What differentiates social strategy from social media practice? It’s this: Strategy sets policy and direction while practice involves engagement and conversation. The two are intertwined and interdependent – you can’t create connections and conversations without content and information, and you can’t drive policy and direction without creating relationships and building engagement through conversation.
Many of the social practitioners that I know talk about their roles in terms of where they add value: in building relationships and in creating and curating content. Some recurring themes of discussions in this vein are relevance, timeliness, and context.
Now, social strategy is taking on another role. Social networks have accumulated vast stores of data. And the complexity and depth of data requires expertise in data analysis to separate what many talented strategists might know as ‘gut’ or ‘intuition’ from information that is based on what the data tells us. Experienced social strategists can cite many examples in which data and information run contrary to statements of intent. It’s in the nature of humans to act differently from the way we talk.
The implications of data science (including bigdata analysis and trending, along with the aspect of influence) are obvious in the business sector in terms of understanding things like consumer behavior and psychology. How about using such tools in the context of quantifying, understanding and predicting impacts on societal issues and solutions? A few recent examples: social unrest in the city of Ferguson, Missouri and the outbreak of ebola in West Africa. The point being that there are ‘hidden’ implications in data that provide insight and wisdom to take action. Unexpected outcomes begin in the most unlikely places.
Data doesn’t lie as long as we approach it objectively. Sure, we all have bias and we each filter our perceptions through our individual experience. But we can gain wisdom from information that is supported by data. In an increasingly mobile and global society we are, more than ever, in this together.
Q1) What is the difference between data and information?
Q2) How do social strategy and social practice differ in their needs for data and information?
Q3) Actions speak louder than words. How do social strategists and practitioners reconcile what we say vs what data proves?
Q4) In practice, say, as community managers – how do we separate personal bias from what data and information tell us?
Q5) Is it a fine line between business results and a larger societal agenda? Does corporate social responsibility work out in practice?
Q6) In what ways can #datascience, social strategy and social practice combine for the best outcomes?