In recent decades, business to business (B2B) buying has become more digital-centric and buyer-driven than before. More than half of the B2B buying process is carried out through online information search. In another word, by the time of establishing contacts between B2B buyers and sellers, the buying process is already in its advanced stages. Hence, identifying the buying stage of potential B2B buyers before their first contact can bring substantial benefits to B2B sellers given the complexity of the transaction and its associated value. In this paper, authors propose to use a statistical model to infer the hidden buying stages of the B2B buyers by only observing their online browsing behaviour on the seller’s webpages. The proposed method utilizes the Hidden semi Markov Model (HSMM) and its performance is compared with the Hidden Markov Model (HMM). Results show the effectiveness of HSMM in comparison to HMM in estimating the buying stages. In addition to that, this paper is the first attempt to simulate the B2B buying process via statistical models trying to mimic the B2B buying journey.
|Tila||Julkaistu - elokuuta 2019|
|Tapahtuma||American Marketing Association Summer Academic Conference - Chicago, Yhdysvallat|
Kesto: 9 elokuuta 2019 → 11 elokuuta 2019
|Conference||American Marketing Association Summer Academic Conference|
|Ajanjakso||09/08/2019 → 11/08/2019|