A Competitive Analysis of Coffee Franchise Brands on Social Media Using Big Data

The rapid growth of users in social networking services has pushed many businesses to adopt social media. In several industries, such as franchise coffee chains, where many companies need to interact often with customers, social networking sites have been used as the most effective tools. Therefore, a big data of user-generated contents in such social networking sites is freely available to every company in the industry. This opens opportunities for increasing competitive advantage and effectively accessing competitive environment of businesses via mining that big data. The companies can monitor and analyze customer-generated contents not only about their own brands but also about their competitive brands on social media sites. This paper proposed a method to apply mining social network data in the context of franchise coffee brands. We conducted a research on ten coffee chains including Starbucks, Caffebene, Tom-N-Tom Coffee, Angel-in-us Coffee, Hollys Coffee, The Coffee Bean & Tea Leaf, Beans Bins Coffee, Ediya Coffee, A Twosome Place, Coffine Gurunaru with unstructured textual data from Facebook in South Korean market. The results show that the companies can extract business value from mining the huge amount of available social media data and strategically use them for attaining competitive advantages. Based on this study outcomes, we provided recommendations to help companies develop their social media competitive analysis strategy.