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Practice paper

Analysis of Voice of Customer data through data and text mining

Jonathan Frey and Sergei Ananyan
Applied Marketing Analytics: The Peer-Reviewed Journal, 2 (3), 192-200 (2016)
https://doi.org/10.69554/UYWT1270

Abstract

The importance of great customer service to building a strong business has prompted increased interest in applying text analytics to customer data. To demonstrate power data and text-mining techniques, we present two case studies outlining the use of advanced text analytics for the analysis of Voice of Customer (VoC) data collected from both external and internal customers of Taco Bell Corporation. External VoC data was collected through several channels over three years and analysed using text-mining techniques. Using historical data, a detailed taxonomy of keywords that typically occur in customer comments was developed to characterise these comments into meaningful categories, with sentiment scoring rules applied to the keywords for further classification. Over 2,000,000 customer contacts were analysed, and the findings were correlated to the structured data collected on the surveys, providing key insights on product, service and facility topics. The impact on overall satisfaction was measured for each topic area, providing focus for the operation of the restaurant. A second case study highlights how data and text-mining techniques provided actionable insights, allowing the internal information technology support service desk to implement changes that improve call answering times and reduce the impact of these issues on sales transaction revenue.

Keywords: Voice of Customer; text mining; data mining; taxonomy; reporting; customer service

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Author's Biography

Jonathan Frey is recently retired from his position as Director of Operations Intelligence at Taco Bell Corporation, where he served for 15 years as a data scientist for Operations, Finance, IT, R&D and HR-related projects. Prior to joining Taco Bell, Jonathan served as a Product Development Manager at Mars for 13 years and at Kraft, Inc. as a Research Scientist for four years. He holds a BS in Bacteriology and a PhD in Food Microbiology from the University of Wisconsin–Madison.

Sergei Ananyan is the CEO of Megaputer Intelligence. Sergei heads a team of consultants who create and customise advanced analytical solutions addressing challenges encountered by practitioners primarily in the insurance, financial and medical domains. He has extensive hands-on experience in survey and social media data analysis, as well as insurance claims analysis, fraud detection and e-Discovery. Sergei plays an active role in the development of a leading data and text mining system, PolyAnalyst™, which is currently used by hundreds of commercial, research and government organisations throughout the world.

Citation

Frey, Jonathan and Ananyan, Sergei (2016, September 6). Analysis of Voice of Customer data through data and text mining. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 2, Issue 3. https://doi.org/10.69554/UYWT1270.

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cover image, Applied Marketing Analytics: The Peer-Reviewed Journal
Applied Marketing Analytics: The Peer-Reviewed Journal
Volume 2 / Issue 3
© Henry Stewart
Publications LLP

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