Analytics Plays an Important Role in Social Media

Social Media data is the new gold and analytics for the businesses. Social media analytics is an amazing art and science of extracting valuable hidden business insights from the platform called social media. Because of rich diversity the social media have to use the analytics very safely and carefully. Not all the tools will get fit into the scenario that�??s why there are four distinct types of analytical procedures which will help in obtaining the social media analytics. Following are the four types of social media analytics tools:

Descriptive Analysis: This is reactive in nature. Descriptive analysis is one of the main parts of social media analytics which aggregates data in terms of visualizations, reports and clustering. Descriptive SMA deal with the questions like �??what happened or what is happening?�?? Descriptive analytics collects and define social media data in the form of reports, visualizations, and clustering to understand a well-defined business problem or opportunity. Social media user comments analysis, for instance, falls into the descriptive analytics category. To formulate a business opportunity, such type of analytics works on readily available data like user comments to understand the trends, moods and sentiments of the current market.

Diagnostic Analytics: This is reactive in nature. Diagnostic SMA Analytics deals with the type of questions like �??why something happened?�?? For example, while descriptive analytics can deliver an overview of your social media marketing campaign�??s performances (posts, mentions, followers, fans, page views, reviews, pins, etc.) diagnostic analytics can refine this data into a single view to see what is already worked in past days and what�??s not. Enablers of diagnostics analytics include inferential statistics, behavioral analytics, correlations & retrospective analysis and outcome being cause and effect analysis of a business. It is an exciting kind of analytics that searches the causal connections between an event and the social media reactions.

Predictive Analytics: This is proactive in nature. Predictive analytics involves analyzing the large amount of accumulated social media data to predict a future event. Thus, it deals with the question like �??what will happen and or why will it happen?�?? For example, an intention expressed over social media such as buy, sell, recommend, quit, desire, or wish) can be mined to predict a future event (such as a purchase. Alternatively, businesses can predict sales figures based on historical visits (or in-links) to a corporate website. So, if a user expresses something regarding the product, such analytics will tell you whether the user ends up buying it or not.

Prescriptive Analytics: This is proactive in nature. While predictive analytics help to predict the future, prescriptive analytics suggest the best action to take when handling a scenario (Lustig, Dietrich, et al. 2010). For example, if you have groups of social media users that display certain patterns of buying behavior, how can you optimize your offering to each group? Like predictive analytics, prescriptive analytics has not yet found its way into social media data. The main enablers of prescriptive analytics include optimization and simulation modeling, multi-criteria decision modeling, expert systems, and group support systems.

Hence, these four analytical tools are very useful for the social media analytics. Not all the tools will get fit into the scenario that�??s why there are four distinct types of analytical procedures which will help in obtaining the social media analytics.

Source: HOB

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