AI technology, like natural language processing (NLP) and machine learning, is being used to create tools that enable brands to instantly gain insights into social media data. The media update team takes a look at the new ways in which social media intelligence tools are gaining these insights.

But first, what is social media intelligence?

Like media intelligence, social media intelligence is a process that gathers and analyses data to gain insights. Social media intelligence involves collecting data from social media platforms, whereas media intelligence uses data generated by multiple media channels.

The social media intelligence process involves social media monitoring, social listening, and social media analysis.

The results of the social intelligence process is two-fold:
  • actionable insights that can improve business and marketing strategies, and 
  • a deep understanding of both social media user behaviour and consumer preferences that can inform decision-making.
Quick note: Don’t confuse social media intelligence with social listening. Social listening finds insights within social media conversations, but it doesn’t offer the ‘why’. When brands know why users are reacting positively or negatively to their social media posts, they can take action to change how they do things.

How AI transforms monitoring, listening, and analysis:


Social media monitoring

Social media monitoring is the way in which social media intelligence tools gather data that is relevant to a specific business. These tools provide information about campaigns, marketing initiatives, and even data about industry activity on social media.

Monitoring tools allow businesses to track mentions of their brands so that they can gauge public interest. They also notify marketing and PR teams of comments and questions social media users have, or can inform them of topics trending on social media. With this information, teams can create content that taps into these topics.

AI makes finding brand mentions more accurate. Social media monitoring tools are being equipped with NLP. This is a component of AI that allows computers to understand the context of social media users’ posts.

"AI makes finding brand mentions more accurate"
These tools can filter out irrelevant posts to only show teams the posts that mention their brands. By understanding the context of sentences, the technology can pick up when users aren’t mentioning their brand, but are referring to an entirely different topic.

This feat is hard to achieve with tools that don’t use AI. Such tools can find mentions of the brand, even if it is misspelt or abbreviated. It can’t understand the context within which the brand name is used though – and could deliver irrelevant results.
Learn more about this topic in our article, Three ways your brand can use social media monitoring.


Social listening


Social listening tools process the data that was gathered during the social media monitoring process.

A blog post by the social media tracking service amaSocial defines it this way: “The social listening process involves monitoring social media channels for posts that include specific keywords or topics. Then all these posts are analysed to reveal the themes they have in common and the conclusions that can be drawn from them.”

One of the ways in which brands use social listening is to identify topics that are being discussed. With this information, they can create content that taps into those conversations. Businesses can also use this knowledge to understand consumers’ interests and identify trends emerging within their industry.

AI can make this process more accurate. It also allows social listening tools to uncover topics of conversation that they would not have been able to find with conventional technology.

Machine learning, a component of AI, can extract topics such as people, places, brands and products that are being referred to within posts. It does this through the process of ‘entity extraction’.

Entity extraction is a more accurate way of finding topics than simply searching social media posts for keywords. This is because entity extraction can do entity linking, also known as co-referencing, which can identify multiple words that refer to the same concept.

With this information, social media listening tools can notify brands when a topic occurs more and more frequently, allowing the brand to take action based on spot-on information.
Find out why your brand should do social listening in our article, What social listening is useful for.

Social media analysis

As the last piece of the social media intelligence puzzle, social media analysis provides brands with information on why their social media posts or campaigns delivered a specific result. With knowledge like this, businesses not only learn how to improve their social media strategy, but can also better understand their audience and industry.

Social media analysts use sentiment analysis to determine social media user reactions to posts.

“Sentiment analysis shows brands and businesses the percentage of positive and negative media coverage,” Anja van Schalkwyk, senior strategic analyst at Focal Points, told media update in an interview in 2017.

Focal Points, a media analysis company, uses a data engine that relies on both NLP and machine learning, she explained.

“This combination allows the engine we use to rapidly analyse the sentiment of media clips with near-100% accuracy. This automatic analysis process has freed up time for our team to mine deeper insights through qualitative analysis.”

AI allows analysis teams like Focal Points to create in-depth reports about every aspect of a social media campaign. This is also an example of how AI doesn’t replace humans, but simply allow humans to achieve more.

"AI doesn’t replace humans, but simply allow humans to achieve more"
Humans are closely involved in every step of producing technology that relies on machine learning. Learn more in our article, The vital role of humans in machine learning.

AI is changing the way data intelligence companies extract information from social media, how they analyse this data for factors like sentiment, and how they find trends and patterns within thousands of data points.

Brands that rely on the social media intelligence tools that these companies provide receive accurate, data-driven insights that help them make strategic decisions for short and long-term success.
The world of AI can be overwhelming. Learn what you need to know in our article, 10 AI terms every marketer should know.
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