Technology is leading us towards new paradigms for the use of content, and it is natural to ask ourselves what contributions automation and Artificial Intelligence will bring to Content Marketing strategies, especially for those companies where editorial production is not the core business.
A small premise is necessary: the two terms are frequently used as if they were interchangeable, but they’re not. Automation indicates software that only follows pre-programmed rules. The added value comes when it is integrated with AI algorithms that can identify models and predictions from the analysis of large amounts of data.
We are at an advanced stage of technology, but we are lagging behind when it comes to the use of this technology in optimizing the processes of creation, distribution and customization of content.
The current situation
Although there has been considerable investment in hyper-automation and hyper-segmentation, there is a lack of strictly necessary skills, and this is partly due to an underground resistance, a fear that human creativity is threatened by technology.
In reality, automation and AI do not kill the creative part of communication, but on the contrary, they maximize it: by saving our time, they allow us to devote ourselves to the development of really relevant aspect for brands and users. We can say they take us to a new level of intelligence.
In addition to the prejudice we just mentioned, this cultural evolution is also held back by data silos: the various channels and processes (social, SEO, etc.) are separate and are often managed in divergent ways.
The consumer's funnel has to be analyzed transversally, and data is a fundamental component to guide the creative part of communication. Business Analysis and Data Science techniques can help marketers collect and exploit this data.
The relevance of messages
Although many companies are not strictly editorial realities, they are becoming media companies. The disintermediation of the Net has allowed them to address people directly, through social media and proprietary channels (blogs, aggregators, magazines, etc..).
In order to emerge as a certified and recognized source by users, the service of information offered must be top quality, and in this regard many journalistic techniques are helping companies’ Content Marketing strategies (brand journalism). Traditional media, on the other hand, are penalized because they are not investing enough to fill the skill gap.
Social media are very important in this process of relevance. The data flow that comes from them is analyzed by AI algorithms with a selective intelligence (which is therefore able to select the right inputs), providing the company with a “compass of prediction” for the following actions.
Just to make an example, it could help us identify the critic elements we need to intervene on (crisis management). And much more.