Over the last few weeks, we have been focusing on the importance of understanding the story within your social media content  as well as key questions to ask about the individual elements of your story. Today, we willing be diving into the process of data analysis and the tools that will provide you with a closer understanding of what consumers are thinking and saying about your brand.

Naturally, the first step is data collection. How are you collecting the details of your story? Are you using data services, web scrapers, listening platforms, research companies, surveys, or a combination of these methods? Do you have a representative sample of your data to provide accurate analysis?  While Twitter’s recent acquisition of Gnip may make make it easier to gather social media data, companies still must piece together data from various sources.

Identifying the right metrics to measure and classify your data is essential to avoid the “garbage in, garbage out” trap. What metrics are relevant to classifying your data? Are you measuring your content for basic sentiment and/or topic classification and are these results providing actionable insight?

This is where human logic, reason, and context are essential. What tools and methods are you using to help derive insight? Do your current tools provide you with the valuable, actionable and relevant views of your data?

How are you visualizing your data and getting to that “ah-ha!” moment? Are personalized dashboards with charts and tables your bread and butter or do you prefer making conclusions from detailed Excel spreadsheets?

Utilizing double-screen monitors, many analysts use spreadsheets, word processing, and slides to consolidate their data into a recognizable format. How are you compiling your data in a way that makes sense?

What is the final product of your analysis? Are your managers and colleagues expecting an infographic-heavy Powerpoint presentation, a concise quarterly report with both written and visual analysis, an oral presentation supported by numbers, or a combination of the above?

At the end of each data analysis process, humans are the ones making conclusions from the data output their tools provide, usually pulling from a variety of platforms and conducting analysis with the help of a number of tools. Despite all the advances in technology, there is yet to be a tool on the market that enables human analysis in one place or a product that accelerates a user’s ability to get the heart of the story … yet.