SciELO - Scientific Electronic Library Online

 
vol.14 número2Strategy for Data: Open it or Hack it?Role of Privacy Legislations and Online Business Brand Image in Consumer Perceptions of Online Privacy Risk índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Em processo de indexaçãoCitado por Google
  • Não possue artigos similaresSimilares em SciELO
  • Em processo de indexaçãoSimilares em Google

Compartilhar


Journal of theoretical and applied electronic commerce research

versão On-line ISSN 0718-1876

Resumo

KAKALEJčIK, Lukáš; BUCKO, Jozef  e  VEJAčKA, Martin. Differences in Buyer Journey between High- and Low-Value Customers of E-Commerce Business. J. theor. appl. electron. commer. res. [online]. 2019, vol.14, n.2, pp.47-58. ISSN 0718-1876.  http://dx.doi.org/10.4067/S0718-18762019000200105.

The knowledge of high-value customers provides the possibility to make decisions ensuring profitability of the company. By analyzing and optimizing a buyer’s journey, companies can better understand their customers and optimize marketing costs in the way that will generate a higher return on investment. The primary objective of this paper is to define the current state of multichannel attribution and, based on the literature, study and analyze the data regarding the buyer’s journey of high- and low-value customers of selected e-commerce business. To accomplish the main objective of our study, we retrieved and analyzed top conversion paths from Google Merchandise Store, the e-commerce website selling goods branded by Google, with the use of Markov chains and heuristic models. A difference between high- and low-value customers regarding the acquisition by marketing channels before the purchase was found. Moreover, it was found that high-value customers' journeys consist of more interactions compared to those of low-value customers.

Palavras-chave : Attribution modeling; Multichannel attribution; Digital analysis; Web analytics; Markov chains.

        · texto em Inglês     · Inglês ( pdf )