The other side of this content creation issue is when we create all this content, many believe it is being wasted because it is not going to the right audience or just not connecting with our audience. Only until recently, we didn’t have the right tools to understand who is really interested in our content. We tested, did surveys and did our research but if we did have the information, most of the time it was dated and too old to rely on for current use.

Big data mining help change that mindset. We are now seeing big data analysis in real time, giving us more reliable data but again, sometimes this is still not enough to understand who benefits from our content creation. This is where predictive analysis comes into play, not only using real-time data to determine the brand perception, users feedback and current key insights to properly position our product toward the right audience; but also use cognitive learning to determine the most effective messaging, medium and type of content messaging that appeals to their functional, emotional and rational expectations. This is where cognitive learning can determine the best way to reach them based on their behaviors, psychographics, personalities, buying habits and trends by creating personalized messaging that touches them just like a story. These types of storytelling results will connect with an audience and could easily influence their mindset toward a product or solution.