Abstract
Temporary deals such as flash sales nowadays are popular strategies in retail business for cleaning out excessive inventories. It is known that the success of a temporary deal is related to product quality, promotion, and discount rates. In this paper, we look at another more obscure factor, that is the timing in the market, and we argue that such timing can be learned from social media. For example, the trending of words “summer” and “ice cream” in social media may indicate successful sales of air conditioners. We propose an approach to detect emerging words in social media as timing signals, and associate them with successful temporary deals. More specifically, the words that tend to emerge just before successful deals are considered as effective timing signals. We obtain a real-world temporary deal dataset from an industry partner and collect a social media datasets from Twitter for experiments. With experimental evaluation, we show and discuss the discovered timing signals. Furthermore, we propose a prediction framework and show that using social media timing signals can achieve better accuracy for predicting temporary deal success, comparing to internal deal information.
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Data Availability
The work in this paper involves two datasets, an e-commerce dataset and a social media dataset. We are unable to make the e-commerce dataset publicly available due to our agreement with our industry partner. However, the social media dataset is freely available from the corresponding author upon request.
Notes
Such a list can be found online as political social media accounts are usually public. An example list is provided by the website Meyou with the url https://meyou.jp/group/category/politician/
By, for example, using the free API Twitter provides
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This research is partially supported by JST CREST Grant Number JPMJCR21F2.
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Zhang, Y., Shirakawa, M. & Hara, T. Predicting temporary deal success with social media timing signals. J Intell Inf Syst 59, 1–19 (2022). https://doi.org/10.1007/s10844-021-00681-6
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DOI: https://doi.org/10.1007/s10844-021-00681-6