We know how social media started off as a platform for individuals to chat, share and connect to the world. Then, these channels grew in base and reach, and this is when brands saw in them an opportunity to target potential customers.
At present, we know some of social media channels have grown in relevance to become easily the most preferred marketing channels for brands from across industry verticals. They have now overtaken TV, print, flyers and other traditional forms of marketing.
Naturally, brands are leveraging social media like never before and with smartphone penetration growing by the day and net connectivity and speed rising by the second, you can just imagine the information and data overload social channels are experiencing. So much data is there on social channels that no one can think of managing them manually ever.
This is where machine learning (ML) comes into the picture straight away. It’s a sub-branch of artificial intelligence (AI) that can empower computers and devices to classify any volume of data in neat clusters.
- Machine learning is about using a series of algorithms to spot patterns in data
- ML is about a sophisticated way to structure social media posts based on their elements such as text, images, videos etc.
- Brands can leverage machine learning to get clear and result-oriented insights about their target users
- ML can be used to work on real-world data for customer segmentation
- Brands can gain better clues about the tastes, preferences, and demographics of users/authors doing posts on social media
Machine learning is thus empowering social media in different ways, including –
Social media analysis is a breeze now
Machine learning has made social media analysis a lot easier than it was before. Today, you don’t have to do the analysis manually and deploy resources and manpower for that. ML can do the job more skilfully and faster rather, therefore, saving time and money in the process. Plus, you now can get a deep insight into the target or selected users in a cost-effective manner.
Social media data can be easily processed into relevant pieces
Machine learning has ensured easy processing of social media data into relevant strands or pieces. Your social media team won’t feel intimidated by with the sheer volume of activity on social media. There are tools to track all channels, activities and brand mentions with ease. ML and its algorithms will take seconds to slice data of any scale and convert them into meaningful pieces.
More meaning and better context to social media data
Keyword and hashtag are no longer the only determiners for social media data when machine learning is used. Big Data can come into play, you can easily create graphs and get more context out of the data and understand the target audience better. The best thing, you can even do sentiment analysis on the data and know how much happy or negative your customers feel about your product or services.
More knowledge about post generators
Machine learning can help you get more information and knowledge about the individuals or groups generating those posts. You can track back the links and see their point of origin easily. what’s more, any changes to the original posts can now be tracked and shown using graphs and this can also give a detailed info in regard to references. All this can help you bring relevant posts consistently to target your selected users and enhance conversion rates.
In overall, you can clearly see the roles of machine learning in empowering social media manifold. This is why social media consulting services are more in demand now than ever before.