCOPUS:85084826947
SN - 9783030461393
T3 - Communications in Computer and Information Science
SP - 252
EP - 266
BT - Information Management and Big Data - 6th International Conference, SIMBig 2019, Proceedings
A2 - Lossio-Ventura, Juan Antonio
A2 - Condori-Fernandez, Nelly
A2 - Valverde-Rebaza, Jorge Carlos
PB - Springer
Y2 - 21 August 2019 through 23 August 2019
ER -