According to the Content Marketing Institute, content marketing is:
…a strategic marketing approach focused on creating and distributing valuable, relevant, and consistent content to attract and retain a clearly defined audience – and ultimately, to drive profitable customer action.
Content Marketing is quickly becoming a very popular tool in the toolbox of digital marketers. However, it is also a very challenging domain because different types of customers are attracted to different types of content. So, publishing items to your social media feeds without a clear sense of what you need to accomplish and how your content is supposed to accomplish objectives and digital marketing strategy will be a waste of time and effort.
Your content also has to be targeted to a very specific audience. You must understand the demographics, psychographic and socioeconomics of your target audience in order for you to provide compelling content to them. What are the wants, needs, interests, questions, concerns, and pain points of your prospects? How does your product or service fit into their lives? What expertise do you have that is of use to them? What kind of content could you distribute that would inform, entertain, and engage them in a meaningful way?
In order to target the right customer with the right content at the right time, the content MUST be tagged so that it can be personalized for every context. At the rate that content is generated in today’s fast-paced economy, manual tagging of content is out of question. VUE uses Machine Learning and Natural Language to extract meaning from the content. Content comes in various forms, from structured to semi-structured and unstructured; In order to make the content more conducive to information discovery and personalization, it must be tagged in a way that maps naturally to user search queries. VUE™ allows auto-categorization and tagging of content using concept tagging, sentiment analysis, and keyword and entity extraction using domain-specific topic modeling and machine learning. As every organization’s content is as unique as their business model, simply applying generic natural language processing algorithms to highly specialized content is not sufficient. VUE™ provides the ability to learn classification and attribution by using an organization’s own content as a training set for generating machine learning models that predict and suggest tags for new and updated content.
It would be a fallacy to say that optimizing content discovery and targeting is a one-time or infrequent process. Those who have concerned themselves with this task know that maintaining relevancy is a balance between art and science – one that requires constant refinement. Current events and trends,, social influence, customer demographics, psychographics and even weather play a role in what customers are interested in. In the past, content distributors attempted to improve content relevancy by creating a myriad of business rules and exceptions which proved unmanageable and ultimately failed to address the core of the problem – the content. Content must be tagged correctly, dynamically, automatically and perpetually in order for us to keep up with the demand and the pace.