Big Data (noun): “A vastly overused term thrown around to make people feel better about their decisions that may or may not take real metrics into consideration.”
Social Media (noun): “A bizarre hurricane of fragmented, irrational thoughts interrupted by paid advertising that has about a 2% chance of being relevant to you.”
Many marketers are focusing their efforts on big data analytics. Big data entails the gathering and analysis of data from all possible sources (another definition, I suppose), including social media data. Unlike other sources, data from social media can be tricky. While the basic premise of big data analytics is to gather as much valuable data as possible, including all social media data, it may become counterproductive and distort the analysis.
Successfully navigating the minefield of social media data requires the following considerations:
- Do not ignore sentiment. Data from transaction logs are straightforward. The customer purchased “x” at a specific date and time. However, a Facebook post can have multiple meanings. Rather than taking the message literally, the marketer needs to identify the underlying sentiment in the posted message. Every interaction is either positive or negative, there is no neutral ground in social media as we have to come to learn all too well recently.
- Look beyond the company name or usual keywords. Many social mentions may not include the company name. Many customers, for instance, may type “me, too” in reply to someone else’s post, duplicating the sentiment. Automated keyword-based scanning would miss capturing this expression. Marketers need to pay attention to everything their prospects or customers say on social media.
- Social media is real-time. That said, it stands to reason that social media data has an expiration date. Posts made yesterday may not be relevant today. Marketers need to ensure social media data aggregated is relevant and not out-of-date. That being said, engagement outlasts social media in nearly every imaginable situation. Even if a tweet is determined to be irrelevant in a matter of 24 hours, the fact that this contact took the time to engage to the point of tweeting/mentioning/retweeting far outlives the relevancy of their post.
- All social media is not equal. Privacy settings may make it impossible for marketers to see everything a prospect writes on Facebook. In contrast, something posted on Pinterest stays there in open display forever. On the other hand, tweets are time-barred. Marketers have to factor in these limitations before assigning value to data. Another aspect to analyze is referral source to your website: most marketing automation systems allow users to assign lead scoring values to the traffic referral source. Are you closing every lead that comes to your website via Facebook? Assign more points to leads from Facebook to ensure that your sales team is aware of these “hot” leads coming into your system.
- Everything on social media isn’t always true, considering that it is a free-for-all landscape. It is common for reputation managers and people with various vested interests to express incredibly positive or negative sentiments. These posts, far removed from reality, can distort big data analytics. Although not everything is true, keep in mind that on the social media landscape, “perception is reality.”
As part of our lifecycle marketing automation solution, Right On Interactive incorporates social integration so brands can gauge sentiment and better manage social reputation as well as score on the different actions on each platform including Twitter, Facebook, and LinkedIn.
What kind of tools do you have in place to gain visibility into what people are saying about your brand on social media? To take visibility a step further, how are you scoring these different sentiments and engagements?
