Managing the Complexities of Social Analytics

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Post 3 of 5 in a series

I Thought This Was Simple – The intricacies of social analytics do in fact exist, but are manageable. The solutions are reliant on the data as they ultimately need to interpret the data accurately. The keys to understanding the specifics of an implementation, whether it is existing or planned, is to manage the Data, Percentages, Sentiment, and Metrics.

The most complicated of these is managing the data, but that is also where the golden insights exist for a business.  When talking about Data these days, it is often preceded by the word “Big” and followed by slightly ambiguous, yet important terms such as: Volume, Velocity and Variety. These are known as the three V’s of Big Data.  Social Media data is subject to these words and their definitions if you have a meaningful amount of information being tracked for your company or the competition.

The Rule of Percentages – It is important to keep in mind that not all shared information is trackable simply because it originated in social media. People print to paper and electronic documents and share via file systems, chat systems and email.This is a classic marketing conundrum where it may not be possible to know the actual percentage tracked. Most estimates place the amount of tracked shares at a relatively low percentage, but meaningful from a market research and many other perspectives. Similarly, you must consider how much of your corporate data is captured within social media channels as this will influence the level of emphasis you place on the analysis. Data should always be taken in context.

A Few Thoughts on Veracity – Accuracy is an important facet in and of itself. This characteristic directly influences the quality of any analysis originating from the data.  Depending on the decisions being made, this may be a critical aspect to consider. What causes inaccuracies? They may be caused by variations in the origin of the data, such as posts coming from different channels or software. Semantic analysis algorithms, if used by a specific solution, may evaluate reviews or comments very differently causing variations in results. However, those solutions with semantic analysis often provide customization of how it is applied to the data.

A Marketer’s Perspective – Then how will these complexities be managed? Implementing consistent tracking methods within social posts will supply better initial data. Adding complementary information and transforming data as it is prepared may dramatically improve the resulting analytics and reporting. Finally, further improvements may be made by providing context when necessary to accurately comprehend the information. A marketer relying upon or presenting this information must be familiar with the details affecting the net result.

Staying Aligned – This sets the stage for aligning social analytics with sales and marketing objectives. Furthermore, it ensures the goals agreed upon are in fact measurable and actionable. Additionally, it proves progress against these goals can be tracked in order to determine what amount of variance in action will cause a certain amount of variance in result.

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