Tuesday, May 27, 2014

Lesson #178: Predictive Social Analytics

Posted By: George Deeb - 5/27/2014


& Comment

Businesses have long struggled to assign ROI to social media marketing efforts. To address this, there is a new trend towards predictive social analytics, which we will discuss in the post.  To assist me here, I sought input from my colleague, Jeff Revoy, the CEO at Viralheat, an early-mover in the predictive social analytics space.

To date, marketers have largely relied on engagement metrics, like follows, likes, shares and retweets, to serve as key performance indicators of social media effectiveness. This strategy divorces social media marketing from a business’s bottom line, as likes and comments don’t necessarily equate to purchases.  And, sponsored content and ads, which have been the primary tactics businesses have used to stay top-of-mind with consumers, can be expensive and obtrusive, using push vs. pull techniques.

Enter predictive social analytics to the rescue, which finally allows businesses to anticipate potential purchasers via social media and capture more leads using human intent and sentiment analysis technologies.

So, how does it work? Let’s look at an example using hashtags in Twitter.  When a Twitter user tweets #moving or #iamengaged, predictive social analytics tools identify these specific tweets as indicators of future human intent and sentiment (in this case, as potentially pre-qualified leads for moving or wedding services), and then imports them into a marketing or sales automation platform like Salesforce.com, Marketo, Hubspot or Eloqua.  Then, if you were the moving company or wedding service in this example, your sales team would then reach out to these users via relevant tweets on Twitter, instead of cold calling them.

Today, there are an array of social media management suites available, that provide social publishing, analytics and monitoring.  From free-trial versions like Sprout Social, TweetDeck or HootSuite, to pricey large-scale enterprise-ready systems like Radian 6, which require big budgets and months of training.  But, these systems largely spit out a fire hose of un-actionable social data, and are not focused on identifying relevant sales leads.

The reason I reached out to Viralheat for this post, is the fact they were the first ones to tackle this “social data to sales leads” opportunity, which I thought was an interesting next evolution in social media marketing.  So, in addition to the social publishing, analytics and monitoring tools which most platforms offer, ViralHeat has added these predictive social analytics tools, which takes social media monitoring and turns it into lead-generating workhorse for your business.

More importantly, predictive social analytics is leading to high-ROI case studies, like this one for Viralheat client, Men's Warehouse.  It suggests that Men's Warehouse is driving revenues of around 20-30x the cost of their predictive social analytics software (assuming they have around 2MM unique monthly visitors to their website, 2% of which have been identified as coming from predictive social analytics efforts and such traffic converts into sales at normal e-commerce conversion rates of around 3% with an estimated average ticket of $50).

If you have any other questions here, Jeff has gratiously made himself available.  Feel free to contact him at 866-832-2197 or via the contact form on the Viralheat website.

For future posts, please follow me on Twitter at: @georgedeeb.

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