We know how social media started 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 an opportunity to target potential customers in them.
At present, we know some social media channels have grown in relevance to become the most preferred marketing channels for brands from across industry verticals quickly. They have now overtaken TV, print, flyers, and other traditional forms of marketing.
Naturally, brands are leveraging social media like never before. With smartphone penetration growing by the day and net connectivity and speed rising by the second, you can imagine the information and data overload social channels are experiencing. So much data is there on social channels that no one can ever think of managing them manually.
- 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 before. Today, you don’t have to do the analysis manually and deploy resources and workforce. Instead, ML can do the job more skilfully and faster, 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 quickly processed into relevant pieces.
Machine learning has ensured easy processing of social media data into relevant strands or pieces. So your social media team won’t feel intimidated by the sheer volume of activity on social media. There are tools to track all channels, movements, and brand mentions easily. 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
When machine learning is used, keywords and hashtags are no longer the only determiners of social media data. Big Data can come into play; you can easily create graphs, get more context out of the data, and better understand the target audience. The best thing you can do is a sentiment analysis of the data and know-how how 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. For example, you can easily track the links and see their point of origin. In addition, any changes to the original posts can now be tracked and shown using graphs, giving detailed info regarding references. This can help you consistently bring relevant posts to target your selected users and enhance conversion rates.
Overall, you can 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.