Social media competitive analysis and text mining: A case study in the pizza industry

作者:

Highlights:

摘要

Social media have been adopted by many businesses. More and more companies are using social media tools such as Facebook and Twitter to provide various services and interact with customers. As a result, a large amount of user-generated content is freely available on social media sites. To increase competitive advantage and effectively assess the competitive environment of businesses, companies need to monitor and analyze not only the customer-generated content on their own social media sites, but also the textual information on their competitors’ social media sites. In an effort to help companies understand how to perform a social media competitive analysis and transform social media data into knowledge for decision makers and e-marketers, this paper describes an in-depth case study which applies text mining to analyze unstructured text content on Facebook and Twitter sites of the three largest pizza chains: Pizza Hut, Domino's Pizza and Papa John's Pizza. The results reveal the value of social media competitive analysis and the power of text mining as an effective technique to extract business value from the vast amount of available social media data. Recommendations are also provided to help companies develop their social media competitive analysis strategy.

论文关键词:Social media,Facebook,Twitter,Case study,Pizza industry,Competitive analysis,Competitive intelligence,Competitor intelligence,Actionable intelligence,Text mining,Content analysis

论文评审过程:Received 27 September 2012, Accepted 2 January 2013, Available online 4 February 2013.

论文官网地址:https://doi.org/10.1016/j.ijinfomgt.2013.01.001