Are you on the Road to Social Analytics Maturity?

By: Clarabridge Team

March 6, 2014

By: Graham Hudgins, Product Management Architect

In my experience, social analysis is time consuming and sometimes can be overwhelming. So where do you start? What should you look for when you’re just starting out? What different types of insights can you find as your social analytics team matures?


 Volume and Buzz – Whenever you start a new social analytics program, the first step is to see what topics get the most attention, identify trends, and understand, directionally, where things are heading.  This is a place for your team to begin as you use DVR-like social aggregators to rapidly build historic data on the fly.

Deep Topic Analysis – By using advanced spam detection techniques, you eliminate the noise and get down to the things that matter to your business.  The goal is to understand why customers are talking about you using positive and negative sentiment.  Doing this well is likely to increase acceptance throughout your organization as to the value of your social analytics program and show why your chosen CEM tools are better than manual methods and other platforms.

Multi-Source Analysis – This is where I see the leaders start to separate from the herd. It’s easy to say, “I am multi-source.” It is much harder to use all of your sources of data to put together a compelling narrative that hits on the true phases of the customer journey.  Start with a single issue; pull in the social feedback including the deep topic analysis mentioned above. Next, using the same topic as a reference point, trace how the conversation changes, starting during the sales process as the social posters become customers. Watch how many people write your support team about the topic or issue you’re investigating. Track how many are chatting about that same issue on your website, and finally look at how many employees share concerns on behalf of your customers.  This holistic view can level the playing field for decision makers. They don’t need to speculate; they can clearly see the reach of an issue.  If you do this, you’re a rock star in my eyes…but like anything, it’s a step in your insights journey.

Data-Driven Insights – How did your last insights analysis project start?  Was it just time to look, according to a release or campaign calendar? Did an executive’s daughter have an experience that caused you to react (true story)?  While these might be legitimate reasons to look into your data, they are not data-driven insights.  Data-driven insights occur as you detect new patterns and capture new information as it breaks.  You can go to a stakeholder and say, “Did you know that GTA5 just tanked our brand sentiment?  How should we try to recover this?”  If you do this well, you start getting that “magic crystal ball” swagger.

 Self Service Insights – At the end of the day, most social analytic teams have a resource problem.  Who should you support?  There’s always a priority—implicit or explicit.  However, if you empower the decision makers with data, then your platform is scalable. Effective data visualizations can help business users find “journalistic headlines” so they can champion the data in their business without you.  No, they don’t need to be advanced CEM tool users – you are still the expert and the support net for advanced analytics. But if you give them the capability, they can take care of the easy stuff that used to keep you busy (well, you’re probably still busy, but hopefully with more strategic work).

 It has really helped me to think about the world this way.  If you know how much of each type of social analysis you are doing, it helps you manage the time spent on various projects and fire drills.  The goal is to become mature enough as a social analytics team to maximize the time spent focusing on the richest information in order to drive the most intelligent decision-making.