Improving measurement with Big Data: Variety-seeking and survival

Mihaela Alina Nastasoiu, Neil Bendle and Mark Vandenbosch

Applied Marketing Analytics: The Peer-Reviewed Journal, 2019, vol. 4, issue 3, 253-263

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.

Keywords: Big Data; variety-seeking; construct validity; survival; data fusion (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:aza:ama000:y:2019:v:4:i:3:p:253-263

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