Using online search data to forecast new product sales |
Abstract:
Search engines are rapidly emerging to be the “go-to” sites for consumers to learn more about a product, conceptor a term of interest, irrespective of the initial channel in which the interest originated — text, radio, TV, multimediachannels, word of mouth, etc. In this paper we argue that data on the search terms used by consumerscan provide valuable measures and indicators of consumer interest in a product, concept or a term. Such datacan be particularly valuable to managers in gauging potential product interest in a new product launch contextor consumption interest in the post-release context. Based on this premise, we develop a model of pre-launchsearch activity and link the pre-launch search behavior and product characteristics to early sales of the product,thus providing a useful forecasting tool. Applying themodel in the context ofmotion pictures,we find that searchterm usage follows rather predictable patterns in the pre-launch and post-launch periods and the model providessignificant power in forecasting release week sales as a function of pre-release search activity.With advertisingdata included in the model, we find that the pre-release search data offers additional explanatory andforecasting power, thus highlighting the ability of the search data to capture other factors, such as possiblyword-of-mouth, in impacting early sales. We offer specific insights into how managers can use search volumedata and the model to plan their new product release. |
| Keywords: |
Online search Entertainment marketing New product sales forecasting |
| Author(s): |
Gauri Kulkarni, P.K. Kannan, Wendy Moe |
| Source: |
Decision Support Systems 52 (2012) 604–611 |
| Subject: |
بازرگانی و تجارت |
| Category: |
مقاله مجله |
| Release Date: |
2012 |
| No of Pages: |
8 |
| Price(Tomans): |
0 |
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