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Effectiveness of value calculators in B2B sales work – Challenges at the sales-call level

Author

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  • Pöyry, Essi
  • Parvinen, Petri
  • Martens, Jonas

Abstract

Value-based selling is assumed to increase B2B sales performance, but empirical evidence about specific practices such as the use of value calculators is lacking. This study explores value calculators in B2B sales work by adopting a mixed-methods approach. First, data on value-calculator usage and sales performance from a B2B service firm show that the usage of value calculators relates to lower-value won deals and does not affect sales conversion or sales-process duration. Second, the analysis of interviews from various B2B firms adds depth with regard to the contingencies of effective calculator use. The results reveal that deal anatomy and challenges in daily sales work limit the general domain of applicability of value calculators, whereas challenges related to quantifying implicit value drivers and salesperson and customer skillsmay explain their negative effect on sales performance.

Suggested Citation

  • Pöyry, Essi & Parvinen, Petri & Martens, Jonas, 2021. "Effectiveness of value calculators in B2B sales work – Challenges at the sales-call level," Journal of Business Research, Elsevier, vol. 126(C), pages 350-360.
    • Handle: RePEc:eee:jbrese:v:126:y:2021:i:c:p:350-360
    DOI: 10.1016/j.jbusres.2020.12.047
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    Cited by:

    1. John V. Colias & Stella Park & Elizabeth Horn, 2023. "Optimizing B2B Product Offers with Machine Learning, Mixed Logit, and Nonlinear Programming," Papers 2308.07830, arXiv.org.
    2. John V. Colias & Stella Park & Elizabeth Horn, 2021. "Optimizing B2B product offers with machine learning, mixed logit, and nonlinear programming," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(3), pages 157-172, September.

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