Social media have been proved as a tool for social branding, but not as a tool for return on investment (ROI) generation. The ultimate goal of any business activities is to generate ROI; therefore, businesses should know what social media practices actually increase their ROI. Researchers in the computer science and engineering areas have attempted to create a systematic model/statistical method to quantify data collected from social media to generate meaningful consumer and market trends and ROI (Zeng, Chen, Lusch, & Li. 2010). This process is called Social Media Intelligence (SMI) or Social Media Analytics (SMA). Researchers have not been yet successful in developing an effective analytical system for social media data to generate ROI. Therefore, the purpose of this study is to explore which social media practices would affect ROI based on SMA process with key techniques used to analyze the indicators in social media (i.e., Key Performance Indicators; KPIs) that show the effectiveness of a company in achieving its business objectives. This study is an exploratory research to determine the nature of a problem in the SMI, to gain further insight, and to show opportunities in the subject area. The result shows that using crawling, topic modeling and social network analysis techniques, businesses could collect and monitor right KPIs depending on their social media goals (e.g., number of followers for awareness, number of link clicks for engagement, number of lead magnets for conversion). After then, using the techniques to analyze the KPIs (e.g., opinion mining, sentiment analysis, etc. for the understand stage), businesses would be able to identify/predict consumer demands and market trends. Based on this prediction, businesses need to visualize the result to customers by executing right marketing strategies (e.g., effective viral marketing, personalized Call-To-Action, customized product/service, direct relationship establishment, frequent communication, establish long relationship, etc.). This study could contribute to the field by presenting the effective KPIs and techniques organized based on the SMA stages and social media goals and could provide the industry a right tool and a direction for their social media promotional practices.

This study is intended to provide marketing practitioners with an overview of web analytics to explore the issue of how to define and measure the effectiveness of social media through analyzing the various activities of current/potential consumers as well as provide a comprehensive analysis of the effectiveness of digital content marketing using social media. These analytics answer broad questions about which types of social media metrics are best at referring traffic, about conversations at the organization’s website, and about comparing different social media channels, such as Facebook and Twitter in this study. The major goal of this study is to demonstrate the value of businesses’ efforts and to optimize their digital/social marketing strategy using web analytics. Based on this goal three research questions were identified: (1) can the model identify social media performance variables that are related to audience response which can be represented by website traffic?; (2) which social media sties are driving traffic to a firm’s website, specifically in B2B environment?; and (3) can the model provide insight into the importance of those variables? These analytics employ time series analysis to specifically address activities in SNSs that effectively drive traffic to a website and accomplish business goals. This study is one of the first empirical investigations in the marketing communication field related to measuring social media’s effectiveness.

This research is intended to provide marketing practitioners with an overview of web analytics to explore the issue of how to define and measure the effectiveness of social media through analyzing the various activities of current/potential consumers as well as provide a comprehensive analysis of the effectiveness of digital content marketing using social media. These analytics answer broad questions about which types of social media metrics are best at referring traffic, about conversations at the organization’s website, and about comparing different social media channels, such as Facebook and Twitter in this study. These analytics employ time series analysis to specifically address activities in SNSs that effectively drive traffic to a website and accomplish business goals. This study is one of the first empirical investigations in the marketing communication field related to measuring social media’s effectiveness. The major goal of this study is to demonstrate the value of businesses’ efforts and to optimize their digital/social marketing strategy using web analytics.