Decoding Digital Consumer Feedback: Customer Intelligence Insights Through Unstructured Data Mining
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 maj
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Decoding Digital Consumer Feedback: Customer Intelligence Insights Through Unstructured Data Mining Supriya Tandon and Aswinraj Govindaraj
Introduction The company’s Printing and Personal Systems marketing team enlisted the help of the Analytics team to investigate factors driving lower sales results for two key inkjet printer families. This investigation focused on understanding perceived strengths and weaknesses of the company’s printers relative to its competitors’ offerings by mining consumer opinions and feedback on a major e-commerce website, JD.com. The team conducted text mining and sentiment analysis using an in-house 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, and highlight other key advantages and pain points of company’s own inkjet products. The calibration technique employed further by the team helped to identify the key product differentiators and these insights were employed by the Regional Marketing team to redesign their go-to market strategy.
S. Tandon (*) • A. Govindaraj Hewlett Packard Enterprise, Bangalore, Karnataka, India © The Author(s) 2018 G. Heggde, G. Shainesh (eds.), Social Media Marketing, https://doi.org/10.1007/978-981-10-5323-8_8
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Problem Statement The printing group within the company had a strategy for developing new business models that targeted price-sensitive customers in emerging markets such as China and India. The technology company’s inkjet printer had a value proposition of a relatively high price for hardware but a low price for supply, and vice versa. But in early 2013, in spite of this strategy, the actual sell-thru of key inkjet printer families, (ultra) ink advantage (UIA/IA), was only 50 percent of the target. Hence the Regional Business Unit wanted to understand its advantages and weakness in these printer families compared to those of competitors, based on unstructured data such as real end users’ experience, available on social media. Local e-commerce websites such as JD.com were popular purchase avenues and also platforms where several customers shared their user experiences of technology products. The Regional team therefore wanted to drill down inside customer reviews from JD.com to identify specific product attributes and learn how the customers’ felt about them. This would not only help to confirm the value proposition that was being offered by the company and understand the advantages and weaknesses vis-à-vis the competition but also redesign/implement the go-to market (GTM) strategy for these printers. The printer families were select models of single-function printers (SFPs) and multifunction printers (MFPs) of key competitor brands where real end-user experience and feedback was available in the public domain. Thus, the main objective was to understand customers’ perceptions of the printers and the features that differentiated one brand from another.
The Solu
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