Is this company a lead customer? Estimating stages of B2B buying journey

Neda B. Marvasti; Juho-Petteri Huhtala; Zeinab R. Yousefi; Iiro Vaniala; Bikesh Upreti; Pekka Malo; Samuel Kaski; Henrikki Tikkanen

doi:10.1016/j.indmarman.2021.06.003

Is this company a lead customer? Estimating stages of B2B buying journey

Neda B. Marvasti^*, Juho-Petteri Huhtala, Zeinab R. Yousefi, Iiro Vaniala, Bikesh Upreti, Pekka Malo, Samuel Kaski, Henrikki Tikkanen

^*Corresponding author for this work

University of Queensland

Research output: Contribution to journal › Article › Scientific › peer-review

16 Citations (Scopus)

396 Downloads (Pure)

Abstract

By advancement in digital marketing, business-to-business (B2B) buyers carry out over half of the buying process through digital touchpoints before they establish any significant contact with the B2B seller. Knowing the buying stage of a potential buyer can bring a substantial advantage to the B2B seller given the complexity of the transaction and the associated value. In this paper, the authors propose a machine learning approach to infer the stages of the B2B buying journey by observing the online browsing behavior of buyer companies. It is shown that observing the buyer's online behavior effectively allows us to estimate the buying stages with high accuracy by utilizing the hidden Markov models. Managers in B2B seller companies may use these techniques for adjusting their marketing efforts to improve the fit with the information demands of the B2B buyer prospects along with their buying journey, and thus, improve the hit rate of marketing and sales activities.

Original language	English
Pages (from-to)	126-133
Number of pages	8
Journal	Industrial Marketing Management
Volume	97
Early online date	13 Jul 2021
DOIs	https://doi.org/10.1016/j.indmarman.2021.06.003
Publication status	Published - Aug 2021
MoE publication type	A1 Journal article-refereed

Keywords

B2B buyer journey
Hidden buying stage
Hidden Markov model
Internet browsing

Access to Document

10.1016/j.indmarman.2021.06.003Licence: CC BY

Is this company a lead customer.1-s2.0-S001985012100105X-mainFinal published version, 804 KBLicence: CC BY

Cite this

@article{9dee10933aca4e4eb52dda925cfc4e4f,

title = "Is this company a lead customer? Estimating stages of B2B buying journey",

abstract = "By advancement in digital marketing, business-to-business (B2B) buyers carry out over half of the buying process through digital touchpoints before they establish any significant contact with the B2B seller. Knowing the buying stage of a potential buyer can bring a substantial advantage to the B2B seller given the complexity of the transaction and the associated value. In this paper, the authors propose a machine learning approach to infer the stages of the B2B buying journey by observing the online browsing behavior of buyer companies. It is shown that observing the buyer's online behavior effectively allows us to estimate the buying stages with high accuracy by utilizing the hidden Markov models. Managers in B2B seller companies may use these techniques for adjusting their marketing efforts to improve the fit with the information demands of the B2B buyer prospects along with their buying journey, and thus, improve the hit rate of marketing and sales activities.",

keywords = "B2B buyer journey, Hidden buying stage, Hidden Markov model, Internet browsing",

author = "Marvasti, {Neda B.} and Juho-Petteri Huhtala and Yousefi, {Zeinab R.} and Iiro Vaniala and Bikesh Upreti and Pekka Malo and Samuel Kaski and Henrikki Tikkanen",

note = "Funding Information: The authors would like to thank Business Finland (the public organization for innovation funding and trade, travel and investment pro-motion in Finland) for funding this research project (B2BAI). The authors would also like to thank Aalto Science-IT project for providing the computational resources needed to perform the simulations and real-world dataset experiments. Funding Information: This work was funded by Business Finland project number 3380/31/2017 . Publisher Copyright: {\textcopyright} 2021 The Authors",

year = "2021",

month = aug,

doi = "10.1016/j.indmarman.2021.06.003",

language = "English",

volume = "97",

pages = "126--133",

journal = "Industrial Marketing Management",

issn = "0019-8501",

publisher = "Elsevier",

}

TY - JOUR

T1 - Is this company a lead customer? Estimating stages of B2B buying journey

AU - Marvasti, Neda B.

AU - Huhtala, Juho-Petteri

AU - Yousefi, Zeinab R.

AU - Vaniala, Iiro

AU - Upreti, Bikesh

AU - Malo, Pekka

AU - Kaski, Samuel

AU - Tikkanen, Henrikki

N1 - Funding Information: The authors would like to thank Business Finland (the public organization for innovation funding and trade, travel and investment pro-motion in Finland) for funding this research project (B2BAI). The authors would also like to thank Aalto Science-IT project for providing the computational resources needed to perform the simulations and real-world dataset experiments. Funding Information: This work was funded by Business Finland project number 3380/31/2017 . Publisher Copyright: © 2021 The Authors

PY - 2021/8

Y1 - 2021/8

N2 - By advancement in digital marketing, business-to-business (B2B) buyers carry out over half of the buying process through digital touchpoints before they establish any significant contact with the B2B seller. Knowing the buying stage of a potential buyer can bring a substantial advantage to the B2B seller given the complexity of the transaction and the associated value. In this paper, the authors propose a machine learning approach to infer the stages of the B2B buying journey by observing the online browsing behavior of buyer companies. It is shown that observing the buyer's online behavior effectively allows us to estimate the buying stages with high accuracy by utilizing the hidden Markov models. Managers in B2B seller companies may use these techniques for adjusting their marketing efforts to improve the fit with the information demands of the B2B buyer prospects along with their buying journey, and thus, improve the hit rate of marketing and sales activities.

AB - By advancement in digital marketing, business-to-business (B2B) buyers carry out over half of the buying process through digital touchpoints before they establish any significant contact with the B2B seller. Knowing the buying stage of a potential buyer can bring a substantial advantage to the B2B seller given the complexity of the transaction and the associated value. In this paper, the authors propose a machine learning approach to infer the stages of the B2B buying journey by observing the online browsing behavior of buyer companies. It is shown that observing the buyer's online behavior effectively allows us to estimate the buying stages with high accuracy by utilizing the hidden Markov models. Managers in B2B seller companies may use these techniques for adjusting their marketing efforts to improve the fit with the information demands of the B2B buyer prospects along with their buying journey, and thus, improve the hit rate of marketing and sales activities.

KW - B2B buyer journey

KW - Hidden buying stage

KW - Hidden Markov model

KW - Internet browsing

UR - http://www.scopus.com/inward/record.url?scp=85109835876&partnerID=8YFLogxK

U2 - 10.1016/j.indmarman.2021.06.003

DO - 10.1016/j.indmarman.2021.06.003

M3 - Article

AN - SCOPUS:85109835876

SN - 0019-8501

VL - 97

SP - 126

EP - 133

JO - Industrial Marketing Management

JF - Industrial Marketing Management

ER -

Is this company a lead customer? Estimating stages of B2B buying journey

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

B2B AI

Science-IT

Cite this

Is this company a lead customer? Estimating stages of B2B buying journey

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Projects

B2B AI

Equipment

Science-IT

Cite this