Cloud Computing Business Intelligence -

Cloud Computing

Business Intelligence - Cloud Computing

The emerging area of social marketing analytics which is today delivered on the Software-as-a-Service (SaaS) or cloud platform (Lawrence, Melville, Perlich, Sindhwani, Meliksetian, Hsueh & Liu, 2010) is used for interpreting and analyzing all messages on social networks relating to a company or product (Raab, 2010). This is one of the newest areas of Business Intelligence (BI), with several new suites of applications still in the R&D stage yet several significant new product introductions this year. The most noteworthy is the SAS Social Marketing Service (Marketing Weekly News, 2010) which is entirely Web-based and supports integration to Facebook, Friendfeed, Twitter and many other social networks. The intent of this analysis is to evaluate the use of social marketing analytics and evaluate the entirely entrants into this market including SAS (Marketing Weekly News, 2010).

Evaluating Social Marketing BI Software

The intent of using social marketing analytics software is to gain greater insights into the unstructured content that is growing exponentially on social networks. The use of advanced unstructured content management techniques and systems including latent semantic indexing (LSI), semantic analysis, sentiment analysis are all used for interpreting and organizing unstructured content into models that can be used in decision-making (Tyagi, 2010). This new area of social marketing analytics for the first time gives companies the ability to quickly parse through unstructured content both internally and externally and gain new insights into how customers perceive their products and services (Tsai, 2009). From this standpoint social marketing analytics compliments and strengthens existing BI platforms, the majority of which analyze only structured content.

It is estimated that 90% of a company's content is unstructured and the majority of insights for devising more effective strategies can be obtained from this content through more effective BI methods (Marketing Weekly News, 2010).

The benefits of social marketing analytics include the ability to quickly parse or analyze literally terabytes of unstructured content obtained from social networks and then succinctly define a linguistic model showing a company's strengths and weaknesses from a customer perception standpoint. These linguistic models encapsulate the unstructured data and make it possible to devise queries and complete further analysis. In addition companies have a baseline measurement of how their customers perceive them from both a positive and negative standpoint. The downside if social marketing analytics is the cost for integrating these BI systems with legacy systems (Raab, 2010) and the ramp-up for learning their advanced features (Tsai, 2009).

The data quality of these systems is excellent as they are more attuned to encapsulating and summarizing the data so it can be quickly used within a BI system and in marketing campaigns. In terms of data privacy, the systems are as secured as the networks of the companies using them. The level of security and authentication needed to gain access to these systems is determined by their level of system administration-based options defined.