Forecasting Conversion Rate for Real Time CPC Bidding With Target ROAS

Creative Commons License

Bulut S., AVCI E., BULUT A.

IEEE ACCESS, ss.134908-134916, 2023 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1109/access.2023.3338022
  • Dergi Adı: IEEE ACCESS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
  • Sayfa Sayıları: ss.134908-134916
  • Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli: Evet

Özet

For bidding in real time, the rate of customer conversion needs to be predicted in real time. Using the rate prediction and the target return on ad spend, a competitive CPC bid can be computed. In our study, we built two models, i.e., MoM and MCI namely, for forecasting the rate of conversion. The results we obtained by applying our models on the marketing campaigns of two startups were promising. Both MoM and MCI run in constant $O(1)$ time, and require $O(n)$ space for $n$ observations. Furthermore, both models can be updated with fresh data in $O(1)$ time; hence, they are suitable for a data streaming application where new data arrives continuously in an online manner.