Clarity 2.0: Improved Assessment of Product Competitiveness from Online Content

Document Type

Article

Publication Date

Summer 2021

Abstract

Competitive analysis is a critical part of any business. Product managers, sellers, and marketers spend time and resources scouring through an immense amount of online and offline content, aiming to discover what their competitors are doing in the marketplace to understand what type of threat they pose to their business’ financial well-being. Currently, this process is time and labor-intensive, slow and costly. This paper presents Clarity, a data-driven unsupervised system for assessment of products, which is currently in deployment in the global technology company, IBM. Clarity has been running for more than a year and is used by over 4,500 people to perform over 200 competitive analyses involving over 1000 products. The system considers multiple factors from a collection of online content: numeric ratings by online users, sentiment of user generated online content for key product performance dimensions, content volume, and topic analysis of content. The results and explanations of factors leading to the results are visualized in an interactive dashboard that allows users to track their product’s performance as well as understand main contributing factors. Its efficacy has been tested in a series of cases across IBM’s portfolio which spans software, hardware, and services. After initial release and first year of use, improvements to the methodology were implemented to ensure it was relevant to and served the highest impact needs of target users. Moreover, new use cases leveraging the initial ideas and approaches continue to be explored.

Comments

Yufeng Huang is an adjunct professor at Sacred Heart University. He was the technical lead of the Clarity project and a lead data scientist at the Chief Analytics Office at IBM.

DOI

10.1609/aimag.v42i2.15100

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