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8. Decoding Digital Consumer Feedback: Customer Intelligence Insights Through Unstructured Data Mining

  • 2018
  • OriginalPaper
  • Chapter
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Abstract

This white paper is based on a study that focused on understanding the perceived strengths and weaknesses of one of the largest PC and printer technology companies in relation to its competitors’ offerings by mining consumer opinions and feedback on a major regional e-commerce website, JD.com. The objective was to understand how the company’s printers were perceived and to identify the features that differentiated one brand from another. Text mining and sentiment analysis was conducted using an in-house sentiment analysis tool. Insights from this analysis helped to identify broad customer themes across different competitor inkjet products, confirm the value proposition of low supply costs for certain printer models owned by the company, and highlight other key advantages and pain points of inkjet products. Several data mining tools are available that are helpful in sentiment analysis, but the in-house tool had a built-in algorithm that captured real-time data from various social media. The finding from this exercise of customer review analysis was shared with the relevant teams. Some of the insights helped to validate the approach taken by the research team and also indicated what the features were that could differentiate the product from its competitors.

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Title
Decoding Digital Consumer Feedback: Customer Intelligence Insights Through Unstructured Data Mining
Authors
Supriya Tandon
Aswinraj Govindaraj
Copyright Year
2018
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-5323-8_8
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