Monetizing AI in Social Media: 6 Ways AI Can Monetize Big Data (update: 2024)

Artificial Intelligence (AI) in Social Media

Nowadays, social media is undergoing a transformation thanks to AI and technologies such as machine learning. ML leverages big data sets in order to get insights and optimize business processes. In fact, social media produces huge amounts of data every day. Mostly it’s content, comments, customer interactions, etc. To gain information about each individual user of your platform you need to translate that data.

Digital marketers should use machine learning in marketing to better understand buyer persona, increase lead generation, improve customer experience, and as a result – increase sales and conversion rates. Moreover, it is possible to encourage social media engagement with AI personalization engines that will match the preferences of each individual person. How can AI in social media actually impact your marketing and analytics? And how to actually start using artificial intelligence in social media?

Below you will discover different ways in which machine learning and AI are transforming social media today.

Why is artificial intelligence important for social media?

Artificial intelligence can help with social media marketing in two ways:

Reduce your expenses

AI in social media can automate processes like scheduling and uploading reposts, getting relevant links and hashtags, and learning what is easier and faster to publish, allowing your team to focus on more important tasks.

Increase your income

Artificial Intelligence in social media may also significantly improve the performance of your social media content and strategy, leading to increased engagement and return on investment. Furthermore, AI in social media can assist you in determining which posts will be the most effective, which audiences are the most relevant, and which channels are performing best.

7 AI applications in social media

Content personalization

The first example of artificial intelligence in social media is content personalization. AI algorithms and machine learning in marketing analytics are specifying the preferences of each user and then recommending appropriate content for them. Additionally, AI algorithms can recommend more articles to read (or videos to watch) which increases the time of using the web service. In other words – AI in social media offers an effective recommendation system.

This kind of content personalization and recommendation engine solution increases and improves user experience (UX) which directly converts to a time users spend on the website and as a result in their monetization. The rule of this example of artificial intelligence is very simple – show the right content at the right time for the right person.

Content popularity prediction

The second example of artificial intelligence in social media is content popularity prediction. It is highly beneficial to be able to predict what will be popular tomorrow. Forecasting daily demand for content will give you the possibility to prioritize content on your website.

With AI in social media, you will be able to properly arrange content on the website according to customers’ preferences. Content popularity prediction in the example of artificial intelligence that helps companies to plan content publications, their topics, and a specific user group target.

Nowadays, social media allows consumers to become contributors and distributors of created content. It led to an exponential growth in the amount of information and has resulted in an online competition for consumer attention! For the past few years, enterprises have been observing particular content popularity dynamics and have been trying to understand what makes one piece of text more popular than another.

How to predict content popularity? Such example of artificial intelligence is used in different areas of social media, the Internet, and some platforms such as Netflix e.g.

Customer churn prediction

Another use of AI in social media – customer churn prediction. Companies try to predict which client is most likely to stop using their platform or delete the profile. Such information can help to maintain relationships with high risk customers. That is highly valuable because the cost of acquiring the client is 5 times greater than the cost of maintaining one.

Read more about Customer churn prediction in our article “Customer Churn Prediction using Machine Learning (How To)” or about AI technology: Machine Learning in Sales.

Customer lifetime value prediction (LTV)

Companies try to predict how much money a particular customer will spend on the platform. By analyzing their behavior on social media and digital platforms, artificial intelligence can determine their habits and what encourages them to spend money.

Read also our article: “Customer Lifetime Value (LTV) Prediction using Machine Learning“.

AI for sentiment analysis of posts on social media

One more example of artificial intelligence in social media which are used by many platforms is sentiment analysis of posts. Entrepreneurs try to detect negative comments (with bad mood) and respond properly to them. It helps to verify how the influencer’s post is received. It is important e.g. for FMCG or production companies to be aware of the opinions about their new products in social media.

Then companies are able to interact with existing or potential customers and better understand their expectations and needs.

Post subject image personalization

It is being used to match the best image to each customer – based on their preferences. It helps to maximize the post-opening conversion. Users are more likely to click on articles that have a background similar to their favorites. Personalization always helps in increasing customer loyalty and as a result, improves sales and customer monetization. Such solutions are being built with the help of advanced AI technologies such as Computer Vision.

Influencer marketing

Most of the already mentioned solutions are also used in the influencer marketing industry. This is a very hot topic and a new way for companies to leverage analytics and data from social media in order to boost their marketing campaigns. AI together with influencer marketing platforms give an opportunity for marketers to understand their audience perfectly and choose the right influencer for a planned marketing campaign.

Influencer marketing platforms with the help of AI engines are able to process huge amounts of data, detect audience demographics, and match the right influencer’s account to the planned marketing campaign.

AI algorithms in your favourite social media

Facebook

Facebook AI is the term of the social media giant’s artificial intelligence inner workings. Facebook’s artificial intelligence capabilities start with text. Facebook uses an artificial intelligence tool called Deep Text to analyze comments, posts, and other data generated by Facebook to understand how people use different languages, slangs, acronyms and exclamation marks to learn context. Facebook is testing Recommended Answers in Messenger, which provides the following logical response to a message from a friend or family member, as part of this development.

Source: digitalinformationworld.com

Also, Facebook image recognition (a type of AI) identifies what happens in images without human signatures or tags, allowing users to search for photos using keywords even if they’re not annotated.

Today, artificial intelligence (AI) affects what you see on Facebook depending on your interests and what your friends are interested in.

Twitter

Artificial intelligence in social media like Twitter is mainly used to determine which tweets should be recommended to users in a timeline. It aims to provide users with the most relevant tweets to enhance a personalized experience. What’s more, Twitter uses IBM Watson and Natural Language Processing (NLP) to track and remove offensive posts. Watson not only understands natural language, but it also interferes with message tones and the meanings of other visual aspects, helping it to analyze millions of inappropriate messages in seconds.

LinkedIn

Another example of AI social media is LinkedIn. LinkedIn uses machine learning to figure out what happens in real time when a user is on the platform. The most common uses of AI on Linkedin are:

• Providing users with job recommendations
• Recommendations for profile connections
• Showing useful content in the feed

Source: engineering.linkedin.com

Like Facebook and Twitter, LinkedIn uses artificial intelligence to manage malicious content. LinkedIn defines a set of words and sentences that should be avoided. Therefore, the account will be deactivated as soon as the profile posts content that appears on the blacklist.

TikTok

The social network TikTok is a huge success around the world and relies heavily on AI. Using an algorithm, it quickly learns user preferences in order to make personal suggestions. TikTok uses AI to train algorithms to increase engagement. The more you interact with a particular type of video, the more related content you will see in the future. Every day, TikTok optimizes its algorithm to predict what will keep you on the platform for a little longer.

Source: medium.com

Read more about Addictive TikTok’s algorithms.

To sum up – AI in social media

AI is continually transforming social media in the digital age, from improving user experience to finding more effective ways to advertise items.

AI is increasingly being used by organizations to manage different elements of their day-to-day operations, including social media marketing platforms. It’s not for nothing that AI in social media industry is estimated to hit $ 2.1 billion by 2023. [1]

If you want to discuss how exactly your company can take advantage of machine learning, drop us a line, we are always happy to help.

Also check out our machine learning services to learn more.

References

[1] Marketsandmarkets.com. AI in Social Media Market worth $2,197.1 Million by 2023. URL: https://www.marketsandmarkets.com/PressReleases/ai-in-social-media.asp?_ga=2.197518892.220028759.1635491996-1972492488.1635491996. Accessed Oct 29, 2021.