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Improving measurement with Big Data: Variety-seeking and survival

Author

Listed:
  • Nastasoiu, Mihaela Alina
  • Bendle, Neil
  • Vandenbosch, Mark

Abstract

Big Data can be used to make sense of highly unstructured consumer data, and improve both the reliability and validity of measures that have historically required manual coding. Furthermore, using available secondary data allows for much faster coding. This research proposes a new and more robust way to measure the degree of variety-seeking exhibited by consumers. It employs the Million Song Dataset, a database of consumergenerated tags describing musical styles, to create measures of musical variety with minimal manual coding. Using a sample of 10,511 SiriusXM subscribers, the research compares this novel method of measuring variety-seeking behaviours with a more simple model, and finds that the novel method is a more accurate predictor of churn.

Suggested Citation

  • Nastasoiu, Mihaela Alina & Bendle, Neil & Vandenbosch, Mark, 2019. "Improving measurement with Big Data: Variety-seeking and survival," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 4(3), pages 253-263, February.
    • Handle: RePEc:aza:ama000:y:2019:v:4:i:3:p:253-263
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    More about this item

    Keywords

    Big Data; variety-seeking; construct validity; survival; data fusion;
    All these keywords.

    JEL classification:

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

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