The case “Text Mining of Fitbit’s Twitter Data – Gaining Business Insights” primarily discusses the process of text mining undertaken on the Twitter data of leading global wearable brand, US-based Fitbit, Inc. (Fitbit) to derive insights related to brand perception and customer service. The case starts out by presenting an overview of the Fitbit Company and then gives a brief description of the elements of text mining. Then two instances wherein independent data analysts conducted text mining on Fitbit’s Twitter data are provided to identify the positive and negative sentiments around the brand and categorize customer complaints. The case discusses in detail the reasons for which Fitbit’s Twitter data analysis was undertaken and provides an overview of the insights that were derived through text mining. As of 2020, leading US-based multinational technology company Google LLC (Google) had acquired Fitbit in a bid to gain an incredible amount of user data, which it intended to leverage for healthcare analytics post acquisition. It remains to be seen whether Google would continue to conduct text mining on Fitbit-related social data to gain valuable business insights.
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The case is structured to achieve the following teaching objectives:
Analyze the importance of gaining business insights from social networks.
Realize the advantages that organizations can derive from employing text mining tools on social data.
Scrutinize the kind of information technology infrastructure that companies need to put in place to analyze their social media and know about their customers’ consumption patterns.
Examine the importance of sentiment analysis done on a company’s social data in understanding brand perception.
Understand the importance of deploying data analytics tools like text mining to analyze customers’ complaints on social media.
Business Analytics; Text Mining; Web Mining; Social Data; Databases and the Web; Sentiment Analysis; Data Mining; Customer Experience Management; Brand Management; Social Media Analysis; and Gaining Business Insights; Social Media; Consumer Behavior; Customer Support; Product Management