Long term behavior of incomplete and time varying product ratings

Piotr Kokoszka, Deepak Singh and Haonan Wang

Statistics & Probability Letters, 2022, vol. 184, issue C

Abstract: Customer feedback is widely used to choose a product among various competing products. Such feedback is most commonly available to consumers via average 0–5 star ratings. These ratings are based only on opinions of purchasers who decided to rate a product and reflect a long term average of those available responses. We develop the SLLN and the CLT applicable to this realistic situation. In particular, we establish a relationship between the true and the reported long term ratings and study the impact of the probability of leaving a rating.

Keywords: Central limit theorem; Incomplete non-iid observations; Product ratings; Strong law of large numbers (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1016/j.spl.2022.109387

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