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Measuring the value of artificial intelligence in improving search and chatbot outcomes

Author

Listed:
  • Larche, Jeff

    (Director, Analytics and Personalization, TA Digital, USA)

  • Lazarevski, Josip

    (Senior Product and Data Science Architect, TA Digital, USA)

Abstract

This paper recommends that the best way to measure the success of artificial intelligence used in internal search or chatbots is not to use the data driving these improvements, but rather to tune a standard user behaviour measurement system to the metrics that matter and use carefully constructed experiments to assess the return on investment. The paper also maintains that digital marketers can learn a great deal about their customers and products from these enhancements, including what products need the most online marketing help. Through this process, the marketer can learn as much about the system as the system is learning from its users.

Suggested Citation

  • Larche, Jeff & Lazarevski, Josip, 2021. "Measuring the value of artificial intelligence in improving search and chatbot outcomes," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 7(2), pages 154-160, September.
    • Handle: RePEc:aza:ama000:y:2021:v:7:i:2:p:154-160
    as

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    More about this item

    Keywords

    artificial intelligence; machine learning; return on investment; technological domestication; Adobe Analytics; Google Analytics; data visualisation; brownie charts;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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