Nowadays, social networks have become relevant ways of communication in organizational contexts and in interpersonal relationships.
This article aims to present a brief reflection on how Data Analytics and Artificial Intelligence can help companies enhance and increase the efficiency concerning the relationship established with their followers on social networks.
In order to understand the extent of the evolution regarding the number of global social network users in recent years, a survey by We Are Social and Hootsuite was consulted, which presents data reflecting the distribution of use over the last 10 years. As we can see in the picture, from January 2012 to January 2022 the number of users has been growing year after year.
Picture – Distribution relative to the number of social network users over the last 10 years. Source: We Are Social and Hootsuite
Bearing this in mind, it becomes challenging to understand how companies can use Data Analytics and Artificial Intelligence to better communicate with their followers/customers.
The greatest benefits associated with their use are related to facilitation in terms of:
- Faster decision making;
- Passing information about products;
- Planning future events;
- Analyzing social media campaigns;
- Ad customization.
Due to the impact of Data Analytics and AI on the construction and segmentation of information to be transmitted, the work of Social Network managers is regarded as more sustained.
Social Media Managers are able to make faster decisions based on defined goals and using techniques such as Sentiment Analysis (through Machine Learning and advanced algorithms it is possible to analyze texts, comments or publications in order to understand whether there is a positive, negative or neutral feeling concerning a brand). Data Analytics also allows for the detection of patterns in large volumes of information, identifying the favorite content of each user and the best platforms and timings to publish.
On the other hand, with Data Science it is possible to segment consumers based on their interests and wishes. This facilitates the publication on social networks of the most relevant product information for each segment and also the best timing.
Also, when planning future events, Data Analytics and AI allow for a more detailed analysis of the events that, in the past, were most and least successful, and understand the factors leading to that. Here, predictive and prescriptive models of Data Analytics are very significant.
Effectively analyzing social network campaigns is important, as it allows us to check if publications have a good level of engagement (number of likes, comments, shares, …), obtain ROI (Return On Investment) and ROA (Return Of Attention)
In order to address the interests and wishes of communication targets, it must be customized, thus becoming an even more effective instrument, since each client is unique. See a practical example of how Data Analytics can help select campaigns here.
Other illustrative examples of the use of Data Analytics and AI on social networks include:
- use of Artificial Intelligence to identify faces in photographs/images and also to segment the target audience (Facebook)
- suggestion of new jobs, networking and the possibility of creating specific posts in the feed (LinkedIn)
Artificial Intelligence and Data Analytics are an essential part of how today’s social networks work and help companies and social media managers in their work.
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