Data Analytics Implemented over E-commerce Data to Evaluate Performance of Supervised Learning Approaches in Relation to Customer Behavior

Hambarde K., SİLAHTAROĞLU G., Khamitkar S., Bhalchandra P., Shaikh H., Kulkarni G., ...Daha Fazla

8th International Conference on Soft Computing for Problem Solving, SocProS 2018, Vellore, Hindistan, 17 - 19 Aralık 2018, cilt.1048, ss.285-293 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 1048
  • Doi Numarası: 10.1007/978-981-15-0035-0_22
  • Basıldığı Şehir: Vellore
  • Basıldığı Ülke: Hindistan
  • Sayfa Sayıları: ss.285-293
  • Anahtar Kelimeler: Customer behavior analytics, Classification, Random forest
  • İstanbul Medipol Üniversitesi Adresli: Evet

Özet

Online purchase portals have a spectacular opportunity for business expansion. E-commerce portals have data repositories pertaining to online transactions that could be analyzed through data analytics to find valuable insight for further expansion of business as well as targeted marketing. This study has made an attempt for the implementation of data analytics over the shared data set of Turkey-based e-commerce company. Precisely, a comparative analysis of supervised machine learning algorithms has been worked out for predicting customer behavior and products being brought. Their efficiency has been found out and they have been ranked purpose wise. The implementations of algorithms are carried out in Python.