IDEAS home Printed from https://ideas.repec.org/a/eee/bushor/v63y2020i2p227-243.html
   My bibliography  Save this article

From data to action: How marketers can leverage AI

Author

Listed:
  • Campbell, Colin
  • Sands, Sean
  • Ferraro, Carla
  • Tsao, Hsiu-Yuan (Jody)
  • Mavrommatis, Alexis

Abstract

Artificial intelligence (AI) is at the forefront of a revolution in business and society. AI affords companies a host of ways to better understand, predict, and engage customers. Within marketing, AI’s adoption is increasing year-on-year and in varied contexts, from providing service assistance during customer interactions to assisting in the identification of optimal promotions. But just as questions about AI remain with regard to job automation, ethics, and corporate responsibility, the marketing domain faces its own concerns about AI. With this article, we seek to consolidate the growing body of knowledge about AI in marketing. We explain how AI can enhance the marketing function across nine stages of the marketing planning process. We also provide examples of current applications of AI in marketing.

Suggested Citation

  • Campbell, Colin & Sands, Sean & Ferraro, Carla & Tsao, Hsiu-Yuan (Jody) & Mavrommatis, Alexis, 2020. "From data to action: How marketers can leverage AI," Business Horizons, Elsevier, vol. 63(2), pages 227-243.
  • Handle: RePEc:eee:bushor:v:63:y:2020:i:2:p:227-243
    DOI: 10.1016/j.bushor.2019.12.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0007681319301624
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.bushor.2019.12.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Paschen, Ulrich & Pitt, Christine & Kietzmann, Jan, 2020. "Artificial intelligence: Building blocks and an innovation typology," Business Horizons, Elsevier, vol. 63(2), pages 147-155.
    2. Merendino, Alessandro & Dibb, Sally & Meadows, Maureen & Quinn, Lee & Wilson, David & Simkin, Lyndon & Canhoto, Ana, 2018. "Big data, big decisions: The impact of big data on board level decision-making," Journal of Business Research, Elsevier, vol. 93(C), pages 67-78.
    3. Chaim Zins, 2007. "Conceptual approaches for defining data, information, and knowledge," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(4), pages 479-493, February.
    4. Paschen, Jeannette & Wilson, Matthew & Ferreira, João J., 2020. "Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel," Business Horizons, Elsevier, vol. 63(3), pages 403-414.
    5. Roland T. Rust & Ming-Hui Huang, 2014. "The Service Revolution and the Transformation of Marketing Science," Marketing Science, INFORMS, vol. 33(2), pages 206-221, March.
    6. Geng Cui & Man Leung Wong & Hon-Kwong Lui, 2006. "Machine Learning for Direct Marketing Response Models: Bayesian Networks with Evolutionary Programming," Management Science, INFORMS, vol. 52(4), pages 597-612, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pelau Corina & Barbul Maria, 2021. "Consumers’ perception on the use of cognitive computing," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 15(1), pages 639-649, December.
    2. Hossain, Md Afnan & Akter, Shahriar & Yanamandram, Venkata, 2021. "Why doesn't our value creation payoff: Unpacking customer analytics-driven value creation capability to sustain competitive advantage," Journal of Business Research, Elsevier, vol. 131(C), pages 287-296.
    3. Canhoto, Ana Isabel & Clear, Fintan, 2020. "Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential," Business Horizons, Elsevier, vol. 63(2), pages 183-193.
    4. Pham, Phuoc & Zhang, Huilan & Gao, Wenlian & Zhu, Xiaowei, 2024. "Determinants and performance outcomes of artificial intelligence adoption: Evidence from U.S. Hospitals," Journal of Business Research, Elsevier, vol. 172(C).
    5. Jarrahi, Mohammad Hossein & Askay, David & Eshraghi, Ali & Smith, Preston, 2023. "Artificial intelligence and knowledge management: A partnership between human and AI," Business Horizons, Elsevier, vol. 66(1), pages 87-99.
    6. William Rand & Roland T. Rust & Min Kim, 2018. "Complex systems: marketing’s new frontier," AMS Review, Springer;Academy of Marketing Science, vol. 8(3), pages 111-127, December.
    7. Black, J. Stewart & van Esch, Patrick, 2020. "AI-enabled recruiting: What is it and how should a manager use it?," Business Horizons, Elsevier, vol. 63(2), pages 215-226.
    8. Black, J. Stewart & van Esch, Patrick, 2021. "AI-enabled recruiting in the war for talent," Business Horizons, Elsevier, vol. 64(4), pages 513-524.
    9. Szabolcs Nagy & Noemi Hajdu, 2021. "Consumer Acceptance of the Use of Artificial Intelligence in Online Shopping: Evidence From Hungary," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(56), pages 155-155, February.
    10. Canhoto, Ana Isabel, 2021. "Leveraging machine learning in the global fight against money laundering and terrorism financing: An affordances perspective," Journal of Business Research, Elsevier, vol. 131(C), pages 441-452.
    11. Sjödin, David & Parida, Vinit & Palmié, Maximilian & Wincent, Joakim, 2021. "How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops," Journal of Business Research, Elsevier, vol. 134(C), pages 574-587.
    12. Mariani, Marcello M. & Fosso Wamba, Samuel, 2020. "Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies," Journal of Business Research, Elsevier, vol. 121(C), pages 338-352.
    13. Rosa Lombardi & Raffaele Trequattrini & Federico Schimperna & Myriam Cano-Rubio, 2021. "The Impact of Smart Technologies on theManagement and Strategic Control: A Structured Literature Review," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(suppl. 1), pages 11-30.
    14. Charles Ayoubi & Boris Thurm, 2023. "Knowledge diffusion and morality: Why do we freely share valuable information with Strangers?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 32(1), pages 75-99, January.
    15. Joerß, Tom & Hoffmann, Stefan & Mai, Robert & Akbar, Payam, 2021. "Digitalization as solution to environmental problems? When users rely on augmented reality-recommendation agents," Journal of Business Research, Elsevier, vol. 128(C), pages 510-523.
    16. Fredström, Ashkan & Parida, Vinit & Wincent, Joakim & Sjödin, David & Oghazi, Pejvak, 2022. "What is the Market Value of Artificial Intelligence and Machine Learning? The Role of Innovativeness and Collaboration for Performance," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    17. Luoma, Jukka, 2016. "Model-based organizational decision making: A behavioral lens," European Journal of Operational Research, Elsevier, vol. 249(3), pages 816-826.
    18. Ayat Sami ODEIBAT, 2021. "The Effect Of Technology Evolution On The Future Of Jobs," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 17, pages 57-67, June.
    19. Neubert, Mitchell J. & Montañez, George D., 2020. "Virtue as a framework for the design and use of artificial intelligence," Business Horizons, Elsevier, vol. 63(2), pages 195-204.
    20. Cho, Jihoon & Janda, Swinder, 2023. "Reciprocity in upward product line extensions: A longitudinal study," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:bushor:v:63:y:2020:i:2:p:227-243. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/bushor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.