Publishing Venue
The IP.com Prior Art Database
Abstract
Utility value of a product is hardly reflected by the specification provided by the manufacturers. The true or assessed value of a product comes through the user experience and reaches out to others through word-of-mouth. The increasing popularity of e-commerce application has led to inevitable integration of social media which fosters people to share their experience through reviews. Prospective buyers seek out these reviews for opinions and value assessed by the consumers on the product. The reviews express varied opinions on several attributes of the product. Diverse opinions on a product by large number of reviews induce dynamism in the assessed market value of the product. In this paper we attempt to capture the dynamism of the assessed market utility value of a product by observing opinions provided by consumers. We bring in the importance of utility value on time especially when opinions are expressed and sought. This is due to the fact that utility value is dependent on the number of the reviews and their content expressed before a consumer chooses to obtain this information. This inherently models the value of a product through out its life-time, as a period of no review will reflect deterrence in its assessed value. We study various attributes of a product that matters to the consumers and model the utility value as function of opinions expressed on these attributes over time. Our experiments are based on large scale review sets (approximately 30,000 reviews) collected from real world review collection portal i.e., Amazon, Mouthshut and IMDB. Our assessment shows that modeling utility as a function of time on the most valued attributes provides information that has greater impact not only to the consumers but also for manufacturers to understand the product value during its life-cycle.
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A system and method for deriving dynamics of consumer product assessment
Lifetime of a product in the market is determined by the response of the consumers to the
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rospective buyer of a particular product always seeks information about these factors, i.e., consumer opinions, market response and its performance compared to other competitors. In this context, one can devise a metric which could provide meaningful information about the product to the consumers. A metric that can provide such information can be termed as Product Utility Value (PUV). Although such metrics are derived from approximate analysis, they can provide the consumer with valuable information that influence the purchasing decision and can in turn affect the product revenue. Estimation of the PUV of a product is not a trivial task.
Normally
roducts are introduced with a default PUV which is determined by either manufacturer's bran
equity or through manufacturer's product specification. Specifications, although truthfully elicit the manufacturing standards a product adheres to, are far from expressing the values when subject to actual usage. Consumers seek opinions from their fellow counterparts who have
reviously purchased the product. Consumers tend to place trust on the value derived out of consumer experience which inherently simulates a large scale
usage test bed. For a consumer who wishes to buy the product, the PUV derived from the consumer experience changes his perception on the product and plays a significant role in influencing his buying decisions. It is therefore important to derive PUV by collating information from the consumer
experience. The gaining popularity of social media especially in E-commerce systems has paved the way for consumers to share their experience through reviews. A large volume of reviews and feedbacks are generated by many users to facilitate the potential buyers of a product. The opinion expressed in these reviews which reflects individual consumers value for a product can be utilized to derive the overall PUV. The opinions may vary from consumer to consumer and induce dynamism in PUV. PUV of a product is dependent on the time when the consumer seeks the information as PUV will be based on the existing reviews and opinions expressed in them. This leads to an interesting phenomenon that when there are no reviews either due to products not fairing well in the market or not fairly well established or another product have been launched with better attributes, PUV will appropriately reflect this to the consumers. In our work, we capture the dynamism involved in estimating the PUV by considering the temporal dependency of PUV on reviews. To the best of our knowledge our work is the first of its kind to model PUV as a function of opinions expressed and the time when it was expressed. A PUV thus derived also behaves as a
p
erformance reference index for the manufacturers reflecting the performance of the product with respect to differ...
