This novel concept is a creative overview of existing concepts, Sequential Content and Content Intelligence have both been moderately addressed in the web literature. However, the synthesis of the two had yet to be examined until now.
Content Intelligence (CI) elevates business semantics, research, production, and distribution. CI employs AI and raw data to optimize content strategy and performance. CI systems tend to operate in the following sequential order :
A four-tiered CI sequence model ensures that each step is maximally executed:
According to [A], content engineers organize the shape, structure, and application of content…(they) define and facilitate the content structure during the entire content strategy, production and distribution cycle from beginning to end.
Content engineers bridge content strategy and development. The engineer does not view content as a static or final asset. Instead, s/he reduces content down to a recyclable quantum state. This omniversal content requires intricate architecture and extensive planning. The engineer further integrates, encrypts, and routes content toward multiple endpoints:
Intelligent engineering is not designed to unnecessarily disrupt existing content pathways. In fact, it refines and expands content elements to maximize their processes over time.
Sequential Content Intelligence™ (SCI) tends to follow the Pareto Law of the vital few (i.e. roughly 80% of results stem from 20% of content). In other words, 20% of produced content tends to yield an 80% increase in online visibility and engagement. Factors involved in this process include the application of "creative spend" toward:
Triberr recommends the following Pareto content intelligence pathway:
In spite of Pareto's Law, "create less, promote more" should not be the de facto approach to successful sequential content development. Instead, identifying and leveraging the 20% of SCI within the marketing stack that garners 80% of results ought to be the proper objective.