Putting Social Media in Context - Four Analytical Use Cases That Have Impact

Dan Grady's picture
 By | October 01, 2014
in WebFOCUS, Advanced Analytics, Analytic Dashboards, Big Data, Business Analytics, Business Intelligence, data visualization, Sentiment Analysis, Social Media
October 01, 2014

Putting social media data in context with other enterprise data allows you to maximize its analytical value.

The ALS Ice Bucket Challenge has served as a great reminder of the power of Social Media.   If you are not familiar with the challenge it is an activity involving dumping a bucket of ice water on one's head or donating to the ALS Association in the United States. See Wikipedia page for more. It went viral on social media this summer.  The awareness is one thing, but as with many social campaigns we are looking to quantify the value, and the most recent numbers are incredible.  From August 12th to August 27th they received 90 million in donations -- that is 35 times higher than for the same time period last year.  The other statistic worth noting is that the number of donors has increased by over 300,000.  Pretty impressive ROI for a social media campaign.

It’s outcomes like this that have organizations excited about social media’s potential, and have them rapidly moving through these three phases when it comes to social media:

·         Create a brand presence across social channels

·         Engage with customers and prospects via these social channels

·         Analyze the effectiveness of their social media efforts

Most organizations have a plan when it comes to the first two, but are struggling with the third because they are quickly recognizing that Social Media “Analytics” is more than just tracking engagement, it’s about understanding the overall impact of the activities by putting them in context.  But what does that even mean?  And why do organizations struggle with this? We’ll answer those two questions, backwards.  Organizations struggle to put their social activities in context because very often the analysis they are doing is limited to only social data.  That limitation can be the result of organizational politics, the listening platform software they are using, or in some cases simply a lack of vision.  I’d like to address the vision challenge here by providing 4 uses cases that have been effective in helping organizations  better understand how they can get more value out of their social media analytics efforts by adding context.

 

  1. Campaign Analysis – This is one of the most popular marketing activities when it comes to social media, and what most marketers struggle with is calculating the ROI on a given campaign.  Why?  Well, usually because you need the dollars spent on the campaign and the dollars generated to perform the ROI calculation.  The engagement-level data generated by social media platforms will help you analyze the if, when, and how much activity took place on the individual platforms but to put that in context you’ll need website traffic and financials.  That data typically lives in different systems, so to do effective campaign analysis you need to start bringing that data together.  The dashboard in our image gallery is an example where we are tracking social activity and also showing sales and transaction level data for the specific products referenced in the campaign. 
  2. Brand Crisis Situation Analysis – Social media data is very good for identifying problems or opportunities, but more often than not, you’ll need context to act on them.  Brand crisis situations are a perfect example.  In our gallery example, we are analyzing a data for a 10 day  period when a cruise ship stopped moving.   There is an individual who found the time to post 229 times on this company’s Facebook page in that 10 day period.  If the majority of this commentary is of the negative variety, that's an issue.  The company needs to figure out who this person is and how best to respond to them quickly. To do that will involve data not available on the social platforms – Is this person on the boat?  That will come from the manifest system.  Have they ever been a customer before? CRM system.  Are they a travel agent we use? Agency system.  The ability integrate social data with those other systems will make your more effective in these scenarios.
  3. Cross Channel Feedback Analysis – Social media has become just another channel your customers interact with your organization.  They provide feedback and submit questions just like they’d send an email to a help desk, or pick up the phone to call the call center.  From an organizational perspective there is tremendous value in analyzing this holistically rather than the silo’d approach many take today.  You may respond differently depending on the channel the feedback is coming in.   For example, if you are seeing a spike in negativity about a product on social media, but you aren’t seeing that same spike across your help desks, online forums, or call centers, then maybe you respond with a digital marketing campaign.  However, if the spike in negativity is consistent across all the channels you may have to make a bigger statement.  The screen in the gallery is an example of a search based application that is used for analyzing content across different channels.
  4. Comparative/Competitive Analysis – while the other use cases focused on putting social in context by integrating it with other enterprise data, this use case provides context by leveraging data related to your peers.  Rarely in the past have you had access to your competitors/peers data, but when it comes to social media, you do.  You can access and analyze what people are saying about others products and services just like you can do with your own.  For example, if I’m Wendy’s and I see a spike in activity on McDonald’s Facebook page, could I benefit from understanding its cause.  Are they running a new campaign that’s having success? Or are they in a brand crisis situation?  Did someone just find a shoe in a cheeseburger and now there is all this negative buzz online?  If the later, Wendy’s could quickly respond with their own digital campaign, “No Shoes in our Burgers”  The Comparative Dashboard in the gallery above is just one example of how to enable competitive or comparative analysis. 

Each of these examples is meant to highlight how you can leverage social media analytics to provide actionable insights, but to truly benefit from social media analytics you need to put the data in context, whether that context be gained by integrating it with other organizational data or by putting it in context with social data about your peers.

To help organizations get started we offer something we call the Social Medial Analytics Challenge, because it’s always easier to see opportunity when working in context of your own data.

For details on the challenge click here.

If you are interested in taking the challenge you can contact me at dan_grady@ibi.com