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The marketing analytics orientation (MAO) of firms: identifying factors that create highly analytical marketing practices

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Listed:
  • Anthony F. Branda

    (Pace University Lubin Graduate School of Business)

  • Vishal Lala

    (Pace University Lubin Graduate School of Business)

  • Pradeep Gopalakrishna

    (Pace University Lubin Graduate School of Business)

Abstract

Marketing analytics (MA) is a relatively new but increasingly prominent field in which data tools are applied to quantify and monitor marketing performance and customer information to optimize investments in marketing programs and maximize customer interaction. MA is a sub-discipline of broader analytics and includes the people, processes, and technology to generate insights that improve marketing performance. In this B2B study, the authors established an initial set of factors, with the help of deep subject matter experts in the field, which help determine the degree to which a firm’s marketing function is analytically driven. The research builds on extant theories of market orientation and lays the foundation for the development of a new construct known as marketing analytics orientation through qualitative research methods.

Suggested Citation

  • Anthony F. Branda & Vishal Lala & Pradeep Gopalakrishna, 2018. "The marketing analytics orientation (MAO) of firms: identifying factors that create highly analytical marketing practices," Journal of Marketing Analytics, Palgrave Macmillan, vol. 6(3), pages 84-94, September.
    • Handle: RePEc:pal:jmarka:v:6:y:2018:i:3:d:10.1057_s41270-018-0036-8
    DOI: 10.1057/s41270-018-0036-8
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    References listed on IDEAS

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    3. Linnenluecke, Martina K. & Griffiths, Andrew, 2010. "Corporate sustainability and organizational culture," Journal of World Business, Elsevier, vol. 45(4), pages 357-366, October.
    4. Germann, Frank & Lilien, Gary L. & Rangaswamy, Arvind, 2013. "Performance implications of deploying marketing analytics," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 114-128.
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    Cited by:

    1. Larisa Sharakhina & Irina Ilyina & Dmitrii Kaplun & Tatiana Teor & Valeria Kulibanova, 2024. "AI technologies in the analysis of visual advertising messages: survey and application," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(4), pages 1066-1089, December.
    2. Shimi Naurin Ahmad & Michel Laroche, 2023. "Extracting marketing information from product reviews: a comparative study of latent semantic analysis and probabilistic latent semantic analysis," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(4), pages 662-676, December.
    3. Agag, Gomaa & Shehawy, Yasser Moustafa & Almoraish, Ahmed & Eid, Riyad & Chaib Lababdi, Houyem & Gherissi Labben, Thouraya & Abdo, Said Shabban, 2024. "Understanding the relationship between marketing analytics, customer agility, and customer satisfaction: A longitudinal perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).

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