Listening to your customer in Social Media effectively is one of the main headaches of the marketing departments of many companies. This is the step before any strategy; essential to know him and in this way to know what his needs are, how you can approach him, and, most importantly, how to hook him to want to be by your side.
For this it is vital to practice active listening in social networks; with this I do not mean a simple monitoring of some keywords, but goes much further, it is to collect and analyze all kinds of interactions between the user and the brand as well as the users with their environment; in short, any act of communication in Social Media where the brand or its product is present. Probably the most relevant conversations for your brand are taking place outside the limits of your social networks, for this reason it is necessary to be attentive and deploy all the radars. In Social Media, speaking effective listening are bigger words.
In order to capture as effectively as possible the social conversation in the moment, as well as to have a certain orientation in the first instance about it, that allows to make a certain filter against the enormous amounts of information that are continuously spilled in Social Media , special care must be taken in selecting the most representative keywords or terms. It is advisable to play with several combinations of the same, until obtaining the most that allow a more effective monitoring. This requires experience and a lot of dedication; so that, based on trial-error, the results obtained are really useful and contain relevant data for their study.
Fortunately there are advances that allow for an increasingly effective listening, such as Natural Language Processing (NLP) based tools. This system allows, not only to focus on the literal combination of keywords, but, from a previously assigned scales, to extract the intentionality that the user transmits with his message. This software also allows the “learning of the machine”, the assimilation and relation of various terms, according to a statistical frequency.
It goes without saying that monitoring systems are a useful tool, but that human intervention, a professional expert in the field, is necessary to evaluate the degree of interest of each conversation detected, analyze its content and draw conclusions about the message that is collected. This is undoubtedly the most arid and costly part, but also the most important, where we have to allocate the necessary resources to achieve valuable results. It is a kind of great gold mine, where you have to extract with patience the nuggets of this precious material. Do you actively listen to your users? What methods do you use for this?