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Pricing and data science: The tale of two accidentally parallel transitions

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  • Wallusch Jacek

    (Instytut Kliometrii i Badań nad Transformacją, ul. Nałęczowska 85, 60-472 Poznań, Poland)

Abstract

Accidentally parallel at the beginning, the transition to value-based pricing and transition to pricing data science have blended harmoniously, changing the pricing landscape. Using the marketing capability approach, I show that the introduction of pricing data science is costly and requires higher management support. Despite its cost, algorithmic price optimisation allows one to react swiftly to changes in demand. The optimisation process is applied to inherently non-linear, multimodal, and right-skewed pricing data. Presenting the interactions between new computational techniques and value-data pricing, I concentrate on altered perceptions of price elasticity, value-driver estimations, and contract opportunity analysis.

Suggested Citation

  • Wallusch Jacek, 2023. "Pricing and data science: The tale of two accidentally parallel transitions," Economics and Business Review, Sciendo, vol. 9(2), pages 115-132, April.
    • Handle: RePEc:vrs:ecobur:v:9:y:2023:i:2:p:115-132:n:6
    DOI: 10.18559/ebr.2023.2.739
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    pricing; value-based pricing; machine learning; data science;
    All these keywords.

    JEL classification:

    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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