Competitive Intelligence (CI) as the process of collecting data, analyzing it, and disseminating intelligence to decision-makers to improve the assessment of threats, risks, and opportunities relies on various source of data collection. Among such sources are the Internet and its increasingly popular offspring Social Media (SM). This quantitative research with an abductive approach used a descripto-explanatory model adapted from Schmidt (2000) and Teo (2001) to examine the effectiveness of CI when gained from SM for business-to-business (B2B) purposes.A Survey adapted from Chen et al. (2002), and Dey (2011) was used to collect 88 B2B business managers’ responses in Canada, the United States, and Sweden. Differences were seen between the efficiency of CI used in different types of decision-making. The findings of the study showed that among the three main types of decision making (strategic, tactical, and operational), SM can contribute to CI which supports tactical decision-making in areas such as regional biases, customer segmentation, popularity of products, and the popularity of products. However, they rank below other CI sources in supporting strategic and operational decisions in areas such as industry warning, country risk, and price fluctuations. As such, when extracting data and mining them for internal use in a B2B organization, managers and CI experts should consider the applicability and reliability of SM data before disseminating them to decision-making processes. The study proposed a framework for examining the role of SM in decision-making processes in a B2B context, which can be applied for further investigation into the implications of such data.