Using Social Media Analytics To Quantify Fan Engagement
The fan experience has changed with the introduction of social media. Teams observe and intermingle with customers across multiple channels giving both increased interaction. However, measuring fan engagement across channels and within lively social spheres can be difficult. Marketers often struggle quantitatively valuing a “like”, retweet, or moderating a forum. The solution to these challenges is to use analytics and text mining. The presentation reviews collecting social information and analytical frameworks for fan engagement, topic identification, and customer segmentation then attempts to measure these interactions against team related merchandise using Amazon.com’s Sales Rank as a proxy.
Ted Kwartler is a data-driven expert in analytics applied to production environments. Ted worked in Amazon.com’s customer service organization, using data for coaching, new product launches, call forecasting, and workforce planning. Additionally, he created Amazon’s Social Care Unit serving customers on Twitter, online forums, and multiple Facebook pages. Currently, Ted works as a Director of Advanced Analytics for a Fortune 100 Insurance company. His team of analysts provides actionable recommendations to improve efficiency, understand the voice of the customer, and forecast production demand. Ted holds an MBA from the University of Notre Dame with a citation in analytics and marketing.