Strategic Communication employing #ML

Strategic Communication is tough. It is more than just writing/singing/recording something for your social channels. Who will engage with it? What should you talk about? When is it the best time to post it?


What you post must point to the target audience group you want to impact. One of the most efficient ways of doing this is by analysing the content your audience has interacted with before and plan your moves accordingly.

One of our financial clients had interest in growing his audience. We undertook a competitor study and employed Live Natural Language Processing (NLP) of similar audiences to understand what they were interested in. Particularly, topics of 2-3 keywords provided us with a more meaningful result in the Twitter platform than anything else.

By doing this and shifting the content focus from politics to trading, he experienced an increase of engagement between 33-50%.


Why? As an influencer (IN ANY FIELD), you are in the business of breaking news. Therefore, whichever system you have in place needs to enable you to post quickly after RELEVANT EVENTS, targeting the things that are going to make your audience react in that specific situation. This has to be tailored-made to you.

Following the same example, after NLP analysis, it was obvious that bullish markets were the most important kind of events. With this in mind, a second layer of intelligence was applied (in this case a Neural Network, here to know more) to translate that  piece of information into actionable tasks for our client’s content strategy. For him, posting about “teoría de la opinión contraria” instead of following the line of thought of big publications such as the Financial Times was proven to work better.

Know your clients before they know you. In ABACE, we strongly believe that employing ML (Machine Learning) is the most efficient way to better understand your current clients as well as finding your future ones.

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