scholarly journals Deriving the Pricing Power of Product Features by Mining Consumer Reviews

2011 ◽  
Vol 57 (8) ◽  
pp. 1485-1509 ◽  
Author(s):  
Nikolay Archak ◽  
Anindya Ghose ◽  
Panagiotis G. Ipeirotis
2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Rushtin Chaklader ◽  
Matthew B. Parkinson

The objective of this work is to introduce a new method for determining preliminary design specifications related to human-artifact interaction. This new method uses data mining of large numbers of consumer reviews. User opinion on specific product features can be time-consuming or expensive to obtain through traditional methods including surveys, experiments, and observational studies. Data mining review text of already released products may be a potentially less time consuming and costly method. Previously established methods of determining design for human variability information from consumer reviews, such as the frequency and accuracy summation (FAS) number and subsequent manual analysis, are explored. The weighted phrase rating (WPR), a new metric which can be an automated tool to quickly analyze consumer reviews, is also introduced. It does not require manual parsing of the reviews, which extends its applicability to larger review pools. This new method is shown to quickly and economically provide information useful to the establishment of design specifications.


2020 ◽  
Vol 115 (11) ◽  
pp. 824-828
Author(s):  
Adrian Barwasser ◽  
Joachim Lentes ◽  
Oliver Riedel ◽  
Nikolas Zimmermann
Keyword(s):  

2021 ◽  
pp. 1-18
Author(s):  
Matthew D. Hilchey ◽  
Matthew Osborne ◽  
Dilip Soman

Abstract Regulators require lenders to display a subset of credit card features in summary tables before customers finalize a credit card choice. Some jurisdictions require some features to be displayed more prominently than others to help ensure that consumers are made aware of them. This approach could lead to untoward effects on choice, such that relevant but nonprominent product features do not factor in as significantly. To test this possibility, we instructed a random sample of 1615 adults to choose between two hypothetical credit cards whose features were shown side by side in tables. The sample was instructed to select the card that would result in the lowest financial charges, given a hypothetical scenario. Critically, we randomly varied whether the annual interest rates and fees were made visually salient by making one, both, or neither brighter than other features. The findings show that even among credit-savvy individuals, choice tends strongly toward the product that outperforms the other on a salient feature. As a result, we encourage regulators to consider not only whether a key feature should be made more salient, but also the guidelines regarding when a key feature should be displayed prominently during credit card acquisition.


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